Interset 5.6 Zeroes in on Endpoint Security with AI-enabled Security Analytics

New and expanded analytics for the endpoint help organizations identify zero-day attacks


OTTAWA, May 31, 2018 (GLOBE NEWSWIRE) -- Interset, a security analytics company powered by self-learning AI, today announced Interset 5.6. This latest version of Interset’s AI-enabled security analytics platform delivers powerful new analytics and investigation capabilities that help companies fortify security — starting at the endpoint.

“Endpoint data is extremely rich and it can reveal important security gaps or threats. Unfortunately, endpoint security traditionally relies on signature-based methods that require a threat “definition” to identify infections — something that severely limits protection against constantly changing endpoint threats and zero-day attacks,” says Mark Smialowicz, CEO at Interset. “Behavioral analytics powered by unsupervised machine learning bolsters endpoint defense by eliminating the need for signatures and instead looks for anomalies based on what an endpoint’s normal operations look like day after day.”

“The most visionary and leading of vendors in 2018 and 2019 will be those that use the data collected from their endpoint detection and response (EDR) capabilities to deliver actionable guidance and advice that is tailored to their clients,” said Gartner.¹ “Detecting known indicators of compromise (IOCs) and suspicious behavior is only one side of the enterprise protection platform (EPP) coin — solutions must detect and proactively alert on weaknesses or vulnerabilities that are being exploited right now, or are likely to be exploited in the future. The fast-moving nature of attacker tools, techniques and procedures means that an organization's endpoint security strategy must be continually assessed and adapted.”

Interset 5.6 features additional models for EDR data, building on the platform's existing catalogue of more than 400 unsupervised machine learning models. The new models emphasize threat detection for data-exfiltration and infected-host use cases by detecting anomalies in port usage, inbound or outbound data transfers and processes. Interset’s behavioral analytics approach to endpoint security makes it uniquely positioned to detect zero-day attacks, which typically involve brand new strains or versions of malware or viruses. Most antivirus and antimalware solutions struggle to identify these attacks without having been introduced to IOCs that are associated with a specific malware — something that is not possible with zero days. Using unsupervised machine learning (a type of self-learning AI), Interset dynamically measures millions of individual behavioral baselines for users and machines to detect anomalies that are typically missed by other solutions.

Interset 5.6’s enhancements help organizations further integrate the threat detection platform into their existing security ecosystems. Click here to learn more about Interset’s latest endpoint-focused updates.

Availability

  • Interset 5.6 is available now.

Learn more

Citations

¹Gartner, “Magic Quadrant for Endpoint Protection Platforms”, McShane, I., Litan, A., Ouellet, E., & Bhajanka, P., January 24, 2018.

About Interset
Interset, a security analytics company powered by self-learning AI, augments existing security tools and empowers security teams to identify and respond to the threats that matter before data is stolen. Interset’s machine learning threat detection platform measures the unique digital footprint of systems and users, distilling billions of events into a handful of prioritized threat leads. What used to take months, can now take minutes. Interset is backed by In-Q-Tel and trusted to protect critical data in finance, critical infrastructure, high-tech manufacturing, healthcare, utility and energy industries. Visit us at interset.ai, and follow us on Twitter, LinkedIn and Facebook.

Contact
Gretha Loubser
gloubser@interset.com
(844) 241-2163

A photo accompanying this announcement is available at http://www.globenewswire.com/NewsRoom/AttachmentNg/68bdf32c-2f91-46eb-8ef1-2f47c5801fa2

Detecting Zero-day Attacks with Behavioral Analytics