Mixmode Blog
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Why The Future of Cybersecurity Needs Both Humans and AI Working Together
A recent WhiteHat Security survey revealed that more than 70 percent of respondents cited AI-based tools as contributing to more efficiency. More than 55 percent of mundane tasks have been replaced by AI, freeing up analysts for other departmental tasks.
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Our Q2 Top Cybersecurity Insights
Since we determine everything on data here at MixMode, we went into our website data to see which of our Q2 articles got the most traffic over the past few months. Not surprisingly, the majority of our top articles covered topics on the advancement of AI in cybersecurity and network traffic analysis (NTA).
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NTA and NDR: The Missing Piece
Most SIEM vendors acknowledge the value of network traffic data for leading indicators of attacks, anomaly detection, and user behavior analysis as being far more useful than log data. Ironically, network traffic data is often expressly excluded from SIEM deployments, because the data ingest significantly increases the required data aggregation and storage costs typically 3-5x.
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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.
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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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