Zero-day threats

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.

Silicon Valley Needs to Step up Their Security: This Week in AI

Silicon Valley Has Let Its Cybersecurity Guard Down According to an article by Brian O’Keefe for Fortune Magazine, Silicon Valley isn’t paying enough attention when it comes to threats posed by state-sponsored hackers. At least, that was the conclusion a group of cybersecurity experts came to in a discussion at the Fortune Brainstorm Tech conference in Aspen, Colo., on …

Silicon Valley Needs to Step up Their Security: This Week in AI Read More →

AI-Enabled Cybersecurity Is Necessary for Defense: Capgemini Report

850 senior executives from Information Security, Cybersecurity, and IT Operations in seven industries across ten countries were recently surveyed by consulting and technology services firm, Capgemini, in their “Reinventing Cybersecurity with Artificial Intelligence” report. The goal being to understand today’s benefits, complexities, and levels of implementation of AI in cybersecurity across IT (information technology), OT (operation …

AI-Enabled Cybersecurity Is Necessary for Defense: Capgemini Report Read More →

The Endpoint Gap in Corporate Security

“The biggest misconception people have about endpoints is that they have an idea of what their endpoints really are. The security industry has rightly taught defense-in-depth & blocking. However, too many companies rely solely on that concept, and aren’t prepared for what happens when something is breached. That breach, when it happens, will take place …

The Endpoint Gap in Corporate Security Read More →

SC Magazine: Beefing Up Your Next Generation Security Tool Set

Originally published on 5/20/19 on scmagazine.com, this article by Dr. Peter Stephenson is the first in a four-part series to help enterprise and security professionals discover the tools needed to deploy a next-generation enterprise security stack. As it features MixMode as the true AI system needed for your deception network, we wanted to share the article here on our …

SC Magazine: Beefing Up Your Next Generation Security Tool Set Read More →

How AI is Solving the False Positives Problem in Network Security

How AI is Solving the False Positives Problem in Network Security By Ana Mezic, Marketing Coordinator at MixMode The term “False Positives” is trending in the cybersecurity industry right now. Rightfully so. Managing the impossible amount of alerts IT teams get from their cybersecurity software is an issue that demands a solution as hackers and gatekeepers play tug-of-war …

How AI is Solving the False Positives Problem in Network Security Read More →

5 Reasons Why Context-aware Artificial Intelligence (Caai) Is Needed in Cybersecurity

5 reasons why Context-Aware Artificial Intelligence (CAAI) is needed in Cybersecurity CAAI delivers understanding of the network baseline and reducing false positives By Dr. Igor Mezic, CTO and Chief Scientist  Artificial Intelligence (AI) has surfaced as the technology of the day, in the same way internet, personal computers, airplanes and cars have in earlier eras. And, just like these others …

5 Reasons Why Context-aware Artificial Intelligence (Caai) Is Needed in Cybersecurity Read More →