UEBA Speeds up Threat Detection Earlier in the Kill Chain

User and Entity Behavior Analytics (UEBA) has proven to be the most effective approach to end-to-end management and monitoring of identity-based risks and unknown threats across all enterprise environments. UEBA security draws on the context of big data. It is driven by machine learning models rather than signatures or rules to provide invaluable visibility and risk assessment of suspicious activity.

UEBA uses algorithms and machine learning to detect anomalies in the behaviour of users and non-human entities such as routers, servers, endpoints, and other network devices. UEBA looks for unusual or suspicious behaviour that deviates from the baseline of standard day-to-day patterns or usage. For example, if a particular user typically logs into the network from an Atlanta IP address, and on a given day, the same user credentials log in from both an Atlanta address and a Los Angeles IP address during a two-hour window, the UEBA security system would consider this an anomaly. You can send an alert to a security administrator, or if automation is in place, the user can be automatically disconnected from the network until the situation is investigated.

Critical UEBA Solution Use Cases from the Latest SOC

 UEBA Solution quickly identifies anomalous activity to maximize timely response to incidents and automated risks. A wide range of use cases makes UEBA scalable and valuable. For organizations to effectively address cybersecurity challenges, their use cases must meet their specific needs and diverse requirements now and in the future.

Below are critical UEBA use cases to support a modern next-gen Security Operations Center (SOC). Protection

• Account Compromise, Takeover and Sharing Detection
• Insider Risk and Threat Monitoring
• Anomalous Activity Monitoring
• Host/Device Compromise Detection
• Lateral Movement Detection
• Reconnaissance Monitoring
• Security Misconfiguration Detection identification

Industry-Specific UEBA Use Cases

 LTS Secure also provides industry-specific pre-packaged analytics for healthcare, finance, government, retail, manufacturing, and insurance use cases. These models focus on addressing the unique challenges and threats of each industry. This reduces customization or implementation efforts to create industry-specific models from scratch. Developed in collaboration with the LTS Secure team, technology, channel partners, and customers, these models consider telemetry from specialized systems, fraud/threat scenarios, and standards.

Key Benefits

 The breadth of UEBA use cases assures customers that their advanced security analytics needs are met. Common benefits include: 

• Enhanced Security Capabilities and Quality – UEBA’s mature capabilities provide robust and optimal advanced security analytics across various on-premises and hybrid environments, risk assesses grey areas of unknown threats, and Minimizes false positives. The result is a better focus for “find and fix” resources, optimized security analyst time, streamlined SOCs, and improved process and staff productivity.

• Enhancement and Optimization, Detection, Monitoring, and Visibility – This includes the essential ability to view the full context of user access and activity, both legitimate and anomalous. UEBA also includes analytics for hybrid environments, providing a combined 360-degree view of identity and risk-rated behavioural anomalies. You can power it by machine learning as part of the newly you can recognize state-of-the-art UEBA standard and powerful capabilities that increase efficiency by interfacing with identity and accessing analytics.

• Increase Productivity and Reduce Costs – Maximize efficiency and reduce costs for your SOC team with comprehensive visibility across your organization’s environment, users, and devices. As organizations continue to move to cloud applications, the platform you can extend without deploying additional solutions, thus minimizing costs.

To know more for UEBA, visit https://en.wikipedia.org/wiki/User_behavior_analytics.