MIxmode Blog
MixMode Product Updates, Stories on Cybersecurity, AI, and Everything in Between.
Featured Content
How MixMode’s AI Builds Your Network’s Baseline
Here we describe the type of information that Mixmode’s AI system “looks” at for decision-making, and emphasize how it is human-like in behavior but with a substantially enhanced computational capacity.
Improvements to MixMode’s PQL: Packetsled Query Language
Packetsled Query Language (PQL) addresses the need of analysts to ask questions from large amounts of data without being forced to learn a complicated query language.
Anomaly Detection with Unsupervised AI in MixMode
Here we will discuss some of the opportunities and challenges that can arise with anomaly detection as well as MixMode’s unique approach to the solution using Unsupervised AI.
ALL BLOGS
No one really wants to talk about the fact that most security products are rules-based systems that may check a box for compliance but do not deliver intelligent, actionable data.
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Security experts and researchers are harnessing AI and ML to create products and solutions for an industry faced with rising and highly intelligent cybercrime and legacy stacks that leave advanced breaches undetected.
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Network Traffic Analysis (NTA) is one of these newer advancements in cybersecurity. NTA allows the analysis of network traffic (hence the name) at a granular, packet-by-packet level.
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Not only is artificial intelligence necessary for keeping up with the onslaught of lower-tech attacks, but also, AI is becoming crucial for defending against AI-powered cyberattacks, which are just on the horizon.
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When revisiting Mixmode API eliminating data over-fetching was one of the key areas that we focused on for our 6.1.8 release.
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Zero-day attacks cost businesses millions of dollars in lost revenue and recovery costs and can cripple a company that is not prepared to respond decisively and effectively.
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Not all Artificial Intelligence is created equal. As we move towards a future where we lean on cybersecurity much more in our daily lives, it’s important to be aware of the differences in the types of AI being used for network security.
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Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably when discussing developments in deep learning. However, there is an important difference between the two that network security professionals will need to understand in order to serve their clientele effectively.
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The cybersecurity industry is in need of a massive shakeup. Rules-based software has created an exponential increase in false positive security alerts and zero-day threats are on the rise.
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In the face of intelligent cyber threats, the best defense is to supplement traditional methods with anomaly detection through unsupervised artificial intelligence (AI).
Read MoreAbout 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.