The issue of security is a pressing concern for every company that handles data. Modern tools enable attackers to effectively imitate the actions of legitimate users. Moreover, protective mechanisms do not always recognize and prevent unauthorized access attempts. As a result, this leads to data leaks, the theft of funds from bank accounts, and other unfortunate incidents.
A solution to this problem has been proposed by a Spanish company , which uses deep learning and behavioral biometrics to detect fraudulent activities in the banking sector, offers an intelligent system. Recently, it received $11 million from investors to expand its platform.
Founded in 2010 in Madrid, Buguroo aims to identify fraudsters attempting to mimic the behavior of legitimate account holders. By employing deep learning algorithms based on neural networks, the company gathers insights into what a typical banking session looks like. Utilizing a fraud detection and prevention technology that combines behavioral biometrics, malware detection, and device assessment, the platform more effectively identifies potential threats from cybercriminals and bots.
Fraudsters may employ numerous methods to bypass authentication processes, such as remote access malware (Trojans), form-grabbing tools, web injections, and more. Representatives of Buguroo claim that their solution can detect previously unknown malicious scripts that end users interact with in mobile applications or browsers. This means that the platform can adapt to new methods that have not yet been added to blacklists.
Operating principle
Buguroo identifies when attempts at fraud are made by analyzing historical patterns and classifying each subsequent login session based on this data. The platform collects a variety of behavioral patterns. Specifically, it takes into account the fingerprint size and screen pressure (on touchscreen devices), typing speed and fluency, mouse movements, and gyroscope position. Subsequently, this data is used in behavior analysis when an intruder attempts to access the system.
How does it work in practice? For instance, a bank client usually uses the vertical scroll bar on the side of their browser for navigation while entering account data using the side of the keyboard. However, the system then notices that in one session, the client uses the mouse scroll wheel and the horizontal number pad at the top of the keyboard. This could indicate that someone else is trying to access the account.
By using cross-analysis of information from different channels, the system is able to detect anomalies arising from fraudulent activity, allowing for early recognition of such attacks.
BugFraud Workspace
The Buguroo service also deals with fraudulent operations involving new accounts (NAF), meaning when a new bank account or credit card is opened using stolen credentials. It also offers assistance in identifying fraudsters already operating within the banking system. To this end, the company provides the Fraudster Hunter solution, which is part of its core BugFraud platform. The solution is primarily focused on identifying intruders who have already infiltrated the bank. It's important to note that BugFraud is available in various deployment options. Clients can choose a virtual SaaS-based or on-premises deployment.
By continuously monitoring user activities, devices, networks, and sessions, Buguroo collects information on fraud methods, creating a unique "cyber profile" for each user, a digital DNA built using thousands of parameters related to customer behavioral biometrics (including smartphone and mouse movements, keystrokes, device profiling, geolocation, and malware records), which recognizes with 99.2% accuracy. The solution's effectiveness is validated by experts. In 2018 and 2019, the company was recognized as the winner in the "Product of the Year for Fraud Prevention" category by an independent organization. .
Award for Winner
Market Situation
Currently, Buguroo protects over 50 million clients in Europe and Latin America during financial services from the moment of user login to logout. With another $11 million in the bank, it plans to expand its global presence into new regions, including the USA, UK, France, and Germany.
However, Buguroo is not the only company tracking behavioral biometrics in banks. The Israeli , offering similar services, received $30 million in investments a year earlier. These figures indicate a real demand for such technologies.
Nevertheless, Buguroo assures that its solution differs from others. For instance, the advanced behavioral biometrics algorithms of bugFraud detect deviations in customer behavior in the fastest and most accurate way compared to other solutions offered by competitors. Furthermore, the company's solution creates a unique profile for each user and compares it with the previous sessions of the same user, whereas other services compare the profile with a broader cluster of "good" and "bad" behaviors. This is an important distinction, as theoretically, fraudsters can learn what constitutes "good" behavior in terms of registration or logging into banking sites. However, it is nearly impossible for an attacker to identify the specific behavioral traits of individual users they are attempting to mimic.
Referring to data Buguroo indicates that about one third of all online banking fraud cases involve accounts that appear to belong to legitimate customers but are actually controlled by fraudsters. The company's solution (Fraudster Hunter) will help identify such profiles, making life more difficult for cybercriminals.
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Source: habr.com
