Existing security tools such as SIEMs are based on rules and thresholds, which obscures threats in a flood of false positive. Extract the signal from the noise with Interset security analytics platform.

How does security analytics make a SIEM smarter?


Interset security analytics analyzes billions of events from SIEMs and other security tools to deliver a prioritized list of threat leads.

Don't Replace Your SIEM. Embrace it with Security Analytics.


Security information and event management (SIEM) systems are often a cornerstone in today’s security operations centers. But they are reliant upon static, rules-based or binary ‘good/bad’ approaches which are not well-suited to the speed and scale of the modern digitally connected world. The static nature of the rules requires frequent updates and to make rules works, a threshold is often involved, leading to too many false positives and a flood of alerts.

Security analytics augments a SIEM with an analytical brain that processes data faster than humanly possible to detect hidden threats. The SIEM investment is protected and additional value is unlocked from the rich cyber log data stored there.

In fact, security analytics uniquely augments other all existing security tools ‒ not just your SIEM, but also data loss prevention (DLP) , identity access and management (IAM), and other solutions. Security analytics makes your existing security solutions smarter by providing a machine learning brain that never sleeps and enables automated, big-data-scale and speed analysis of your entire ecosystem of security and business data.

Transform Threat Detection and Threat Hunting


The more data you give Interset’s analytics platform, the smarter it gets. Persistent, morphing, elusive threats, such as malware infiltrations and insider threats, simply cannot hide. Interset integrates with other security tools (such as SIEM systems) to analyze countless data sources and applies machine learning to extract a list of prioritized threat leads for the security team to radically accelerate threat detection and response.

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Streamline Security Operations


Empower SOC teams by giving them less false positives and more qualified threat leads. With Interset’s 400+ machine learning models your SIEM gets smarter with big data enabled machine learning and AI.

When augmenting your security toolset, SIEM, DLP, IAM, EDR and more, with integrated security analytics, you gain a unified view of enterprise risk across a fragmented landscape of security tools. By adding an automated brain, you maximize your investment in each tool, as the whole is greater than the sum of its parts.

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Eliminate Alert Fatigue


The rules- and thresholds-based approach of most SIEM vendors and other existing security tools produces too many false positives and a flood of alerts. A SIEM augmented with security analytics distills billions of events into a handful of prioritized leads so that security teams can spend less time chasing false positives and more time stopping genuine threats.

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The Business of Security


Augmenting your security tool set with analytics improves risk visibility and enables more holistic cyber-risk management. A platform approach to security analytics makes every other security tool — SIEM, DLP, IAM, EDR, etc. —  smarter, reducing security gaps and improves an enterprises security posture. By optimizing your existing security investments with additional intelligence, enterprises maximize SOC team efficiency and reduces risks of insider threats and data-breach fallout.

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The Evolution of SIEM Software


SIEMs are evolving to adapt to the modern age. The speed and scale of modern cybersecurity needs can no longer be fulfilled by a product category first designed a decade ago. The latest SIEM innovations involve scaling solutions to the rate of data storage and processing required today — a clear requirement for a big data architecture. To keep pace with the problem at hand, modern SIEMs must adopt a native Hadoop architecture to be able to collect the sheer volume, variety, and velocity of incoming security data.

At the same time, more than collection is now required, and the ability to process and analyze the incoming security data is critical as human teams can no longer rely on manual rules and threshold approaches to keep pace with sophisticated cyber attacks. Integrated User and Entity Behavioral Analytics (UEBA), powered by machine learning must be integrated with existing SIEM platforms.

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