Collin’s dictionary defines “behavior pattern” as a recurrent way of acting by an individual or group toward a given object or in a given situation. Analyzing and understanding the behavior patterns of individuals has proven to provide in-depth solutions to problems in different walks of life, including cybersecurity.
When it comes to organizations battling against cyberthreats, traditional rule-based security solutions cannot provide visibility into increasingly sophisticated cyberattacks. We see this pattern in successful breaches that occur on a daily basis. Also, in the process of rapid detection and remediation of security threats, traditional security tools tend to overwhelm security analysts with alerts that lack context.
This is where user and entity behavior analytics (UEBA) offers a more efficient solution. A UEBA solution orchestrates advanced analytics through data enrichment, data science, and machine learning to battle advanced threats. Through this process, UEBA produces a lower volume of alerts that are more accurate and reduces the number of false positives. Incorporating behavior analytics in your SIEM solution helps address the landscape of abnormal and advanced security threats along with the traditional rule-based threat detection.
Let’s look at some use cases where behavior analytics plays a significant role in attack detection.
Differentiating between normal and malicious behaviors
It is no secret that insider threats are one of the many sources of sensitive data loss. Here, the threat actor is a malicious or a compromised insider. Detecting insider threats can be challenging, as most security tools cannot differentiate a legitimate user from a potential threat actor.
In this case, a UEBA solution detects users performing suspicious activities that are outside of their normal baseline. Behavior analytics takes into account the history of a particular user’s behavior and detects abnormal activities like:
- Logins at unusual hours, in unusual frequencies, from unusual locations and accessing unusual data or systems, such as SQL servers
- Privilege escalation changes for critical systems
- Unauthorized access to user accounts
- Data exfiltration attempts by correlating seemingly unrelated events, such as logging in at an unusual time, accessing a SQL server database, and insertion of a USB drive
Detecting compromised assets quickly and accurately
When it comes to cyberattacks, some of the initially targeted assets include systems, hosts, accounts, or devices. Malicious threat actors can operate undetected in your organization’s network for weeks or even months. Using behavior analytics, detecting security threats like compromised devices becomes easier, more accurate, and a lot quicker.
In this case, the UEBA solution detects anomalous activities by monitoring the behavior of the entities in your organization. The solution monitors:
- Privileged user accounts for compromise
- Servers for activities that deviate from the normal baseline
- Anomalous behavior in real time, like increased traffic in network devices including Windows devices, routers, and firewalls
Detecting data exfiltration attempts
Data exfiltration occurs when sensitive data is transferred outside the organization without authorization. This can happen when a malicious user transfers data either by copying the contents to a physical device or over the internet. It can also occur through malware infections in your organization’s systems.
In this case, the UEBA solution monitors network devices, detects, and provides real-time alerts for suspicious events such as:
- Unusual software installations on particular devices
- Unusual downloads or access to sensitive data
- Unusual amounts of network traffic that might be an indication of large data transfer, contradicting the normal baseline of the user or machine transferring the data
As today’s attacks become increasingly sophisticated and security threats emanate from both outside and within the network, your organization needs a security solution that is skilled in detecting and mitigating unusual threats. A UEBA solution can adapt to your organization’s environment quickly by learning and analyzing the behavior of your users and entities, and alert you to anomalous activities that deviate from the norm. It also helps you prepare for uncommon threats from both malicious insiders and outsiders.
If you are interested in learning more about behavior analytics and machine learning in SIEM, join us for this two-day webinar series where we dive deep into the world of machine learning and explore some real-life examples of mitigating cyberthreats like account compromise, insider threats, data breaches, and more. Learn how you can use this latest cybersecurity trend to strengthen your defenses.
