Cybersecurity teams working in municipal settings face a constant struggle — protecting vital public network infrastructure with limited resources. The situation can reach a breaking point when these teams become overwhelmed managing false positive and negative flags triggered by legacy cybersecurity solutions.
In the report, 451 Research explains why security analytics needs to include advanced Third-Wave AI, which autonomously learns normal behavior and adapts to constantly changing network environments, to address the next generation of cyberthreats and increase SOC productivity.
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.
It’s the open secret no one’s talking about — too many cybersecurity solutions in the marketplace stand no chance of providing comprehensive coverage because they are incapable of handling data arising from all sources. Many available solutions are effectively legacy platforms hiding within fresh marketing packages.
Many vendor claims are unclear as to what they’re promising in this space, but they are quite insistent that without Zero Trust network architectures, organizations are at great risk for data breaches and other network sabotage.
MixMode Whitepaper: Authentication Does Not Equal Zero Trust A quick glance at current Cybersecurity vendor offerings will reveal an emerging marketing buzzword: Zero Trust. But it’s important to not dive into a Zero Trust investment until you’re well armed with the fundamentals. What is Zero Trust? Why do you need it? How do you know …
MixMode Whitepaper: Authentication Does Not equal zero trust Read More →
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.
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.
ou may be surprised to learn that log data is proprietary to each security platform vendor. There is no standard format or even a standard labeling mechanism. Your data only has context within the parameters of your SIEM vendor.
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:
We recently released a new video to better explain how MixMode’s next-generation cybersecurity anomaly detection platform combines the functionality of SIEM, NDR, NTA and UEBA for advanced threat detection, zero day attack identification, false positive alert reduction, forensic investigation and more.
It’s evident that while organizations are spending more and more on legacy cybersecurity solutions, these platforms are not holding up their end of the deal and are not able to proactively defend in a modern, non-signature attack threatscape.
Unfortunately, the majority of cybersecurity solutions available today rely on outdated applications for AI. So-called first- and second-wave AI solutions don’t cut it, but few vendors have the technical capabilities and know-how to apply cutting edge, third-wave AI to their platforms.
On the surface, an “incremental stacking” approach to correlative analysis platforms like SIEM, XDR and UEBA is logical. Organizations can overcome some of the inherent limitations present in their security solutions by adding a network traffic analysis (NTA), for example. Industry analysts have been touting this approach for some time now as necessary for full coverage enterprise security.
Cybersecurity vendors promise the moon when it comes to AI. As the recent TechRepublic article, “Why cybersecurity tools fail when it comes to ambiguity,” makes clear, often, these promises fail short in real world network environments.
The next cybersecurity challenge lies with the advances in quantum computing that are set to revolutionize tech while simultaneously equipping threat actors with a new arsenal of cyberweapons.
Staying on top of cybersecurity risk can feel like a losing battle in today’s modern, hyperconnected reality. The influx of IoT devices and increased reliance of BYOD devices has created a diverse, complex threatscape rife with overlapping vulnerabilities across physical and cyber assets.
Every network vulnerability opened new opportunities for hackers to infiltrate systems, steal data and wreak havoc. Several notable security incidents have left governments, private organizations, medical systems and large enterprise networks reeling. Many of these entities have discovered that their security plans are simply not up to the task of mitigating modern cybersecurity threats.
The only truly workable network solution must bridge the inherent gaps that exist throughout [infrastructure] systems. It must also be capable enough to root out hidden vulnerabilities ripe for hacking.
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.
