The era of individual threat actors has been replaced by organized syndicates utilizing sophisticated processes to break through expansive networks and IT architecture. A robust security tool is needed to combat insider threats and commodity malware within an organization. RSA NetWitness’ User and Entity Behavior Analytics (UEBA) capabilities use big data analytics and automated threat detection features to secure networks. RSA NetWitness UEBA features can be deployed for:
- Insider Threat Detection
- Brute Force Detection
- Malware Detection
- Automated Incident Response
- Behavioral Data using Artificial Intelligence
Insider Threat Detection
RSA’s UEBA functions are largely turnkey. The tool protects against Advanced Persistent Threats (APTs) by integrating the use of RSA NetWitness Platform’s log collection, endpoint visibility, and data analytical tools to detect sophisticated attacks. The threat detection process focuses on both internal and external threats to ensure detection and mitigation before they can do major harm to IT systems. The platform provides contextual notification alerts, which reduce false positives and simplifies tasks for security teams.
Organizations can face serious consequences when not prioritizing internal threat actors. Unwitting employees can often be the source of data leakage or malware installation. Even more sinister are retaliatory employees or corporate espionage.
Brute Force Detection
In today’s threat landscape Distributed Denial of Service (DDoS) attacks are commonplace and can overwhelm security teams. RSA NetWitness’ UEBA integrations take advantage of big data analytics and the MITRE ATT&CK framework. The speed at which brute force attacks can be detected and eliminated is vital for security teams and complex IT infrastructures.
Malware has become all too common for organizations. Often it is not a question of if an organization will face malware, but when.
Although common malware is dangerous, commodity malware takes things a step further by providing cyber criminals with professional-grade attack tools for breaching IT systems. RSA NetWitness UEBA tools are capable of detecting advances malware and analyzing attack patterns behind these attacks. This provides the data needed to secure networks from future attacks while enhancing the tool’s ability to discover new or mutated malware.
Automated Incidence Response
Automation can be incredibly helpful when facing large alert volumes. Follow up can be lacking when more pressing issues are at hand. Following up threat detection with an adequate response in real-time ensures organizations do not experience downtime while dealing with threats. NetWitness’ UEBA features integrate artificial intelligence and machine learning to refine its response capabilities to discovered threats. UEBA also provides security teams with incident reports and actionable insights to enable them to respond to cyber incidence with accuracy and speed.
Behavioral data using Artificial Intelligence
RSA utilizes data analytics and artificial intelligence to better understand user behavioral patterns ensure normal activities can easily be differentiated from suspicious ones. UEBA employs an identity-based chronological visualization process which quickly picks up on abnormal patterns across expansive networks. The ability to delve deeper into attack patterns showcase the perspective of hackers and cyber criminals to security teams. This helps in developing robust security measures for enterprise networks.
RSA NetWitness UEBA’s Value-Added Proposition
As a solution for detecting and responding to advanced cyber threats, the platform’s UEBA offers its users multiple key features. These features cut across data collection, a risk-scoring engine, and identity-context visualization. Security teams can take advantage of the UEBA features for:
Automated, unsupervised behavioral machine learning
Continuous monitoring is key to detecting threats in real-time and the ability to execute behavioral analytics without supervision. The automated continuous analytical process delivers a preemptive approach to threat detection. The machine learning capacity of UEBA also makes it possible to detect yet-to-be-seen threats and techniques cyber criminals may deploy soon.
A simplified risk-scoring engine
Prioritizing incident response to eliminate the most dangerous threats is vital when dealing with incidents in real-time. The UEBA risk-scoring engine uses data science to discover and visualize an organization’s risk exposure. The threat detection engine is also capable of piecing together disjointed cyber incidents from a common base. Security teams can then access and visualize risk reports using a streamlined user interface.
Automated false positive reduction
UEBA provides visibility across each endpoint within complex or sprawling networks. This visibility empowers security teams to speed up detection times and investigations into threats. Combined with its threat forecasting features, the tool reduces false positives and alert fatigue in security teams.
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