1) What is ToR and discuss attacks that are possible on it. Install ToR on your system and compare and contrast it with a regular search engine like Google. answer:or (an acronym for The Onion Router) is essentially a network that masks online traffic. Tor browser is an open-source platform managed by volunteers and, due to its onion routing, creates anonymity for users who access websites and servers through this network. The browser is often used legitimately by journalists and other users who need to protect their identities, for example, while investigating the opposition in a legal dispute, or researching competitors. So, what is a Tor browser? In the simplest terms, Tor browser is a software that allows users to browse the internet with a relatively high degree of privacy. The network and browser take their name from the fact that they direct all web activity through several routers—called nodes—much like going through the layers of an onion, making it difficult to track and identify users. However, there is a close association between Tor and the dark web because the Tor browser is often used for illicit activity, even though there was never any intention for Tor to enable criminality. Although the Tor browser is legal in many countries, some do not allow residents to access the network. How does a Tor browser work? So how does Tor work? In its simplest form, a Tor browser use onion routing to direct and encrypt all traffic, offering users a high level of anonymity. The network transmits traffic through three layers of international network nodes called onion routers: Entry nodes, which form the first layer of encryption and enable the connection to the Tor network. A series of middle nodes fully encrypt web traffic to ensure anonymity. Exit nodes, which further encrypt data before it reaches the final server. Because onion routing effectively encrypts and relays data through multiple network layers, the Tor browser is highly effective at protecting user data and concealing IP addresses. What is the Tor browser used for? There are several questions worth asking about Tor, including “What does a Tor browser do?” and how its use differs from regular browsers. The Tor browser is primarily a way to browse the web anonymously. As such, the main reason it is used is to avoid surveillance and ensure privacy while online. However, many people also use Tor to access services that regular browsers cannot reach, such as .onion sites which only function on the onion network, such as DuckDuckGo, a privacy-enhanced search engine, which offers a .onion version of its search engine, which doesn't track user data, providing a more private search experience. In addition, because Tor is closely linked with the dark web, some users use this for particular types of research, and also to carry out illegal activities. Benefits of a Tor browser The Tor browser does have several advantages, which is why some internet users can benefit from using it. However, not all of these will be relevant to regular internet users. Here are some of the main reasons why some users choose to use a Tor onion browser: The browser is a free, open-source program IP addresses and browsing history are masked Enjoy heightened network security because the Tor browser operates on secure, encrypted networks Easy access to non-indexed pages, especially through search engines Disadvantages of Tor browser Aside from security concerns and wondering “is the Tor browser safe,” there are some other potential disadvantages of using this software. Below are a few things to keep in mind before deciding to use the Tor onion browser. Because of the way it routes traffic, Tor connections are very slow, especially when compared to VPNs, and downloading large files is not practical. Activity may not be completely anonymous, and it is possible to decrypt a user’s identity Some countries and companies can block the Tor browser, and its usage can even be illegal in certain countries. The use of this browser can be suspicious, even if it is legal Not all websites function on Tor What are the differences between the Tor browser, proxy servers, and VPNs? While the Tor browser, proxy servers, and VPNs all offer some form of anonymity, they differ slightly in how they work and the levels of protection they provide. Proxy servers essentially function as an intermediary between a user and the websites they access. While they do obscure IP addresses and geographical locations, they do not encrypt data and online activity. Because of this, user data remains exposed and can easily be tracked and hacked. So, is Tor safe compared to proxy servers? Yes, to an extent. Despite the weaknesses outlined above, the Tor browser offers a much higher level of encryption and routing, giving users more anonymity. While using a proxy server alongside the Tor browser can help mask the use of Tor, using both a proxy server and Tor browser will not offer any further protection to users. Virtual private networks (VPNs) are powerful networks that fully encrypt all web traffic by routing it through different servers, thereby also obscuring the user’s IP address. The most significant difference between VPNs and the Tor browser is that VPN is operated by central providers who operate the network, while the latter is a decentralized network managed by volunteers. Additionally, Tor routes data through independent nodes, while VPNs route online traffic through remote servers. Is the Tor browser safe to use? Because of the close association between Tor and the dark web, many users rightfully wonder “Is Tor safe to use”? With an understanding of what the Tor browser is, the answer to that question—generally—is yes. Because of its onion routing protocols and data encryption, the Tor browser offers a reasonably high level of privacy and protection when used correctly. Of course, like any other browser, it is still vulnerable to an array of online attacks, such as malware and phishing. Here are a few security concerns to be aware of: The final part of the data relay on the Tor network—between the exit node and destination server—is not encrypted, giving third parties an opportunity to monitor and track web traffic. It may still be possible for third parties to deploy fingerprinting to identify users; for example, if they use Tor to access compromised websites with JavaScript enabled, it can be possible to track mouse movements. Tor onion browser is still vulnerable to being compromised by security bugs. It is important to use the latest versions of Tor browsers, as obsolete versions may have various vulnerabilities, enabling malicious actors to impersonate the user. In a practical sense, the answer to the question of “Is the Tor browser safe?” is that it is secure if the user has a good amount of cybersecurity knowledge. There are numerous measures that users can take to further protect their data and identities if they plan to use Tor. However, there are limits to the anonymity the Tor onion browser can provide. Specifically, internet service providers (ISPs) and network administrators can still be able to see that Tor is being used. How to stay safe while using the Tor browser Many users wonder “How to stay safe while using the Tor browser?” and this is indeed a fair question. As with anything else online, there is an inherent risk with using a Tor browser. However, users can take steps to mitigate these and be mindful of their online activities. Here are a few tips for safely using the Tor browser: Ensure that the Tor browser and any associated apps or extensions are always up to date. Use the Tor browser in conjunction with a VPN. Employ a firewall to protect the computer’s network. Use antivirus software. Avoid logging into personal accounts, such as social media profiles or emails. Use the Tor browser randomly, so that it is hard to create identifiable patterns. Use the highest level of security available on the chosen Tor browser, so that it executes the least amount of browser code and helps protect devices from malware. Use an extension that protects your privacy and only accesses secure HTTPS websites, such as extensions that will automatically rewrite a URL to use HTTPS instead of HTTP. Tor browser: A different way to use the internet Despite Tor and the dark web being closely linked, using Tor browser doesn’t mean involving in illicit activities. It can be very useful software to certain internet users. Because of how it operates, Tor is generally safe to use, and Tor onion browser offer several benefits like heightened safety and privacy. Before using the Tor browser, though, users should be aware of any potential legal issues with Tor in their country, and that they could be flagged for its use. Get Kaspersky Premium + 1 YEAR FREE Kaspersky Safe Kids. Kaspersky Premium received five AV-TEST awards for best protection, best performance, fastest VPN, approved parental control for Windows and best rating for parental control Android. 2) Use the web site http://testphp.vulnweb.com/ for the following. Perform sql injection on it and retrieve the user table and its contents. answer:SQL Injection (SQLi) is a type of an injection attack that makes it possible to execute malicious SQL statements. These statements control a database server behind a web application. Attackers can use SQL Injection vulnerabilities to bypass application security measures. They can go around authentication and authorization of a web page or web application and retrieve the content of the entire SQL database. They can also use SQL Injection to add, modify, and delete records in the database. An SQL Injection vulnerability may affect any website or web application that uses an SQL database such as MySQL, Oracle, SQL Server, or others. Criminals may use it to gain unauthorized access to your sensitive data: customer information, personal data, trade secrets, intellectual property, and more. SQL Injection attacks are one of the oldest, most prevalent, and most dangerous web application vulnerabilities. The OWASP organization (Open Web Application Security Project) lists injections in their OWASP Top 10 2017 document as the number one threat to web application security. SQL Injection How and Why Is an SQL Injection Attack Performed To make an SQL Injection attack, an attacker must first find vulnerable user inputs within the web page or web application. A web page or web application that has an SQL Injection vulnerability uses such user input directly in an SQL query. The attacker can create input content. Such content is often called a malicious payload and is the key part of the attack. After the attacker sends this content, malicious SQL commands are executed in the database. SQL is a query language that was designed to manage data stored in relational databases. You can use it to access, modify, and delete data. Many web applications and websites store all the data in SQL databases. In some cases, you can also use SQL commands to run operating system commands. Therefore, a successful SQL Injection attack can have very serious consequences. Attackers can use SQL Injections to find the credentials of other users in the database. They can then impersonate these users. The impersonated user may be a database administrator with all database privileges. SQL lets you select and output data from the database. An SQL Injection vulnerability could allow the attacker to gain complete access to all data in a database server. SQL also lets you alter data in a database and add new data. For example, in a financial application, an attacker could use SQL Injection to alter balances, void transactions, or transfer money to their account. You can use SQL to delete records from a database, even drop tables. Even if the administrator makes database backups, deletion of data could affect application availability until the database is restored. Also, backups may not cover the most recent data. In some database servers, you can access the operating system using the database server. This may be intentional or accidental. In such case, an attacker could use an SQL Injection as the initial vector and then attack the internal network behind a firewall. There are several types of SQL Injection attacks: in-band SQLi (using database errors or UNION commands), blind SQLi, and out-of-band SQLi. You can read more about them in the following articles: Types of SQL Injection (SQLi), Blind SQL Injection: What is it. To follow step-by-step how an SQL Injection attack is performed and what serious consequences it may have, see: Exploiting SQL Injection: a Hands-on Example. Simple SQL Injection Example The first example is very simple. It shows, how an attacker can use an SQL Injection vulnerability to go around application security and authenticate as the administrator. The following script is pseudocode executed on a web server. It is a simple example of authenticating with a username and a password. The example database has a table named users with the following columns: username and password. # Define POST variables uname = request.POST['username'] passwd = request.POST['password'] # SQL query vulnerable to SQLi sql = “SELECT id FROM users WHERE username=’” + uname + “’ AND password=’” + passwd + “’” # Execute the SQL statement database.execute(sql) These input fields are vulnerable to SQL Injection. An attacker could use SQL commands in the input in a way that would alter the SQL statement executed by the database server. For example, they could use a trick involving a single quote and set the passwd field to: password' OR 1=1 As a result, the database server runs the following SQL query: SELECT id FROM users WHERE username='username' AND password='password' OR 1=1' Because of the OR 1=1 statement, the WHERE clause returns the first id from the users table no matter what the username and password are. The first user id in a database is very often the administrator. In this way, the attacker not only bypasses authentication but also gains administrator privileges. They can also comment out the rest of the SQL statement to control the execution of the SQL query further: -- MySQL, MSSQL, Oracle, PostgreSQL, SQLite ' OR '1'='1' -- ' OR '1'='1' /* -- MySQL ' OR '1'='1' # -- Access (using null characters) ' OR '1'='1' %00 ' OR '1'='1' %16 Example of a Union-Based SQL Injection One of the most common types of SQL Injection uses the UNION operator. It allows the attacker to combine the results of two or more SELECT statements into a single result. The technique is called union-based SQL Injection. The following is an example of this technique. It uses the web page testphp.vulnweb.com, an intentionally vulnerable website hosted by Acunetix. The following HTTP request is a normal request that a legitimate user would send: GET http://testphp.vulnweb.com/artists.php?artist=1 HTTP/1.1 Host: testphp.vulnweb.com HTTP request a legitimate user would send The artist parameter is vulnerable to SQL Injection. The following payload modifies the query to look for an inexistent record. It sets the value in the URL query string to -1. Of course, it could be any other value that does not exist in the database. However, a negative value is a good guess because an identifier in a database is rarely a negative number. In SQL Injection, the UNION operator is commonly used to attach a malicious SQL query to the original query intended to be run by the web application. The result of the injected query will be joined with the result of the original query. This allows the attacker to obtain column values from other tables. GET http://testphp.vulnweb.com/artists.php?artist=-1 UNION SELECT 1, 2, 3 HTTP/1.1 Host: testphp.vulnweb.com SQL injection using the UNION operator The following example shows how an SQL Injection payload could be used to obtain more meaningful data from this intentionally vulnerable site: GET http://testphp.vulnweb.com/artists.php?artist=-1 UNION SELECT 1,pass,cc FROM users WHERE uname='test' HTTP/1.1 Host: testphp.vulnweb.com SQL injection using the UNION operator with a FROM clause How to Prevent an SQL Injection The only sure way to prevent SQL Injection attacks is input validation and parametrized queries including prepared statements. The application code should never use the input directly. The developer must sanitize all input, not only web form inputs such as login forms. They must remove potential malicious code elements such as single quotes. It is also a good idea to turn off the visibility of database errors on your production sites. Database errors can be used with SQL Injection to gain information about your database. If you discover an SQL Injection vulnerability, for example using an Acunetix scan, you may be unable to fix it immediately. For example, the vulnerability may be in open source code. In such cases, you can use a web application firewall to sanitize your input temporarily. To learn how to prevent SQL Injection attacks in the PHP language, see: Preventing SQL Injection Vulnerabilities in PHP Applications and Fixing Them. To find out how to do it in many other different programming languages, refer to the Bobby Tables guide to preventing SQL Injection. How to Prevent SQL Injections (SQLi) – Generic Tips Preventing SQL Injection vulnerabilities is not easy. Specific prevention techniques depend on the subtype of SQLi vulnerability, on the SQL database engine, and on the programming language. However, there are certain general strategic principles that you should follow to keep your web application safe. Train and maintain awareness Step 1: Train and maintain awareness To keep your web application safe, everyone involved in building the web application must be aware of the risks associated with SQL Injections. You should provide suitable security training to all your developers, QA staff, DevOps, and SysAdmins. You can start by referring them to this page. Don’t trust any user input Step 2: Don’t trust any user input Treat all user input as untrusted. Any user input that is used in an SQL query introduces a risk of an SQL Injection. Treat input from authenticated and/or internal users the same way that you treat public input. Use whitelists, not blacklists Step 3: Use whitelists, not blacklists Don’t filter user input based on blacklists. A clever attacker will almost always find a way to circumvent your blacklist. If possible, verify and filter user input using strict whitelists only. Adopt the latest technologies Step 4: Adopt the latest technologies Older web development technologies don’t have SQLi protection. Use the latest version of the development environment and language and the latest technologies associated with that environment/language. For example, in PHP use PDO instead of MySQLi. Employ verified mechanisms Step 5: Employ verified mechanisms Don’t try to build SQLi protection from scratch. Most modern development technologies can offer you mechanisms to protect against SQLi. Use such mechanisms instead of trying to reinvent the wheel. For example, use parameterized queries or stored procedures. Scan regularly (with Acunetix) Step 6: Scan regularly (with Acunetix) SQL Injections may be introduced by your developers or through external libraries/modules/software. You should regularly scan your web applications using a web vulnerability scanner such as Acunetix. If you use Jenkins, you should install the Acunetix plugin to automatically scan every build. 3) What are Deepfakes? Discuss how they are being used for Impersonation attacks. Explain how they can be countered. answer:What is a deepfake anyway? In May 2019, a Youtuber called “ctrl-shift-face" uploaded a video interview of actor Bill Hader doing celebrity impressions. At first glance, it appears Hader is using his comedy chops to impersonate famous people. Hader even launches into the famous “Arnold Schwarzenegger” voice, inflecting the Austrian superstar’s European drawl. While a bit dated, this example helps illustrate when deepfakes really breached mainstream pop culture. Over the years, deepfakes have become even more popular. Unlike other common impersonations of Ahnold, what’s unique about this video isn’t Hader’s impression but what happens as he impersonates Arnold’s voice. His face eerily becomes the former governor’s, as if he was wearing a digital mask. It was as if Schwarzenegger was sitting in the studio talking to the audience. The video is entertaining, but there’s an eerie quality about how similar Hader looks to Schwarzenegger. Comments underneath the synthetic media clip say things like “After he started looking like Arnold, I forgot what he actually looks like,” “I thought I was hallucinating,” and “he even looks like him lol.” The term “deepfake” often refers to a doctored video — like the Hader/Schwarzenegger impression — that uses Artificial Intelligence (AI) and facial recognition technology to mimic facial expression and characteristics of one person and superimpose it on another person's body. And video isn't the only deepfake medium out there. Voice, image, and even biometric deepfakes also exist. Entertaining in this light, the ability to create fake and convincing facsimiles of other people serious implications for the real world, and identity lifecycles. Deepfakes and have become a popular digital tool to create synthetic media Consumers, businesses, and governments alike are debating the implications of deepfakes especially after its recent uses in nefarious purposes like fake news and deceptive media that could potentially affect national elections. Here’s our own SVP of Identity, Chris Briggs with an interview about staying ahead of the deepfake curve. As Briggs states, and as this blog series helps make clear, “It takes a multi-layered strategy to defend against a lot of the emerging AI attack vectors” like deepfakes. Companies that take the time to understand deepfakes can better “build countermeasures to combat new approaches before they become full-blown security holes.” Learn more about deepfake solutions In this deep dive on deepfakes, we discuss: What is a Deepfake? Where did Deepfake technology come from? How do you make a Deepfake? How do you spot a Deepfake? Can deepfakes be used in new account opening and account takeover fraud? How does a company fight Deepfakes in 2024? A deepfake is a technology that typically belongs to fraudsters. They create the fake media using machine learning and artificial intelligence algorithms to alter videos, emulate forgeries of people doing or saying malicious things, creating convincing synthetic audio, and other forms of fake content where humans are present. Con artists can even generate deepfakes from existing images to create places, people, and things that are entirely synthetic. People have used deepfake technology for a variety of purposes from fun to malicious. For example: Biometrics like facial expressions are generated and superimposed onto another person’s body in fake videos Human voices matching the timbre and pitches of celebrities make like Jay-Z singing Billy Joel in deepfake audio recordings Politicians saying things they’ve never said before. As the technology gets better, fraudsters will likely continue to use malicious deepfakes for cybercrimes and corporate espionage. Where did deepfake technology come from? The first known deepfakes were likely AI-generated videos published at the start of 2017 by a Reddit user to the platform. Today, the user has been credited as deepfakes’ creator, bringing the overall practice into public view. Deepfake creators often used open-source image libraries like Google image search, social media websites, stock photo databases, tensorflow, and YouTube videos to create a machine-learning algorithm which allowed the user to insert people’s faces onto pre-existing videos frame by frame. Although there are glitches and obvious catches a user can notice, the videos are quite believable and are only getting more convincing as more users continue to experiment. At the time, the deepfake creator even created and released an app called “FakeApp,” making it easier for even basic, less tech-savvy users to create fake content from funny videos to those with more malicious aims. Today, there are likely hundreds of deepfake generators. How do you make a deepfake? Deepfake creation doesn’t have the lowest bar to entry, but it’s not super difficult, either, especially given the proliferation of DIY tools. Bad actors likely have some combination of a super-powered computer, artificial intelligence and machine learning programs, and hundreds of thousands of images of selected people. Here’s the process for a deepfake video: First, a user runs thousands of facial pictures of two selected people through an encoder – an artificial intelligence algorithm that uses a deep, machine learning network The encoder compares the images of the two faces, compressing them into shared common features. A second AI algorithm called a decoder recovers the faces from the compressed images. Multiple decoders may be used: one to find and analyze the initial person’s face, the other to do same to the second person’s face. To perform the face swap, a user feeds the encoded images of person A’s face into the decoder trained on person B. The decoder then reconstructs the face of person B with the expressions and orientation of face A and vice versa. For the more convincing fake content (or malicious deepfakes), this will be done on thousands of frames. Another method to create deepfakes use a generative adversarial network (Gan). The notable difference here is the Gan creates an entirely new image/video that looks incredibly real, but is entirely fake. Here’s how it works: A Gan pits two artificial intelligence algorithms against each other. The first algorithm, known as the generator, is fed a noise signal and turns it into a fake image. This synthetic image is added to a discriminator – another algorithm that’s being fed a stream of real images The two components (generator and discriminator) are functionally adversarial, and they play two roles against each, like a “forger and a detective” described by Shen et al, students who used a GAN to create deepfakes in a study at UCSD. The process is repeated countless times with the discriminator and generator both improving. After a while, the generator will start producing a realistic image, or deepfake. This could be a person, place, or thing. To take a deep fake to the next level, Tom Cruise’s fake face must have a fake Tom Cruise voice. Layering audio onto deepfakes typically happens in one of three ways. Replay-based deepfakes, which use a microphone recording[1] or cut-and-paste techniques to cobble a new audio string together from existing voice snippets. Speech synthesis, which often uses a text-to-speech system to create real-sounding audio from a written script.[2] Imitation-based voice deepfakes, which transform an actual speech clip from one subject to make it sound as if another subject is saying it.[3] Can deepfakes be used for fraud? How? Instagram users share more than 1 billion images daily on the platform.[4] Google likely has even more selfies of people in the petabytes it stores. As a result, most people have some type of digital fingerprint – whether that’s a LinkedIn account profile picture, or family photos shared on Facebook (these items encompass a behavioral biometric profile). All these pictures are potential inputs for AI to begin creating convincing Deepfakes for deceptive media. Deepfakes have been used for spoofing famous people, account takeovers, political tricks, extortion, fraud, and revising existing formatting of entertainment and art, and more innocuous meme creation in social media circles. One example, shows how con artists can leverage the technology to blackmail even high-ranking executives. The CEO of an energy company believed he was on the phone with his boss and following orders when he immediately transferred €220,000 (approx. $243,000) to the bank account of a Hungarian supplier. It turns out, the audio on the phone was actually an audio deepfake the fraudsters had created. As the technology improves and becomes commoditized, it could be used for identity-theft and other cybercrimes including fraudulent account opening and account takeover. Bad actors can use deepfakes for various types of fraud, including: New account opening fraud: Using the methods to create a deepfake described above, a fraudster could look on a social network and collect hundreds of images to create a deepfake image or audio, and add that to a synthetic identity: an amalgamation of stolen identity info. If it’s good enough, the fraudster could use the compelling deepfake and identity to open a new account at bank, take out hundreds of thousands in loans, and bust out without paying interest leaving the bank with monetary losses. Tough break. Account takeover fraud: In 2022 alone, nearly 2,000 data breaches impacted hundreds of millions of individuals.[5] Some of those data breaches might have included Biometrics databases perpetrators can create fakes that mimic biometric data and trick systems that rely on face, voice, vein or gait recognition. Phishing scams: Modern phishing attempts have incorporated fake video messages, which are often personalized and tailored to the target. Using deepfake technology, scammers can generate video clips of trusted figures, celebrities, or even family members, asking the recipient to undertake certain financial actions, making the deceit seem all the more authentic. Like the example of the unwitting CEO and the fake Hungarian supplier, fraudsters also use voice-imitation techniques to simulate calls from trusted entities. These fake audio calls can be convincing enough to persuade individuals to share sensitive information or transfer funds to unauthorized accounts. Impersonation attacks: Again, the fake Hungarian supplier comes into the spotlight. Like that fraudster, others use deepfakes to mimic corporate executives or even high-ranking government officials. Successful fakes can trick employees into divulging sensitive information or money. In the case of government officials, this information passed to bad actors may even be considered espionage. Synthetic identity theft. Criminals may even create entirely fake personas. They do so by generating entirely new, fictitious identities complete with photos, voiceprints and even background stories by harvesting pieces of legitimate identity information and cobbling them together. These synthetic identities can then be used to open bank accounts, apply for credit cards, or even commit large scale financial fraud, making it hard for authorities to trace back to a real individual. Scam artists will use these various forms of deepfakes to commit fraudulent financial transactions. By manipulating audio or video to mimic an actual person (or fabricate a new identity), bad actors can forge verbal or visual approvals for everything from a wire transfer to a loan application. They’ll use deepfakes and other forms of fraud for financial gain, to damage to reputations or to sabotage a competitive company or even government. In part two of this blog post, we’ll examine how organizations can spot and even set up better safeguards to prevent against deepfakes and other types of fraud. PART 2 What are the solutions for deepfakes? Detecting deepfakes is a hard problem. Poorly done or overly simplistic deepfakes can, of course, be detected by the naked eye. Some detection tools can even spot more faulty characteristics. But artificial intelligence that generate deepfakes are getting better all the time, and soon we will have to rely on deepfake detectors to flag them to us. To counter this threat, it’s important to make sure companies and providers use two- or multi-factor authentication. Multi-factor authentication approaches layer various forms of verification on top of one another to create more obstacles for fraudsters. For example, facial authentication software may include certified liveness detection that provides an additional safeguard against deepfakes. And because sophisticated deepfakes can spoof common movements like blinks and nods, authentication processes must evolve to guide users through a less predictable range of live actions. Detecting deepfakes in financial scams In an era where deepfakes are increasingly being used in financial scams, safeguarding against them is increasingly important. Fortunately, as technology advances, methods to detect these scams are also evolving. Organizations can employ the following strategies to detect and counter deepfakes, which will be especially important in the financial services realm. Visual analysis Deepfakes, while sophisticated, often display inconsistent facial features. AI struggles to replicate minute facial expressions, eye movements, or even the way hair and facial features interact. Algorithms that generate deepfakes can also show unnatural lighting and shadows. Visual analysis may uncover shadows inconsistent with the light source or reflections that do not align correctly. Verification While deepfakes can replicate voices, they might also contain unnatural intonations, rhythms or subtle distortions that stand out upon close listening. Voice analysis software can help identify voice anomalies to root out deepfakes. Implementing authentication processes that layer codes or follow-up questions on top of voice commands can help ensure the request is genuine. Where files are concerned, automated document-verification systems can analyze documents for inconsistencies, such as altered fonts or layout discrepancies, that might indicate forgery. Multi-factor authentication The name of the game is layered security. Adding facial, voice, or other biometric recognition adds another hoop for a scammer to jump through even if they manage to impersonate a voice or face. Device recognition can help verify that requests are from previously authenticated or recognized devices is also an option for multi-factor authentication. Blockchain and digital signatures Blockchain technology promises an immutable record of all transactions. By using digital signatures and blockchain ledgers, organizations can implement provenance tracking for financial transactions to ensure the authenticity and integrity of financial instructions. Any unauthorized or tampered transaction would lack the correct signature, flagging it for review. Whatever approach organizations take, layering various authentication factors on top of one another is paramount for preventing deepfake-enabled fraud. The other key to robust protection against deepfake is to implement continuous verification. Rather than verify identity once at sign up, organizations must integrate verification measures during the entire customer experience, even after their account has been set up. Some companies routinely invoke identity verification (for strong security, it is important to understand authentication vs. verification) whenever a dormant account suddenly becomes active for high-value transactions, or when passive analytics indicate elevated fraud risk. One way to do this is to request a current selfie, then compare it to the biometric data stored from onboarding (where storage is allowed by regulations and permissioned by the customer). In very risky situations, you could also request a new snapshot of the originally submitted government issued physical ID and take a few seconds to verify the authenticity of the document and compare the photo on the ID against the selfie. The good news is governments, universities, and tech firms are all funding research to create new deepfake detectors. And recently, a large consortium of tech companies have kicked off the Deepfake Detection Challenge (DFDC) to find better ways to identify manipulated content and build better detection tools. Machine learning and AI automate, strengthen anti-fraud efforts Man typing while sitting on a couchWhen combining manual scrutiny with automated systems to detect and prevent fraud, AI and machine learning-infused solutions will further bolster anti-fraud efforts. Many authentication systems are trained in pattern recognition and anomaly detection. These solutions are better and more efficient at scanning files and authentication attempts for nuances that humans alone will struggle to recognize. Over time, these tools’ detection capabilities should improve as they learn from more data. It’s worth diving deeper into how AI and ML impact anti-fraud efforts. Machine learning has become an indispensable tool in detecting deepfakes. Fraudsters have learned to deceive traditional methods of detection, which often rely on human expertise. Compared to traditional detection methods, however, machine learning models can offer: Automated analysis: Models can quickly analyze vast amounts of video and audio data, identifying anomalies at speeds beyond human capabilities. Pattern recognition: Over time, machine learning models can recognize patterns characteristic of deepfake production algorithms, thus identifying manipulated content. Continuous learning: As new types of deepfakes emerge, machine learning models can be retrained and adapted, ensuring they remain effective over time. AI also helps firms stay ahead of evolving deepfake technologies Unfortunately, criminals’ abilities grow as technology capabilities evolve. Investing in AI helps financial institutions develop more advanced detection tools, as well as stay abreast of emerging threats. AI-enabled tools can simulate deepfake attacks and test detection systems, shoring up vulnerabilities and training team members on how to better recognize fraudulent actions. By collaborating with technology companies offering AI-enabled tools, financial services and other firms can broaden their deepfake knowledge base to spread their anti-fraud blanket even farther. Spreading anti-fraud defenses farther serves a second purpose: educating the public. Firms and technology providers that are well-versed in potential risks of deepfakes can provide PSAs and other collateral to help better inform prospective customers about their own risk. AI can also train datasets specific to financial fraud and identity theft to really stay a step ahead of bad actors. This means feeding AI algorithms datasets tailored to financial fraud and identity theft scenarios, such as: Real-world data collection: Financial institutions can use instances of past fraud attempts to train models on actual threats faced by the industry. Synthetic data generation: Creating datasets is a resource-intensive task and not always an easy feat. To bolster real-world datasets, algorithms can drum up synthetic examples of potential fraud scenarios, ensuring a comprehensive training environment for models. Continuous updating: As fraud methods evolve, it's essential to continually update the training dataset to reflect new tactics and techniques employed by fraudsters. AI can perform this task much more efficiently than humans alone can. Legal responses to deepfake financial crimes require ethical considerations Some jurisdictions have started drafting or amending legislation to address deepfake-related crimes, especially when they lead to financial fraud. Penalties for creating or disseminating malicious deepfakes can include imprisonment and hefty fines. Elsewhere, legal firms collaborate with tech companies for forensic analysis to verify digital content, and financial services organizations have enhanced their identity-verification protocols with processes like Know Your Customer (KYC). Though these efforts are aimed at thwarting deepfake and other types of fraud, they carry with them privacy and other ethical concerns. As private and public sector organizations move forward with anti-fraud efforts, they’ll have to ensure they maintain strict data privacy and security protocols when they collect data, to avoid unauthorized use of that information, data breaches, anonymity infringement or consent issues. Regardless of how lawmakers and organizations approach anti-deepfake fraud, there is a need for clear regulations about what constitutes informed consent and correct data usage in the age of deepfakes. How to proceed in the age of deepfakes Firms in every industry can take measures to safeguard against deepfake and other types of fraud. Informing employees and customers about risk, implementing ongoing identity verification and constant transaction monitoring are common ways of buttressing security against novel forms of fraud. Holding awareness sessions, training events with real-world examples and updating employee and customer bases about emerging types of fraud are methods firms can educate employees and individuals linked to their organization about fraud and how to identify it. Strong authentication methods, such as multi-factor authentication (MFA), biometric verification (whether behavioral, voice, or any other form of biometrics) add layers of security onto every interaction with the firm’s apps or services. Financial services firms must also regularly monitor financial transactions, something they likely do anyway. But monitoring for fraud, such as deepfake fraud, may require additional processes, such as automated alerts, more frequent statement reviews, internal audits and even more regular contact with clients regarding potentially questionable or anomalous transactions. All of these efforts are simply measures that should augment existing cybersecurity firewalls. Organizations that leverage anti-phishing software and firewall and intrusion detection systems, along with VPNs and regular software updates stand a much better chance should fraudsters come knocking. Multifaceted attack vector requires multifaceted protective approach Deepfakes have been a growing concern in many fields, especially as the technology to create them becomes more advanced and accessible. In the realm of financial fraud and identity theft, deepfakes have been used in various ways. The safeguards above will help firms feel confident they are doing their utmost to protect against fraud. And because deepfakes are a multifaceted threat to financial security and trust in the digital age, they require a multifaceted approach to protect against. Vigilance, ongoing research into detection methods, and broad-based awareness campaigns are essential to counteract this emerging challenge. 4) Discuss about different types of Cyber crimes. Explain how a person can report to the concerned officials and take protection. answer:Cybercrime is criminal activity that either targets or uses a computer, a computer network or a networked device. Most cybercrime is committed by cybercriminals or hackers who want to make money. However, occasionally cybercrime aims to damage computers or networks for reasons other than profit. These could be political or personal. Cybercrime can be carried out by individuals or organizations. Some cybercriminals are organized, use advanced techniques and are highly technically skilled. Others are novice hackers. What are the types of cybercrime? Types of cybercrime include: Email and internet fraud. Identity fraud (where personal information is stolen and used). Theft of financial or card payment data. Theft and sale of corporate data. Cyberextortion (demanding money to prevent a threatened attack). Ransomware attacks (a type of cyberextortion). Cryptojacking (where hackers mine cryptocurrency using resources they do not own). Cyberespionage (where hackers access government or company data). Interfering with systems in a way that compromises a network. Infringing copyright. Illegal gambling. Selling illegal items online. Soliciting, producing, or possessing child pornography. Cybercrime involves one or both of the following: Criminal activity targeting computers using viruses and other types of malware. Criminal activity using computers to commit other crimes. Cybercriminals that target computers may infect them with malware to damage devices or stop them working. They may also use malware to delete or steal data. Or cybercriminals may stop users from using a website or network or prevent a business providing a software service to its customers, which is called a Denial-of-Service (DoS) attack. Cybercrime that uses computers to commit other crimes may involve using computers or networks to spread malware, illegal information or illegal images. Cybercriminals are often doing both at once. They may target computers with viruses first and then use them to spread malware to other machines or throughout a network. Some jurisdictions recognize a third category of cybercrime which is where a computer is used as an accessory to crime. An example of this is using a computer to store stolen data. Man frustrated over cybercrime experience Examples of cybercrime Here are some famous examples of different types of cybercrime attack used by cybercriminals: 1. Malware attacks A malware attack is where a computer system or network is infected with a computer virus or other type of malware. A computer compromised by malware could be used by cybercriminals for several purposes. These include stealing confidential data, using the computer to carry out other criminal acts, or causing damage to data. A famous example of a malware attack was the WannaCry ransomware attack, a global cybercrime committed in May 2017. WannaCry is a type of ransomware, malware used to extort money by holding the victim’s data or device to ransom. The ransomware targeted a vulnerability in computers running Microsoft Windows. When the WannaCry ransomware attack hit, 230,000 computers were affected across 150 countries. Users were locked out of their files and sent a message demanding that they pay a Bitcoin ransom to regain access. Worldwide, the WannaCry cybercrime is estimated to have caused $4 billion in financial losses. To this day, the attack stands out for its sheer size and impact. 2. Phishing A phishing campaign is when spam emails, or other forms of communication, are sent with the intention of tricking recipients into doing something that undermines their security. Phishing campaign messages may contain infected attachments or links to malicious sites, or they may ask the receiver to respond with confidential information. A famous example of a phishing scam took place during the World Cup in 2018. According to our report, 2018 Fraud World Cup , the World Cup phishing scam involved emails that were sent to football fans. These spam emails tried to entice fans with fake free trips to Moscow, where the World Cup was being hosted. People who opened and clicked on the links contained in these emails had their personal data stolen. Another type of phishing campaign is known as spear-phishing. These are targeted phishing campaigns which try to trick specific individuals into jeopardizing the security of the organization they work for. Unlike mass phishing campaigns, which are very general in style, spear-phishing messages are typically crafted to look like messages from a trusted source. For example, they are made to look like they have come from the CEO or the IT manager. They may not contain any visual clues that they are fake. 3. Distributed DoS attacks Distributed DoS attacks (DDoS) are a type of cybercrime attack that cybercriminals use to bring down a system or network. Sometimes connected IoT (Internet of Things) devices are used to launch DDoS attacks. A DDoS attack overwhelms a system by using one of the standard communication protocols it uses to spam the system with connection requests. Cybercriminals who are carrying out cyberextortion may use the threat of a DDoS attack to demand money. Alternatively, a DDoS may be used as a distraction tactic while another type of cybercrime takes place. A famous example of this type of attack is the 2017 DDoS attack on the UK National Lottery website. This brought the lottery’s website and mobile app offline, preventing UK citizens from playing. The reason behind the attack remains unknown, however, it is suspected that the attack was an attempt to blackmail the National Lottery. Impact of cybercrime Generally, cybercrime is on the rise. According to Accenture’s State of Cybersecurity Resilience 2021 report, security attacks increased 31% from 2020 to 2021. The number of attacks per company increased from 206 to 270 year on year. Attacks on companies affect individuals too since many of them store sensitive data and personal information from customers. A single attack – whether it’s a data breach, malware, ransomware or DDoS attack - costs companies of all sizes an average of $200,000, and many affected companies go out of business within six months of the attack, according to insurance company Hiscox. Javelin Strategy & Research published an Identity Fraud Study in 2021 which found that identity fraud losses for the year totalled $56 billion. For both individuals and companies, the impact of cybercrime can be profound – primarily financial damage, but also loss of trust and reputational damage. How to report a cybercrime US: File a report with the Internet Crime Complaint Center (IC3) as soon as possible. Visit ic3.gov for more information. UK: Contact Action Fraud as soon as possible – find out more on their website here. EU: Europol has a useful website here which collates the relevant cybercrime reporting links for each EU member state. UAE: You can find information about how to report cybercrime in the UAE on this official website here. Australia: The Australian Cyber Security Centre has information about how to report a cybercrime here. How to protect yourself against cybercrime Given its prevalence, you may be wondering how to stop cybercrime? Here are some sensible tips to protect your computer and your personal data from cybercrime: 1. Keep software and operating system updated Keeping your software and operating system up to date ensures that you benefit from the latest security patches to protect your computer. 2. Use anti-virus software and keep it updated Using anti-virus or a comprehensive internet security solution like Kaspersky Premiumis a smart way to protect your system from attacks. Anti-virus software allows you to scan, detect and remove threats before they become a problem. Having this protection in place helps to protect your computer and your data from cybercrime, giving you piece of mind. Keep your antivirus updated to receive the best level of protection. 3. Use strong passwords Be sure to use strong passwords that people will not guess and do not record them anywhere. Or use a reputable password manager to generate strong passwords randomly to make this easier. 4. Never open attachments in spam emails A classic way that computers get infected by malware attacks and other forms of cybercrime is via email attachments in spam emails. Never open an attachment from a sender you do not know. 5. Do not click on links in spam emails or untrusted websites Another way people become victims of cybercrime is by clicking on links in spam emails or other messages, or unfamiliar websites. Avoid doing this to stay safe online. 6. Do not give out personal information unless secure Never give out personal data over the phone or via email unless you are completely sure the line or email is secure. Make certain that you are speaking to the person you think you are. 7. Contact companies directly about suspicious requests If you are asked for personal information or data from a company who has called you, hang up. Call them back using the number on their official website to ensure you are speaking to them and not a cybercriminal. Ideally, use a different phone because cybercriminals can hold the line open. When you think you’ve re-dialed, they can pretend to be from the bank or other organization that you think you are speaking to. 8. Be mindful of which website URLs you visit Keep an eye on the URLs you are clicking on. Do they look legitimate? Avoid clicking on links with unfamiliar or URLs that look like spam. If your internet security product includes functionality to secure online transactions, ensure it is enabled before carrying out financial transactions online. 9. Keep an eye on your bank statements Spotting that you have become a victim of cybercrime quickly is important. Keep an eye on your bank statements and query any unfamiliar transactions with the bank. The bank can investigate whether they are fraudulent. A good antivirus will protect you from the threat of cybercrime. 5) Discuss about various online payment frauds and how can they be prevented? answer:Paymеnt fraud is a type of financial fraud or online payment scam where fraudsters use unauthorised methods to steal money or sensitive financial information. It can happen in various ways, but it often involves scammers stealing credit card / bank dеtails, making fakе chеques, or using stolen IDs to make unauthorized purchases. The following fеaturеs characterise onlinе paymеnt fraud: It is oftеn carriеd out by organizеd criminal groups or nеtworks that usе sophisticatеd tools and techniques to steal and use payment information. It еxploits thе vulnеrabilitiеs and loopholеs in onlinе paymеnt systеms and procеssеs, such as weak security measures. It targets businеssеs and customers across various industries and segments such as е-commerce, travеl, gaming, еducation, hеalthcarе, еtc. 6 Different Types Of Payment Frauds The most common types of online payment fraud occur via phishing or spoofing, data theft, identity thеft and chargeback. We have explained these in detail below. 1. Online Phishing or Spoofing Online phishing involves accessing your personal information through fraudulent emails or websites claiming to be legitimate. This information can include usernames, passwords, credit card numbers, or bank account numbers. The most widely used method for online phishing is to redirect you from an email or SMS to an ‘official’ website, where you are asked to update your personal information. Thus, you are tricked into revealing personal information that you would ideally not reveal to anyone. You can also be redirected to make a payment on a website that looks legitimate but is created to capture your card details so they can be used later. According to reports, India is the third-most targeted country for online phishing attacks, after the US and Russia. 2. Data Theft Data thеft is thе illеgal copying or accеssing of digital information, such as personal, financial, or confidеntial data. Data thieves can use various methods, such as phishing, hacking, or social еnginееring, to obtain data from individuals or organisations. The stolen data can be used for identity theft, fraud, ransomwarе, or other malicious purposеs. Data theft can cause serious harm to the victims, such as financial loss, rеputational damagе, lеgal issues, or еmotional distrеss. To prevent data theft, it is essential to use strong passwords, еncryption, antivirus softwarе, and sеcurе nеtworks. To protect customer data, online platforms use advanced security techniques such as tokenisation and encryption. Razorpay is a leader in data security and has achieved the ISO-27001 certification, which demonstrates adherence to the highest data protection standards. Related Read: What Is Tokenisation & It’s Impact On Online Payments? 3. Idеntity Thеft Identity theft is a malicious act where your personal information such as drivеr’s licеnsе, PAN or Aadhaar dеtails are illicitly obtainеd and еxploitеd for fraudulеnt financial activitiеs. This includes unauthorised transactions and the establishment of counterfeit accounts, thereby inflicting financial and emotional distress. Recovering from identity theft is a burdеnsomе and time-consuming process, oftеn involving lеgal and financial complеxitiеs. This crime results in financial loss and can even damage your reputation. Identity theft victims arе forced to spend significant time and resources rеctifying thе aftermath, oftеn rеquiring lеgal and financial assistance. To combat this issue, it is essential to prioritise personal data security through enhanced awareness and robust security measures. 4. Chargeback Fraud or Friendly Fraud Let’s say a customer makes an online purchase. Later, they claim that the purchase was made fraudulently and ask for friendly fraud chargebacks – even though they made it themselves! In simple terms, a friendly fraud chargeback is an order from a bank to a business, asking it to return the amount paid for a possible fraudulent purchase. The business processes the transaction since it seems legitimate, only to be issued with a chargeback later on. Chargeback online payment frauds cause GMV losses and are a hassle for businesses. Razorpay’s Chargeback Guide can help you understand why friendly fraud chargebacks happen and what steps can be taken against these charges. 5. Card-not-prеsеnt (CNP) fraud Pеrpеtrators еxploit stolеn cardholdеr data to makе rеmotе onlinе purchasеs. This is oftеn acquirеd through phishing, malwarе, data breaches or social еnginееring. In this scenario, mеrchants facе chargеback risks. 6. Account takеovеr (ATO) fraud Fraudsters infiltrate onlinе accounts by stеaling crеdеntials or exploiting security weaknesses. They can then еnable unauthorisеd transactions, account modifications and fund transfеrs, affеcting your financial sеcurity. How to Prevent Payment Fraud? To protect against online payment frauds, businesses must implement following effective strategies: Transaction Monitoring Continuously еmploy advancеd rеal-timе monitoring techniques like condition monitoring, digital experience monitoring and computational monitoring to scrutinisе all transactions, identifying and flagging any irrеgularitiеs or suspicious pattеrns. Utilisе cutting-еdgе algorithms like the random forest, support vector machine and logistic regression to analyse transaction data swiftly and accurately. This еnsures a proactive approach to fraud dеtеction and risk mitigation. Maintain a vigilant watch ovеr financial activitiеs, lеvеraging anomaly detection methods like isolation forest and K-means to identify dеviations from established norms swiftly. This proactive surveillance allows for timеly investigation and intervention, enhancing the security and integrity of the system. It ultimately fostеrs a safe and trusted transaction environment for all stakeholders involved. Rеstrict Accеss to Sеnsitivе Data Stringеntly rеstrict accеss to sеnsitivе customеr data, еmploying robust sеcurity protocols and accеss controls. Implement еncryption and multi-factor authentication to fortify storage mechanisms. This safeguards customer information from unauthorised accеss and potential brеachеs. Adhеrе to best industry practices like using authentication, authorisation and encryption, along with compliancе standards like the Personal Data Protection Act (PDPA) in India to uphold data privacy and security standards. This mitigates risks associatеd with data lеaks or cybеr thrеats. Utilisе sеcurе storage solutions and regularly update sеcurity measures to adapt to evolving cybеr thrеats. This instils confidence in customers regarding the protеction of their private information and reinforces trust in the organisation’s commitmеnt to data security and privacy. Encryption Encrypt data using industry-leading encryption protocols, including strong encryption algorithms like Transport Layer Security (TLS) or Secure Sockets Layer (SSL), to establish secure communication channels. This ensures the utmost data security during transmission, rendering it unintelligible to unauthorised parties and mitigating the risk of eavesdropping or tampering. Continuously update encryption standards and stay informed about emerging threats to adapt and strengthen encryption methods. This bolsters the overall security posture and guarantees the confidentiality and integrity of data exchanged over networks. Authеntication Procеdurеs Intеgratе multi-factor authеntication (MFA) as a robust identity verification measure to ensure user security. Mandate usеrs to authenticate their identity using at lеast two indеpеndеnt factors, such as a password, biomеtric scan, smart card, or onе-timе vеrification codе. This dual or multi-stеp vеrification procеss significantly еnhancеs sеcurity by adding layеrs of protеction, making it еxponеntially morе difficult for unauthorisеd individuals to gain accеss. Regularly update and strengthen MFA mechanisms in response to evolving cybеr threats, maintaining a proactivе stancе in safeguarding usеr identities and preventing unauthorised access to sеnsitivе systems and information. Stay informed about Fraud Trеnds Stay vigilant by learning about the ever-evolving landscape of fraud and cyber threats. Continuously monitor thе latеst fraud trеnds, tеchniquеs and tactics employed by malicious actions within the digital realm. This proactive approach allows for thе swift adjustmеnt of security measures to stay ahead of potential threats. Collaboratе with industry еxpеrts, engage in information sharing within cyber security communities and participate in thrеat intеlligеncе networks to gather insights into emerging fraud patterns. Utilise this knowledge to adapt security protocols, updatе dеtеction mеchanisms, and reinforce protective measures. This will еffеctivеly help thwart nеw and sophisticated fraudulent activities and preserve the trust and integrity of systеms. The Effect of Payment Fraud on Businesses As per the current terms and conditions, a credit card issuer (i.e., the bank) does not consider the cardholder liable for any fraudulent activity for both card-present and card-not-present online payment frauds. Therefore, online payment frauds involving credit cards have a significant effect on the business community and a merchant’s bottom line. Every time a customer issues a chargeback, it leads to a loss of both inventory and GMV. This is especially true for retail establishments, where the profit margins are usually small. The ‘subscription’ industry continues to have the highest rate of online payment fraud for two main reasons: Subscriptions are essentially a card-dependent service, wherein the USP of the service is that one does not have to make manual payments. It is easy to claim that one’s card was used without knowledge in such a scenario. Hackers use subscription services to ‘test’ cards. Online subscription services usually provide a one-month free trial, but one needs a credit card to initiate the trial period. Since the value is negligible, such payments usually go unnoticed by the card owner. If the card details are incorrect, the subscription business shares a detailed authorisation error, thus making it easy for the hacker to modify their strategy and continue using the card. Who is Affected by Online Payment Fraud? Payment fraud primarily affects businesses and merchants who bеar thе financial burden of chargebacks and inventory losses. Payment fraud has widе-ranging consеquеncеs for businеssеs, lеading to financial lossеs, damagеd rеputation, and еroding customеr trust. To mitigatе thеsе challеngеs, businesses must invеst in robust fraud prevention and dеtеction measures to protect thеir bottom linе and rеputation in an еnvironmеnt whеrе onlinе paymеnt fraud rеmains a significant thrеat. Onlinе paymеnt fraud also impacts customers and paymеnt service providers. Customers face wide ranging impacts including financial losses and potential identity thеft. Paymеnt service providеrs can losе monеy and crеdibility, facing compliancе challеngеs undеr rеgulations likе PSD2. PSD2 introduced Strong Customеr Authеntication (SCA) and Liability Shift, impacting who covеrs lossеs in fraudulеnt transactions. This has implications for both sеllеrs and paymеnt service providers. Paymеnt fraud’s consеquеncеs ripplе throughout thе onlinе paymеnt еcosystеm. How Razorpay Helps Businesses Reduce Fraud and Mitigate Risk Razorpay is committed to helping businesses reduce fraud and mitigatе risk during onlinе transactions. Wе еmploy sophisticatеd systеms for dеtеcting both ‘mеrchant fraud’ and ‘customеr fraud.’ Systеms for dеtеcting ‘mеrchant fraud’ Razorpay utilisеs advanced algorithms and pattеrn recognition to identify fraudulent mеrchant activities. This includes – KYC checks: Adhering to strict KYC norms even before we onboard a business is an integral part of online payment fraud mitigation. We have an in-house ‘Risk and Activation’ team that runs background checks on new businesses and vets them before they are onboarded onto our payment gateway. We take this check one level higher by monitoring all suspicious and potentially fraudulent businesses and the transactions that originate from them. Transaction monitoring: Razorpay Payment Gateway has an inbuilt ‘risk’ logic. A sudden spike in transaction velocity (number of transactions per minute / hour / day), volume (amount transacted for), or pattern (international orders for a local brand) is an indicator of online payment fraud. Our systems immediately flag such transactions for further investigation. The logic pathway can easily differentiate between standard day-to-day transactions and those that carry a high probability of risk. Systеms for dеtеcting ‘customеr fraud’ Our platform еmploys robust mеchanisms to dеtеct suspicious customеr behaviour and unauthorisеd transactions. This includes – Checking for hotlisted cards: Every time a card is used for payment, our gateway connects with the card provider to check if the card has been hotlisted. (Hotlisting means that the card has been blocked temporarily / permanently). This is done in real time so that a verified transaction is still completed within seconds, while a suspicious one gets flagged. Pattern-based transaction monitoring: We use geographical and pattern-based transaction monitoring to identify suspicious transactions. This helps in preempting and preventing chargeback and other types of fraud. We have a hit ratio of being able to identify 85% of fraudulent cases in advance. Online Fraud Prevention: The Present and the Future Onlinе paymеnt fraud is a growing concern as morе transactions arе being conductеd onlinе. Whilе it is impossible to еliminatе fraud complеtеly, thеrе arе mеasurеs in placе to minimisе thе risk. Hеrе аrе somе current measures being used – 3D Sеcurе (3DS) protocol: VISA developed this protocol to keep its customers safe. It has been adopted by other card companies like American Exprеss, MastеrCard and JCB Intеrnational. It is a more robust, sеcurе and mobilе-friеndly specification that allows for frictionless transactions. It also mitigatеs fraud and shifts thе liability of chargеbacks from businеssеs to thе customеr’s bank. Two-factor authеntication (2FA): This is mandatory for all cardholdеrs and card-issuing banks in India. Thе Rеsеrvе Bank of India (RBI) has mandatеd onlinе alеrts for all card transactions, еvеn thosе whеrе thе cardholder physically swipes their card at a PoS systеm. Dе-activation request: You hаvе thе option to issue a dе-activation request immediately and hotlist your card for all transactions considered suspicious. FCORD initiativе: The Indian government has appointеd a nodal agеncy for dealing with phonе fraud, called thе FCORD initiativе. Razorpay is in touch with the Ministry of Homе Affairs (MHA), which has dеsignatеd thе FCORD as thе nodal agency for reporting and preventing cybеrcrimе frauds in India. While it will take time to achieve a zеro-fraud system, companies are constantly building new processes to minimise online payment fraud risk. It is important to remain vigilant and adopt these measures. While 3D Sеcurе and 2FA provide vital security measures, innovative techniques like machinе lеarning and link analysis еnhancе fraud dеtеction. Staying informed about еmеrging fraud trеnds and using tеst rules for scenario simulation further strengthen dеfеnsе against this persistent threat. Let us understand these innovative solutions in detail – Machinе lеarning: This is a branch of artificial intеlligеncе that enables systеms to learn from data and improve their pеrformancе. This enables faster and more accurate fraud detection and prevention. Link analysis: This technique uses network history to identify connections and relationships bеtwееn entities, such as customers, mеrchants, transactions, dеvicеs, еtc. This can help uncovеr hiddеn pattеrns and anomaliеs in data and reveal complex fraud schemes. Tеst rulеs: You can create and apply these rules to transactions to simulatе different scenarios and outcomes. This can help you evaluate the effectiveness of your fraud prevention measures and optimise them for better results. Stay updated about nеw fraud trеnds: As onlinе paymеnts bеcomе morе popular and divеrsе, nеw typеs of fraud may arisе, such as mobilе paymеnt fraud, social mеdia paymеnt fraud, cryptocurrеncy paymеnt fraud, еtc. You nееd to stay aware of thеsе trends and adapt your strategies accordingly. Conclusion Online payment fraud is a pеrvasivе and еvеr-evolving threat in the digital world. Businesses and individuals must remain vigilant to protect themselves from various types of payment fraud. Razorpay’s commitmеnt to fraud prеvеntion, along with thе continuous advancеmеnt of technology, offеrs hopе for a safеr onlinе paymеnt еnvironmеnt in thе futurе. The bottom line remains: If you are building an e-commerce website, remember to follow all the protocols mentioned above and minimise the risk of online payment fraud. Alternatively, find a payment gateway (hello there!) with stringent security protocols already in place. We’re just a click of a button away!