Network Detection and Response

Generative Unsupervised Learning vs. Discriminative Clustering Technology: Which Prevents Zero-Day Attacks?

Knowing the difference between Discriminative and Generative Unsupervised Learning can tell you a lot about the effectiveness of a cybersecurity solution’s artificial intelligence, for example, whether or not that security solution can perform actions like identifying and stopping a zero-day attack.

Case Study: MixMode AI Detects Attack not Found on Threat Intel

In October, 2019 a MixMode customer experienced an incident where an external entity attacked a web server located in their DMZ, compromised it, and then pivoted internally through the DMZ to attempt access of a customer database. While the attacker was successful in penetrating the customer’s network, MixMode was able to detect the event before they were successful in penetrating the customer database.

What is Network Detection and Response (NDR)? A bEginner’s Guide

Recently, network detection and response, or NDR, has been established as a key tool for companies seeking to improve their threat response. It’s a relatively new network security strategy which developed in response to perceived shortcomings in existing network security systems.  We wanted to help explain what modern network detection and response is, how it …

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Threat Hunting and Endpoints – A Dr. Stephenson tutorial

“Packetsled provides the enrichment that triggers early warnings and proactive action to prevent breaches.” Dr. Stephenson SC Magazine’s Dr. Peter Stephenson analyzes the best threat hunting platforms in cyber security. Read the full blog here About MixMode MixMode is the first to bring a third-wave, context-aware AI approach that automatically learns and adapts to dynamically changing environments. …

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