MIxmode Blog
The latest stories on Cybersecurity, AI, and everything in between from MixMode
An enterprise’s inability to detect cyber attacks has tangible effects on its productivity and profitability. Various reports have noted a correlation between the time it takes to spot an intrusion and the cost of recovery.
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The world’s reliance on fast, reliable, secure networks has likely never been as apparent as it became in early 2020, when the world responded to the Coronavirus pandemic. Suddenly, vast swaths of the global workforce needed to access and send enormous stores of data from home. In some ways, it couldn’t have happened at a worse time.
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This year on the MixMode blog, we have covered headline stories, analyzed every pain point within network security, and shared what we believe to be some of the most innovative solutions to help you analyze network traffic, surface threats and anomalies, and stop attacks using autonomous AI.
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The best way to detect threats across an entire network in the quickest manner is to have complete visibility over every part of that network with a multi-stream platform which can incorporate not only network data, but Cloud Data and SIEM logs as well.
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Alert fatigue is a top pain point in cybersecurity right now. Security operations center (SOC) analysts are chasing an overwhelming amount of false positive alerts taking time away from analyzing and remediating actual security threats. According to a recent study…
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Effective modern network security needs to defend against an unprecedented number of threats. Today’s SecOps teams face both rudimentary hacking attempts and highly sophisticated, targeted attacks that pose serious safety and security risks.
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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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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.
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.