Network Security Blogs
The latest stories on Cybersecurity, AI, and everything in between from MixMode
In our newest case study, “How a Major U.S. City Rapidly Modernized Its Cybersecurity Defenses,” we share how the City cut its cyber tool footprint in half, gained visibility into advanced foreign adversary attacks, and greatly improved the productivity of its SOC staff.
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87 percent of organizations use network traffic analysis (NTA) tools for threat detection and response according to ESG, an IT strategy firm. In their 2020 study, 43 percent of organizations surveyed said NTA is a “first line of defense” for detecting and responding to threats.
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Network detection and response, or NDR, has been established as a key tool for companies seeking to improve their threat response. It has become a network security strategy which developed in response to perceived shortcomings in existing network security systems.
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Experts have warned that the Russia-Ukraine conflict poses an unprecedented cyber risk for U.S. organizations as well as State and local governments and municipalities.
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It’s no surprise that organizations are pouring resources into their security approaches, from investments into hardware and software and significant increases in Cybersecurity professional hiring. In fact, industry watchers expect organizations globally to contribute to $1.75 trillion in cumulative spending on Cybersecurity between 2021 and 2025.
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Monthly reports that lack relevant details about an organization’s true risk level are insufficient and not representative of the further steps an organization should take to protect itself. This approach leaves organizations feeling secure against the threat of ransomware while they are actually left exposed to potentially expensive, wide-scale damage.
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When Cybersecurity teams assume that log-based platforms are the best available network security solutions, they have made a decision to invest in “bad gas.” These products will cost more and deliver less than systems enhanced by context-aware AI.
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MixMode announced today their inclusion in the 2021 Gartner report, ‘Emerging Trends: Top Use Cases for Network Detection and Response.’ The report, available only to Gartner users, provides in depth analysis on the top four use cases driving the NDR market including detection, hunting, forensics and response, as well as NDR development recommendations for product leaders.
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A jumble of ineffective, incomplete, extremely expensive platforms that don’t meet the fundamental challenges faced by enterprise SOC teams in the early 2020s is not sustainable.
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In partnership with Ravenii, our 60-minute talk was hosted by MixMode’s Head of Sales and Alliances, Geoff Coulehan, CEO of Ravenii, Jeff Shipley, and MixMode’s CTO & Chief Scientist, Igor Mezic. They discussed key topics including:
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.