As the world becomes increasingly digital, cyber attacks are becoming more sophisticated, and traditional security measures, like firewalls and passwords, are no longer sufficient in protecting sensitive data. Fortunately, advancements in technology have given rise to user and entity behavior analytics (UEBA), a behavioral biometrics-based approach that can effectively detect and prevent cyber threats. In this blog post, we will explore the role of behavioral biometrics in UEBA.
UEBA (user and entity behavior analytics) is a powerful cybersecurity technology that uses AI and machine learning to detect and respond to anomalous behavior patterns exhibited by user accounts and entities within a network, helping organizations identify potential threats. UEBA is an enhanced version of UBA (user behavior analytics) that also analyzes the behavior of entities, such as devices and applications, in addition to users, to better detect and respond to security threats. A higher volume of data compared to UBA is one of the main advantages of UEBA. This is because the UEBA system analyzes a wider range of data sources, including behavioral biometrics, corporate network traffic, and system logs. This comprehensive approach provides security teams with more visibility of user and entity behavior, making it easier to detect and prevent a wider range of threats. So what about UEBA vs traditional security? Traditional security measures focus on detecting known threats and vulnerabilities. What makes UEBA different is that it can also adapt to changes over time, making it a more effective solution for detecting and preventing advanced cyber attacks.
Behavioral biometrics in cybersecurity refers to the use of data related to the unique behavior of individuals to authenticate and verify their identity. This can include things like typing rhythm, mouse movement, and mobile device usage patterns. By analyzing these patterns, security systems can identify whether user accounts are who they claim to be and therefore detect suspicious activity. Understanding behavioral biometrics is important in cybersecurity because it provides an additional layer of security beyond traditional methods, such as passwords or tokens, that can be hacked by identity theft activities.
The role of behavioral biometrics in UEBA is crucial in cyber threat detection through analyzing user behavior. UEBA benefits behavioral biometrics by establishing a baseline of normal user behavior, allowing it to detect any deviations that could indicate a security threat. By incorporating behavioral biometrics in UEBA, organizations can enhance their security posture and better protect themselves from cyber attacks. Biometric UEBA security is particularly effective in detecting insider threats, which are one of the biggest cybersecurity risks faced by organizations. By identifying unusual behavior patterns, such as a user logging in from an unusual location or accessing sensitive data at an unusual time, UEBA can alert security teams to potential insider threats before they cause any damage. MarketsandMarkets predicts that the global behavioral biometrics market size is set to expand from $871 million in 2018 to $2.6 billion by 2025. According to another report by Market Data Forecast, the global user and entity behavior analytics market is anticipated to experience significant growth, expanding from $890.7 million in 2019 to $1,178.3 million by 2025, with behavioral biometrics as a key driver of this growth.
Behavioral biometrics in UEBA has several benefits over traditional authentication methods, including:
Behavioral biometric security can help prevent unauthorized access to sensitive data by verifying the identity of users based on their unique behavioral patterns. This method is more secure than traditional authentication methods, like passwords, which can be easily compromised.
UEBA analytics can identify unusual behavior patterns that may indicate a security threat. This can include a user logging in from an unusual location, accessing sensitive data at an unusual time, or downloading large amounts of data. UEBA can alert security teams to investigate further, potentially stopping a security threat in its tracks.
While behavioral biometrics in UEBA is an excellent solution, there are a few challenges to consider, including:
Behavioral biometric data is subjective and can vary from one user to the next. It can be challenging to establish a baseline of normal user behavior, and the system may produce false positives or false negatives.
It can be challenging to distinguish between normal and abnormal behavioral patterns. For example, downloading vast amounts of data may seem unusual to UEBA analytics, but it may be an essential part of a user's specific project.
Next-gen UEBA solutions with advanced AI and machine learning features can overcome these obstacles, providing a highly secure and reliable solution for protecting your organization's valuable data. These tools can accurately establish baselines of user behavior, detect unusual behavioral patterns, and reduce false positives and negatives. With the right technology, behavioral biometrics in UEBA can provide an exceptional level of security to prevent cyber attacks.
UEBA with behavioral biometrics is a powerful tool that can be used in many ways to protect organizations from cyber threats. Here are some of the ways it can be used:
Behavioral biometrics can be used to detect suspicious user behavior that could indicate an insider threat. UEBA can identify when a user accesses data they don't typically access or when they attempt to access data outside of normal business hours. This can help security teams identify potentially malicious activity by insiders, who are often the biggest cybersecurity threat to an organization.
By analyzing user behavior, UEBA can detect patterns and changes in user activity that could indicate a security threat and create a risk score for each user based on their behavior. This score can be used to identify users with a high risk of causing a security incident and take appropriate action.
Behavioral biometrics in UEBA can identify unusual entity behavior that could indicate a cyber threat. UEBA can detect when an entry accesses data from an unusual location or attempts to access data they don't typically access. This can help organizations to detect potential security incidents and prevent unauthorized access to sensitive data.
Behavioral biometrics can also detect fraud in real time. Since UEBA works by analyzing user behavior patterns, it can detect potentially fraudulent activity as it happens. This can help organizations prevent financial losses and protect their customers from fraud.
At Logsign, we understand that cybersecurity is a top priority for organizations of all sizes. That's why we are dedicated to providing comprehensive solutions that empower our clients to identify and prevent threats before they cause harm. Logsign UEBA is not just another standalone solution. It is a fully integrated part of our SIEM platform that offers semi-automated or fully automated actions to address known threats. With built-in Incident Management and Response features, Logsign UEBA can detect and decisively respond to security incidents in real time. Our platform comes equipped with over 500 built-in correlation rules, leveraging Logsign's own threat intelligence feeds, and advanced analytics & data enrichment features to allow you to empower your security posture. Take the next step towards a more secure future and get a live demo of Logsign SIEM today!
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