MIxmode Blog
The latest stories on Cybersecurity, AI, and everything in between from MixMode
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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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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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).
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Whether your network analysts are spending too much time on false positives or neglecting to recognize false negatives, when actual cyber threats go unnoticed, fear not. Here are 4 ways to combat false positives and negatives in your network security program.
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Recent cybersecurity news, trends, and highlights and how artificial intelligence (AI) is transforming the industry.
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Mixmode’s platform utilizes third-wave, context-aware AI to inform the user of threats (including Zero-Day, and encrypted traffic) on their network, and reduces the rate of false positives in intel and alerts consistently by 90% or more.
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.