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Despite AI’s potential to help defend against cyber attacks, AI adoption in cybersecurity practices remains in its early stages. Why is this the case, and how can organizations overcome these hurdles to pave the way for a secure future?
The SANS Institute recently released an analyst First Look Report on MixMode titled, “Self-Supervised Learning Cybersecurity Platform for Threat Detection.” Matt Bromiley, Senior Security Analyst at SANS and author of the report, explores the barriers SOCs face to conquering the vast amounts of data generated by modern enterprises and the solutions that MixMode provides for detecting and investigating threats including our utilization of self-supervised AI for cybersecurity.
Keeping up with security alerts can be a Herculean task without the right tools on board. Security teams face more than 11,000 alerts per day on average, according to industry analysts — including thousands of false positives triggered by legacy security solutions.
Real unsupervised AI spots security issues sooner and predicts future behavior more accurately than older first- and second-wave solutions. Self-supervised AI technology draws on an understanding of the fundamental nature of the network where it lives, an understanding that isn’t possible with supervised-AI.
Yann LeCun and Yoshua Bengio were recently interviewed by VentureBeat Magazine on the topics of self-supervised learning and human-level intelligence for AI. Our CTO Dr. Igor Mezic sat down with our team to discuss some of the most interesting pieces of the LeCun article, and offer a potential solution to a search for truly self-supervised …
MixMode CTO Responds to Self-Supervised AI Hopes Read More →
COVID-19 has caused most corporate businesses that remain open to shift to a work from home, remote workplace. Because of this, the cybersecurity industry has been turned on its head. Security teams went from monitoring and protecting established network environments to quickly pivoting their tools, resources, and oversight to manage a distributed workforce. This has …
One Thing All Cybersecurity teams Should Have During COVID-19 Read More →
The world’s reliance on fast, reliable, secure networks has likely never been as apparent as it became in early 2020, when the world responded to the Coronavirus pandemic. Suddenly, vast swaths of the global workforce needed to access and send enormous stores of data from home. In some ways, it couldn’t have happened at a worse time.
MixMode leaders John Keister, Dr. Igor Mezic, Bryan Elliot, and Russell Gray share how the single algorithm that is the foundation of MixMode’s self-learning AI can understand and continually build a generative baseline of your network without human training.