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Zero-day threats

Webinar On Demand: Stopping Novel Attacks – Secure Your Business Against Unknown Threats

Blog, Cybersecurity News, Third-Wave AI, Threat Detection, Webinar, Zero Day Attacks / By

Hosted by Mark Ehr, Senior Consulting Analyst for 451 Research Advisors and Igor Mezic, Chief Scientist and CTO for MixMode on Tuesday, November 1st at 1pm EST / 10am PST, they will discuss why security analytics needs to include advanced Third-Wave AI, which autonomously learns normal behavior and adapts to constantly changing network environments, to address the next generation of cyberthreats and increase SOC productivity.

3 Reasons Why a Rule-Based Cybersecurity Platform Will Always Fail

Blog, False Positives, Network Baselines, Network Security, Network Traffic Analysis, Predictive AI, Self-Supervised AI, SIEM, Zero Day Attacks / By

When it comes to advancements in cybersecurity, rule-based systems are holding the industry back. Relying on humans to constantly input and label rules in order to detect and stay ahead of threats is a bottleneck process that is setting security teams up for failure, especially with tools like SIEM, NDR, and NTA.

The Many Ways Your Employees Can Get Hacked While Working From Home and How to Respond

Blog, Network Security, Network Traffic Analysis, Threat Detection, Uncategorized, Unsupervised AI, Zero Day Attacks / By

Although it is not surprising at all that hackers are taking advantage of the global pandemic —phishing threat reports are always highest when there is some natural disaster happening— we have never before had such an unsafe environment to protect. Here are a few of the most popular malicious acts:

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

Blog, Network Detection and Response, Threat Detection, Unsupervised AI, Zero Day Attacks / By

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

Blog, Case Study, Network Detection and Response, Threat Detection / By

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.