Third Wave AI Blogs
The latest stories on Cybersecurity, AI, and everything in between from MixMode
Some of you may have seen the “funny” statistic in the last few months that during the pandemic, ice cream sales are way up while deodorant sales are way down. Let’s just say that, for me, it’s coffee ice cream. Dessert aside, this stat does lead one to think about what other trends occur during a pandemic or a crisis when we look back at events such as world wars, the Great Depression, the Global Financial Crisis (GFC) of 2007-08, etc.
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The transition from office to remote environments was abrupt and one of the most defining moments that the cybersecurity industry and professionals faced in 2020. We wrote about the top issues CISOs were facing throughout the year but also doubled down on sharing insights about the evolution of next-generation SOCs, the failure of SIEM platforms as organizations are experiencing them today, and how self-supervised AI fits into the equation.
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In what the New York Times is calling, “One of the most sophisticated and perhaps largest hacks in more than five years,” malicious adversaries acting on behalf of a foreign government, likely Russian, broke into the email systems of multiple U.S. Federal agencies including the Treasury and Commerce Departments.
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MixMode CTO and Chief Scientist, Igor Mezic, recently contributed an article for Techiexpert that examines three modern AI adversarial attacks, the financial toll they are having on some of our most important systems (including healthcare), and how predictive, third-wave AI is the only future-proof cybersecurity solution to protect organizations from these intelligent attacks.
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A number of recent high profile ransomware attacks on U.S. hospitals have demonstrated the urgency for organizations, municipalities, and critical services to take a proactive approach to protecting networks with a predictive AI solution.
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Despite a three-year SIEM deployment and a two-year UBA deployment, government personnel needed an alternative to better detect and manage threats in real-time, as well as an improved platform for gathering comprehensive data.
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At MixMode our one algorithm is capable of catching any anomaly that may appear on the network. In contrast, other security programs rely on a reactive method of patching and constantly adding to their algorithms each time a hack occurs so that the network learns what to look out for.
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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.