Network Detection and Response

A Well-Equipped Security Team Could Save You Millions of Dollars a Year

Data breaches are expensive. By now, most organizations are well aware of this fact. When it comes to resource planning, however, SecOps teams need concrete data to ensure adequate funding is available to handle a breach.

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Network Data: The Best Source for Actionable Data in Cybersecurity

With the right tool, your network data can now provide you with most valuable, actionable alerts in your security stack. What follows is a discussion of some of the reasons why you may want to look to your network first when trying to identify potential threats or attacks.

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Staying CCPA Compliant with MixMode’s Unsupervised AI

Companies are expected to spend up to $55 billion dollars on efforts to comply with the California Consumer Privacy Act (CCPA), which is still working out its final rules after going into effect this month.

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Yesterday’s SIEM Solutions Can’t Combat Today’s Cyberthreats

While it’s true that having a SIEM is better than forgoing network monitoring all together, a standalone SIEM solution is simply insufficient in today’s cybersecurity landscape. Hackers and other bad actors have become more sophisticated — many of today’s cybercriminals can easily outsmart a standard SIEM setup.

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Our Top 5 Cybersecurity Insights from 2019

This year on the MixMode blog, we have covered headline stories, analyzed every pain point within network security, and shared what we believe to be some of the most innovative solutions to help you analyze network traffic, surface threats and anomalies, and stop attacks using autonomous AI.

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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.

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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.

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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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