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UEBA- Secured Data and Fraud Detection

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.


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.

What is UEBA ?

Advanced cyberattacks and persistent vulnerabilities to your business frequently rely on compromised credentials or coercion of people to do actions that vandalize enterprise security. To detect these types of threats, you’ll need a robust solution that allows analysts to swiftly distinguish between regular and unusual network behavior. The UEBA module has the fastest time-to-value in the industry, allowing for same-day deployment and quick insights.

User and Entity Behavior Analytics (UEBA) is the application of machine learning and security research to discover when users or entities are engaging in unusual and unsafe ways. It tracks users’ interactions with data, systems, and apps to identify and attribute threats so that security analysts can respond swiftly. UEBA uses comprehensive context information to enrich security data. Context data improves event detection accuracy, decreases false positives, and allows for context-based searching and threat hunting. Machine learning, behavioral analytics, and threat modeling are all used by UEBA’s analytics engine to detect your top threats. As a result, analysts are continually on the lookout for your most critical security incidents.

According to Infosecurity Outlook, people have specified patterns of behavior, and behavioral analytics is about how we take those patterns and start to extract usable information from them.

UEBA is being adopted by businesses to bring advanced analytics and machine learning capabilities to their IT security arsenal. UEBA solutions recognize patterns in regular user behavior and identify anomalous behaviors that do not match those patterns and may be linked to security events.

Organizations utilize UEBA technologies to increase efficiency and risk management while minimizing financial and reputational loss. They bring value by allowing firms to prevent attacks, particularly those that originate from within the network, detect breaches more quickly to decrease exposure, and mitigate the damage caused by cyber threats. Organizations would be able to detect and respond to threats more quickly and easily if they used such technologies. Customers and business partners will trust organizations that use effective security and risk management strategies and processes. As a result, they can serve as a business enabler, assisting firms in meeting their data privacy and security obligations, as well as compliance goals.

Some of the Essential Features of UEBA that you should know are;

  • Connects security information to identity and entity context.
  • UEBA uses machine learning to provide powerful behavior analytics.
  • Reduces false positives by analyzing the context of user, object activities and security events.
  • Threat chains automate machine learning and analytics processes, reducing the time to detect and respond to threats.
  • UEBA covers a variety of use cases for detecting cyber threats, fraud, non-compliance, and attacks from both inside and outside the company.

Security solutions like UEBA, which were once viewed solely as a means of lowering possible financial losses and increasing productivity, are now seen as a means of enabling a business. Organizations may better prioritize their investments to improve their overall security posture and enable them to satisfy privacy and compliance objectives by understanding what people are doing and how they interact with applications and data. Customers and business partners trust organizations that use effective security and risk management strategies and processes. Thus, they can serve as a business enabler, supporting firms in meeting their data privacy and security obligations, as well as compliance goals.