Mixmode Blog
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The (Recent) History of Self-Supervised Learning
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.
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Guide: The Next Generation SOC Tool Stack – The Convergence of SIEM, NDR and NTA
Traditional security vendors offering solutions like SIEM (Security Information and Event Management) are overpromising on analytics while also requiring massive spend on basic log storage, incremental analytics, maintenance costs, and supporting resources.
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Redefining the Definition of “Baseline” in Cybersecurity
While many security solution providers promise to protect your network by establishing a baseline of your network behavior, the definition of “baseline” can vary widely.
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MixMode CTO Responds to Self-Supervised AI Hopes
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 […]
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Why Training Matters – And How Adversarial AI Takes Advantage of It
The following is an excerpt from our recently published whitepaper, “Self-Supervised Learning – AI for Complex Network Security.” The author, Dr. Peter Stephenson, is a cybersecurity and digital forensics expert having practiced in the security, forensics and digital investigation fields for over 55 years. Section 4 – Why Training Matters – And How The Adversary […]
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New Video: How is MixMode Different From Today’s Network Security Tools?
With MixMode in the center of a program, we will make all the other security investments that you’ve made, better. So when you send data to your SIEM, when you send data to your SOAR, you don’t want those products to be overwhelmed with false positive alerts, with data you don’t need.
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Machine Learning, Deep Learning and Neural Networks, Oh My!
Deep learning makes decisions based upon the data it sees and the data that it doesn’t see but infers from what it does see. This became useful in the AV industry when the adversary introduced polymorphic viruses. These are viruses that change their appearance on the fly and not always in the same way.
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4 Challenges of Stand-Alone SIEM Platforms
While SIEM is undoubtedly a step up from unmonitored network environments, the inherent nature of today’s SIEM software often falls short in several important ways. SIEM is an outdated solution for adequately protecting networks within the modern threatscape.
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Whitepaper: Self-Supervised Learning – AI For Complex Network Security
Artificial Intelligence – or AI – has become a buzzword since it emerged in the 1950s. However, all AI systems are not created equal. In our white paper, “Self-Supervised Learning – AI For Complex Network Security,” Dr. Peter Stephenson explains the different “waves” of artificial intelligence. He uses the DARPA definitions for each of these […]
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