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Better Anomaly Detection Is Key to Solving the False Positive Problem Once and for All

Keeping up with security alerts can be a Herculean task without the right tools on board. Security teams face more than 11,000 alerts per day on average, according to industry analysts — including thousands of false positives triggered by legacy security solutions.

It’s no wonder network breaches are at an all-time high, even among organizations with dedicated SOCs and expensive Cybersecurity platforms. Manually sorting the constant, ever-growing mountain of alerts into true risks, false positives, and low priority issues is a task very few organizations can fully tackle. Even when staffing isn’t an issue — a rarity given today’s IT employment market — surely those workers could be used more effectively on other SOC priorities.

In their joint report “2021 State of Security Operations,” Forrester Consulting and Palo Alto Networks uncovered several eye-popping stats:

  • Security teams face an average of 11,047 alerts every day
  • 10% of respondents said they deal with 25,000 to 50,000 daily alerts
  • More than 25% of all alerts go untouched or ignored
  • Only about 18% of alerts are touched by automation
  • Only 51% of respondents said they felt confident about their security postures

The researchers concluded that most organizations spend their time “triaging and investigating alerts, rather than responding to or hunting for threats and improving processes.” 

How CISOs are Tackling Alert Management 

A recent CSO article highlights several issues facing CISOs in 2021, including the issues around alert management. The article cites a Dec. 2021 report, Security Outcomes Study Volume 2, which identified notable drivers of successful Cybersecurity programs, including:

  • Early, accurate threat detection
  • Quick incident response capabilities
  • Disaster response preparedness

CISOs must develop robust incident response plans to deliver on these three points, according to the CSO article. “To be well prepared,” author Mary K. Pratt writes, “enterprise Cybersecurity teams need to have accurate asset inventories and visibility into all areas of their IT environment; they need to know their organization’s mission-critical systems; and they must understand how to respond if they detect hackers.”

Pratt details several steps CISOs can take to shore up their security postures when an active adversary is present on a network, including taking stock of knowns and unknowns and triaging alerts to quickly surface higher priority risks. It’s also crucial, Pratt writes, to locate points of entry and egress right away.

The MixMode platform is uniquely positioned to achieve each of these high-priority tasks by helping organizations triage alerts in a quick, focused manner, reducing false positives, and providing a real-time, comprehensive understanding of network environments. 

MixMode uses third-wave, self-learning artificial intelligence (AI) to deliver 95% fewer false positives and predictive, real-time threat and anomaly detection across any data stream SOCs might encounter. The platform is data agnostic, operating effectively and independently regardless of data format or type. SOCs can identify threats and anomalies in network traffic, log, API, time series, cloud data and more.

On average, organizations spend more than $1.3 million in the form of 21,000 hours of wasted time investigating false positives and negative security alerts. MixMode filters out the noise, surfacing only those alerts that truly matter, allowing your team to focus and act upon genuine threats.

Unlike legacy Cybersecurity solutions like standalone SIEM, MixMode requires no tuning or rules updates. Instead, the platform uses unsupervised AI to create an evolving baseline of network behavior. And, unlike other typical AI-driven Cybersecurity solutions, MixMode can start identifying anomalies in the first hour, providing immediate value versus the 18 months some platforms need to develop an understanding of network nuances.

Learn more about how your security team can save time and money with MixMode and set up a demo today.

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*** This is a Security Bloggers Network syndicated blog from MixMode authored by Christian Wiens. Read the original post at: https://mixmode.ai/blog/better-anomaly-detection-is-key-to-solving-the-false-positive-problem-once-and-for-all/