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UEBA vs SIEM: The Key Differences of Each Solution

User and Entity Behavior Analytics (UEBA) is a cybersecurity solution that analyzes the behavior of users and machine entities using machine learning and mathematical algorithms to detect anomalies that may indicate risk to the organization.

Security Information and Event Management (SIEM, pronounced “sim”) provides security professionals with a centralized view of their organization’s security events. SIEM systems collect and analyze security-related data from multiple sources, use advanced analytics and correlation techniques to identify potential security threats, and provide real-time alerts and automated response actions.

UEBA and SIEM – A Complementary Team of Cyber Tools

By integrating SIEM and UEBA, organizations can achieve a more comprehensive and proactive security posture. SIEM provides event correlation, log management, and real-time monitoring, while UEBA enhances threat detection by focusing on user and entity behavior analysis. Together, they offer improved visibility, faster incident response, and better protection against advanced threats.

What is User and Entity Behavior Analytics (UEBA)?

UEBA is the scientific process of transforming behavior data from human users and entities such as servers, routers, endpoints, and IoT devices into risk-prioritized intelligence, for the purpose of driving business action. It’s the application of data science to create user and entity behavior baselines from months of historical access and activity. Once behavior baselines are established, analytics is used to monitor user and entity behavior in real time, for the purposes of predicting and detecting anomalous activity. The output of security analytics is a single risk score for every user and entity. The risk score provides actionable intelligence on potential risky situations in real-time so organizations can take corrective action.

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The Threats That UEBA Detects

Because UEBA works on subtle changes in behavior of both human users and machine entities, it can detect a variety of cyber-attacks, including insider threats, account takeovers, stolen credentials, ransomware attacks, brute force attacks, DDoS attacks, compromised devices, and more. UEBA uncovers risk from known as well as unknown threats.

Who Uses UEBA?

UEBA solutions are utilized by a variety of organizations across different industries, but typically it is those that have extensive user bases, complex networks, or valuable digital assets that make them prime targets for cyber threats. Among the common users are financial institutions, healthcare providers, government agencies, operators of critical infrastructure, and technology companies.

The Benefits of UEBA

UEBA enhances an organization’s security posture by leveraging behavioral analytics, machine learning, and automation to identify and respond to advanced threats effectively. It improves threat detection capabilities, reduces response times, and provides valuable insights into user behavior for proactive security measures.

Some of the key advantages of using UEBA include:

  • Advanced threat detection
  • Insider threat detection
  • Real-time incident response
  • Reduced false positives
  • User profiling and risk scoring
  • Insider threat prevention
  • Compliance and regulatory requirements
  • Data loss prevention

What is Security Information and Event Management (SIEM)?

A SIEM system is a cybersecurity tool that provides organizations with a centralized and holistic view of their IT infrastructure’s security by collecting, correlating, and analyzing security events and logs from various sources.

The key components and functionalities of a SIEM system include:

  • Log collection
  • Log correlation and analysis
  • Real-time monitoring and alerting
  • Threat detection and incident response
  • Compliance and reporting
  • Centralized security management
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The Threats That SIEM Detects

By using well-defined rules, correlation techniques, and threat intelligence feeds, SIEM systems can detect a wide range of threats and security incidents within an organization’s IT infrastructure.

Some of the common threats that SIEM can detect include:

  • Malware infections
  • Insider threats
  • Network intrusions
  • Account compromise
  • Data breaches
  • Denial of service (dos) attacks
  • Security policy violations
  • Web application attacks
  • Insider trading or fraud
  • Compliance violations

Who Uses SIEM?

SIEM systems are used by various organizations and entities across different industries. While larger organizations often have dedicated resources for managing SIEM systems, smaller organizations may rely on managed SIEM services or cloud-based SIEM solutions provided by third-party vendors.

Some of the typical users of SIEM include:

  • Enterprises and organizations
  • Security Operations Centers (SOCs)
  • Managed Security Service Providers (MSSPs)
  • Regulatory and compliance bodies
  • Incident response teams
  • IT administrators and security analysts

The Benefits of SIEM

SIEM systems provide organizations with better visibility into their security posture, early detection of security incidents, streamlined incident response processes, and improved compliance management. They play a critical role in enhancing security operations, mitigating risks, and protecting sensitive data and assets.

Here are some of the key advantages of using SIEM:

  • Centralized log management
  • Real-time threat detection
  • Early incident identification
  • Efficient incident response
  • Improved compliance and audit capabilities
  • Enhanced threat intelligence
  • Reduced false positives
  • Forensic investigation and reporting
  • Security operational efficiency
  • Proactive threat hunting
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UEBA Security vs SIEM Security – Congruent or Contradictory?

UEBA and SIEM are two distinct cybersecurity technologies that serve different purposes but can be complementary in an organization’s security strategy. Here’s a comparison of the two:

  • UEBA vs SIEM Focus
    UEBA primarily focuses on analyzing user and entity behavior to detect anomalies, suspicious activities, and potential insider threats. It leverages machine learning algorithms and behavioral analytics to establish baselines and identify deviations from normal behavior patterns.

SIEM focuses on aggregating, correlating, and analyzing security events and logs from various sources across an organization’s IT infrastructure. It aims to detect and respond to security incidents by monitoring and analyzing network activity, system logs, and security events.

  • UEBA vs SIEM Data Sources
    UEBA typically analyzes data from user activity logs, endpoint logs, network logs, and application logs. It collects and correlates data related to user behavior, access patterns, and entity interactions to identify potential threats.

SIEM collects and correlates data from a broad range of sources, such as firewalls, intrusion detection systems, antivirus systems, servers, and applications. It includes logs and events from network devices, security devices, operating systems, and applications.

  • UEBA vs SIEM Threat Detection Approach
    UEBA uses machine learning and behavioral analytics to establish baselines of normal behavior for users and entities. It then identifies deviations from these baselines, indicating potential insider threats, insider risks, or abnormal activities that may require investigation.

SIEM utilizes predefined rules, correlation techniques, and threat intelligence to identify patterns, signatures, or indicators of compromise. It detects security incidents by correlating events from different sources and applying rules and logic to detect patterns of malicious or suspicious behavior.

  • UEBA vs SIEM Scope of Analysis
    UEBA focuses on analyzing individual user behavior, entity interactions, and activities within the network. It aims to detect anomalies, account compromises, data exfiltration attempts, insider threats, and other behavioral irregularities.

SIEM provides a broader scope of analysis by correlating and analyzing security events and logs from various sources. It looks for patterns and indicators of security incidents, including network intrusions, malware infections, policy violations, data breaches, and other security-related events.

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UEBA and SIEM Combined: Accomplishing the Highest Levels of Protection

Combining SIEM with UEBA can provide organizations with a more comprehensive and powerful security solution. Here are some benefits and outcomes of integrating SIEM with UEBA:

  • Enhanced Threat Detection
    The SIEM system can leverage UEBA insights to prioritize and contextualize security events, reducing false positives and improving the identification of sophisticated threats, including insider threats and advanced persistent threats.
  • Improved Incident Response
    Security teams can get greater visibility into security events, enriched with behavioral context. This allows for quicker and more accurate incident triaging, investigation, and mitigation, resulting in reduced response times and minimized potential damage.
  • Proactive Threat Hunting
    Security analysts can utilize the behavioral analytics of UEBA to proactively search for potential threats and indicators of compromise within the organization’s network. This proactive approach helps identify hidden or emerging threats that traditional rule-based detection might miss.
  • Insider Threat Detection
    An integrated solution can monitor and analyze user activities, access patterns, and data interactions in real-time. It can identify deviations from normal behavior, potentially indicating insider threats, compromised accounts, or unauthorized activities.
  • Improved Compliance Management
    SIEM can leverage UEBA insights to identify policy violations, non-compliant behaviors, or suspicious activities related to compliance requirements.
  • Advanced User Profiling
    An integrated solution can establish detailed behavioral profiles for users and entities, including their normal activities, access patterns, and deviations. This enables security teams to create risk-based user profiles, assign dynamic risk scores, and trigger alerts or additional authentication measures for high-risk users or entities.
  • Contextualized Security Events
    Security analysts can have a more comprehensive view of an event by understanding the associated user or entity behavior patterns. This context helps in making more informed decisions, prioritizing incident response efforts, and reducing the time required for investigation and remediation.

Conclusion

SIEM and UEBA are two popular cybersecurity tools that organizations use to detect threats in their environments. The threat detection tools serve different purposes, using different kinds of data, but they can be complementary to each other when used together. Combining SIEM with UEBA can provide organizations with a more comprehensive and powerful security solution.

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FAQs

What does UEBA do?

UEBA transforms behavior data from human users and entities such as servers, routers, endpoints, and IoT devices into risk-prioritized intelligence, for the purpose of driving business action. Data science is used to create user and entity behavior baselines from months of historical access and activity. Once behavior baselines are established, analytics monitor user and entity behavior in real-time, for the purposes of predicting and detecting anomalous activity. Real-time is the key here: analytics ingests massive amounts of data and provides insight into what’s actually going on with users and entities in an organization, as it’s happening. The output of security analytics is a single risk score for every user and entity. The risk score provides actionable intelligence on potential risky situations in real-time so organizations can take corrective action.

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What are the 3 pillars of UEBA?

The single most critical factor in differentiating merely anomalous behavior from risky behavior is context. That context comes from the three pillars of behavior: identity, access, and activity. Detecting and stopping insider threats and cybercriminals involves monitoring and linking all three.

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What are 3 types of threat intelligence data?

  1. Indicators of Compromise (IOCs),which are specific artifacts or patterns that indicate the presence of a security compromise or malicious activity. IOCs are used to identify and block or mitigate known threats quickly.
  2. Tactics, Techniques, and Procedures (TTPs),which describe the methods, techniques, and strategies employed by threat actors to carry out attacks or exploit vulnerabilities. TTPs provide insights into the behaviors, tools, and procedures used by attackers, helping organizations understand potential attack vectors and improve their defenses.
  3. Threat Actor Profiles, which provide information about specific individuals, groups, or organizations involved in cyber threats. These profiles include attributes such as the motivations, capabilities, tactics, and history of the threat actors. Understanding threat actor profiles helps organizations anticipate potential threats, identify their targets, and align their security strategies accordingly.
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