Cyber security measures are rapidly becoming obsolete, and more proficient hackers and cyber attackers are now able to circumvent the perimeter defenses utilized by the majority of organizations. As long as organizations had firewalls, gateways, and other intrusion prevention systems, they were considered safe back in the old days. Today’s threat landscape is more complicated than ever before. The need for a better-secured technology market is imminent with increasing cyberattacks and data theft. Traditional ways of keeping corporate systems safe are no longer enough. Organizations are no longer safe from intrusion with Web gateways, firewalls, intrusion prevention tools, and encrypted connection systems like VPNs. Sometimes, hackers will gain access to the systems; when they do, it is crucial to identify them immediately.

The primary focus of User Behavior Analytics (UBA) is data security and fraud detection technologies. However, UBA needed maturity to deal with prominent security threats. As a result, a distinct departure from fraud detection technologies broadened its scope. The rise of chaos engineering and the evolution of DevSecOps have highlighted the importance of tracking and monitoring all devices connected to a system, as well as monitoring their access controls. Understanding what each entity on an access control list (ACL) represents, including the implicit identities built into a Windows environment, and specifically the difference between the “Everyone” group and “Authenticated users,” is critical today.

UBA transformed into UEBA 

UBA is changed to UEBA, which stands for “User and Entity Behavior Analytics.” According to experts, the “E” in UEBA recognizes that profiles of things other than users are often used to find threats more accurately, in part by comparing the behavior of these other things to the behavior of users. In other words, UEBA software considers user activity as well as controlled and unmanaged endpoints, applications (including cloud-based, mobile, and on-premises apps), networks, and external threats. Using UEBA, you protect against external threats that penetrate the perimeter and existing insider threats, securing your data from the inside out. The value of UEBA is that it prevents hackers or insiders from accessing critical systems. It can spot when this has happened and alert you about the risk.

UBA vs. UEBA 

UEBA systems do much more than keep track of what users do. It keeps track of what happens with devices, apps, servers, and data. This technology doesn’t just look at how users behave; it also looks at how entities behave.

UEBA goes a step further, makes more data, and gives more complex options for reporting than the original UBA systems.

Traditional UBA and UEBA technologies can do the same, but UEBA systems use more advanced analytics techniques. While UBA is made to track insider threats, UEBA uses machine learning to look for more strange activities linked to more kinds of threats, including advanced threats. Normal network activity may make it hard to see this, though. Enterprises often use UEBA with Security Information and Event Management (SIEM) technologies to better analyze the data they collect.

UEBA is the right choice!

UEBA can decrease your susceptibility to popular cyberattacks such as phishing, whaling, social engineering, Distributed Denial of Service (DDoS) attacks, malware, and ransomware. UEBA will notify you immediately if any of these assaults are successful.

UEBA tools and processes, instead of replacing earlier monitoring systems, are used to complement them and enhance your company’s overall security posture.

UEBA collects different kinds of data, such as user roles and titles, access, accounts and permissions, user activity, location, and security alerts. This information can be gathered from both the past and the present. The analysis looks at the resources used, the length of sessions, connectivity, and peers’ behavior to compare unusual behavior. It also updates itself when changes are made to the data, such as when permissions or promotions are added.

It isn’t always the case that the UEBA and UBA systems flag everything that’s out of the ordinary as dangerous. Instead, they consider the impact on others of their actions. A “minimal impact” rating is given to behavior if it consumes little resources. There’s a higher effect score for sensitive information, such as information that can be used to identify a specific person. While the UBA system automatically limits or makes it more difficult to authenticate the user whose behavior is out of the ordinary, security teams can determine what to focus on first.

 The pros and cons of UEBA are:

Need for UEBA!

Behavior analysis systems help marketing teams analyze and predict customer buying patterns. Current user behavior analytics tools have more advanced profiling and monitoring capabilities than SIEM systems. They are used to find out what is normal for the organization and its users and when something isn’t normal. UBA uses big data and algorithms for machine learning to look at these changes in almost real-time.

Even though applying user behavior analytics to just one user might not help find malicious activity. But running it on a large scale can help an organization find malware, including other potential cybersecurity threats such as data exfiltration, insider threats, and compromised endpoints.