One of the most prevalent issues impacting the effectiveness of security teams who use SIEM as their primary means of threat detection and remediation is the fact that data logs are an attractive medium for modern hackers to exploit.
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 →
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 …
Why Training Matters – And How Adversarial AI Takes Advantage of It Read More →
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.
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.
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 SIEM is an outdated solution for adequately protecting networks within the modern threatscape.
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 …
Whitepaper: Self-Supervised Learning – AI For Complex Network Security Read More →
For the past few years, many have been talking about the changing “threat landscape” as it pertains to the increase in zero day, insider and phishing threats. While all of these threats are on the rise, and constitute a concern, there is, perhaps, an even larger shift presenting a threat to enterprises – the shift …
The relationship between modern cybersecurity solutions and AI has become inextricable. The unfortunate reality is that even the most talented and responsive SecOps teams are unable to manually catch every threat posed to the sprawling, hybrid networks on which today’s organizations rely. Forward-looking organizations know they need to bring AI and machine learning based security …
Self-Supervised Learning – The Third-Wave in Cybersecurity AI 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 →
