Christian Wiens is Director of Marketing at MixMode. He has 10+ years of experience as a cybersecurity professional. He has his BA from The University of California, Berkeley and resides in Austin, TX.
A large U.S. city’s cybersecurity leader has been at the forefront of adopting new technology to solve the fundamental problem perplexing cybersecurity leaders everywhere: how can we reduce our ever-expanding, costly and inefficient cyber tool footprint while also increasing the effectiveness of our cyber defenses and the productivity of our lean SOC team?
With years of experience as a veteran cybersecurity leader, the City’s CISO described this fundamental problem faced by all CISOs explaining:
“For 15 years I have been trying to implement a cyber defense that surfaces increasingly sophisticated threats in real-time, with the least amount of maintenance and cost. This problem has grown exponentially with exploding cloud utilization, architecture and network complexities. The good guys have fallen too far behind the advanced threat actors.”
When the City’s leadership team was approached by a Federal agency notifying them of active targeting by a foreign nation state sponsored threat actor using advanced techniques designed to circumvent traditional rule and threshold-based cybersecurity tools, they knew the City could no longer rely on its expansive, costly and ineffective legacy systems.
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.
MixMode worked with the City’s cybersecurity team to deploy a next-generation SOC platform using Self-Learning Artificial Intelligence to enable real-time visibility into all threats and anomalies in their network, both known and novel (like zero-days), consolidate their legacy toolset, and improve the productivity of their SOC team.
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