The Problem with Relying on Log Data for Cybersecurity

The Problem with Relying on Log Data for Cybersecurity

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 ... Read More

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 ... Read More
Guide: The Next Generation SOC Tool Stack – The Convergence of SIEM, NDR, and NTA

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 ... Read More
Redefining the Definition of “Baseline” in Cybersecurity

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 ... Read More

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 ... Read More
How is MixMode Different From Today's Network Security Tools?

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 ... Read More

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 ... Read More
4 Challenges of Stand-Alone SIEM Platforms

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 ... Read More
Whitepaper: Self-Supervised Learning – AI For Complex Network Security

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 ... Read More

How the Role of the Modern Security Analyst is Changing

As organizations began to rely more heavily on networking to carry out their operations over the past decade, IT teams added security analyst positions. These professionals focused on network security and providing regulatory compliance oversight. Over time, the role of the security analyst has expanded to include threat hunting tasks ... Read More