MIxmode Blog

The latest stories on Cybersecurity, AI, and everything in between from MixMode

Phishing for Bitcoin: The Twitter Hack Masterminded by a 17 Year Old

By Chris Mitzlaff | August 18, 2020

The evidence indicates that these attackers are traditionally specialized in hijacking social media accounts via SIM Swapping.

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Guide: How to Choose an AI-Based Cybersecurity Platform

By Christian Wiens | August 6, 2020

Most cybersecurity vendors today tout some form of “Artificial Intelligence” as an underlying mechanism for the differentiation of their product among the market. But if everyone is saying they have AI, and everyone is also claiming theirs is the “best,” how can they all be telling the truth?

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Deep Dive: How much time do security teams spend labeling with Supervised Learning?

By Christian Wiens | July 28, 2020

Many CISOs and SecOps teams were faced with a gut-wrenching choice: addressing the operational challenges of keeping workers connected, or shoring up vulnerabilities before hackers exploited them. Both options involved time-consuming, repetitive, manual work.

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Why The Future of Cybersecurity Needs Both Humans and AI Working Together

By Ana Mezic | July 21, 2020

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 More than 55 percent of mundane tasks have been replaced by AI, freeing up analysts for other departmental tasks.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

By Christian Wiens | July 16, 2020

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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The (Recent) History of Self-Supervised Learning

By Christian Wiens | July 7, 2020

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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MixMode CTO Responds to Self-Supervised AI Hopes

By Ana Mezic | June 23, 2020

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

By Christian Wiens | June 4, 2020

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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Self-Supervised Learning – The Third-Wave in Cybersecurity AI

By Ana Mezic | May 28, 2020

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 …

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New Video: How Does MixMode’s AI Evolve Over Time With a Customer’s Environment?

By Christian Wiens | May 14, 2020

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.

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About MixMode

MixMode is the first to bring a third-wave, context-aware AI approach that automatically learns and adapts to dynamically changing environments. MixMode’s monitoring platform, PacketSled, better understands network behavior as it adapts to baseline changes and enables both misuse detection and anomaly detection, as well as predictive maintenance. Used by enterprises and MSSPs for real-time network analysis, threat hunting and incident response, the platform leverages continuous stream monitoring and retrospection to provide network forensics and security analytics. Security teams can integrate PacketSled into their orchestration engine, SIEM, or use PacketSled independently to dramatically reduce false positive alerts and the resources required to respond to persistent threats, malware, insider attacks and nation state espionage efforts.

The company has been named an innovator in leading publications and by security analysts, including SC Magazine, earning a finalist award in 2018 and 2019 for "Best Computer Forensic Solution.” Based in Santa Barbara, with offices in San Diego, the company is backed by Keshif Ventures and Blu Venture Investors. For case studies, continuous product updates and industry news, please visit us at www.mixmode.ai.