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The marriage of AI (Artificial Intelligence ) and ML (Machine Learning) technologies with cybersecurity tools promises a glorious future. According to Gartner, in 2016, AI and ML, coined with predictive analytics, are becoming a core part of SIEM platforms.

Legacy SIEM ( security information and event management) systems were first available in the nineties and adopted by the security operations center. Although the first generations of SIEMs provide insights into their networks' deep, dark corners, it requires better data analysis and a skilled team to filter out the growing avalanche of false positives to discover the real security threats. Then came the next-generation SIEM. AI-ML SIEM uses modern technology that provides automated, continuous analysis and correlation of all the activities observed within the IT environment. Moreover, the platform can perform preliminary inquiries on detecting threats to cut down a significant number of false cases in security systems.

What Constitute Next-Generation SIEM?

Attackers are becoming more dangerous, and a simple task is enough to keep your security team busy 24×7. Using AI-ML SIEM platforms can enable businesses to track advanced and targeted cyberattacks.

Here are the features of the next-gen SIEM platform, combining the latest technology.

User And Entity Behavior Analytics (UEBA)

UEBA or User and Entity Behavior Analytics is a modern AI- ML SIEM category that uses innovative analytics to discover abnormal and risky behavior by users, machines, and other entities on the corporate network. UBEA can detect security incidents that traditional security tools couldn't detect. The advanced technology analyzes access, and authentication data, establishes user context, and reports suspicious behavior.

Security Orchestration, Automation, And Response (SOAR)

SOAR is a growing area of security that the Next-Gen AI-ML SIEM platform provides. It enables AI-ML SIEM providers to leverage swifter and better-informed decisions. The use of broader intelligence and BIG data will enable reliable threat identification and fewer false positives. Another vital way SOAR influences Next-Gen SIEM is by helping to standardize incident analysis and response procedures. SOAR helps teams become more efficient and focus on threat hunting and patch management by automating security routine actions.

Risk Scoring

Risk scoring is part of the SIEM and user entity behavior and analytics (UEBA) solutions. Cybersecurity risk scoring solutions provide network-wide risk assessment and management workflows to detect deviant behaviors and ensure an organization's security posture. The risk score may range between zero to 100, indicating no risk to maximum risk, respectively. An actual situation may indicate a deviation from regular activity patterns, resulting in an increased risk score. To prevent false alarms, AI-ML SIEM solutions must constantly evolve and learn the routine of every user and entity, ensuring what is considered normal behavior. With these capabilities, an AI-ML SIEM platform can recognize the changes in patterns and bring down the risk score if there's no indication of a threat.

Compliance Reporting

AI-ML SIEM technology has transformed from its original mission of simply monitoring and logging security events to defend the daily cybersecurity attacks while meeting the demands of government and industry compliance. Today the platform provides a comprehensive view of helpful information drawn by normalizing data across different network sources- software applications, databases, servers, and firewalls. An AI-ML SIEM tool provides every business with compliance reporting to collect data, safeguard data storage and automate the creation of regulatory reports.

Advanced Threat Intelligence

The key objectives of advanced threat detection are to understand an organization's vulnerabilities and to have adequate experience and intelligence to mitigate threats. While real risk is often difficult to identify, and preparation for each new threat is impossible, making the best use of AI-ML SIEM technology will help your organization prioritize threats and broaden your armory.

ML And AI-based Alam Analytics

AI-ML SIEM tracks the past incidents and significantly monitors your entire infrastructure by reducing the lead time required to identify and react to any potential network threats and vulnerabilities, helping to strengthen security posture as the organization scales. The platform provides Alam analytics to detect advanced threats beyond chasing down individual events and multiple data sources. Advanced threat analytics is one aspect of a holistic cybersecurity strategy that enables businesses to collect and analyze data on the latest threats from a wide range of sources. 

LTS Secure management 15 years of experience and security solution management veterans. We offer Security Suite to rationalize, prioritize & automate response to risks in your environment. Comprehensive Cyber Security Solutions with continuous monitoring at all layers of the IT stack: network packets, flows, OS activities, content, user behaviors, and application transactions.


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