Mixmode Blog
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Webinar Recap: The Failed Promises of SIEM
MixMode teamed up with Ravenii to host a webinar focused on the history and evolution of SIEM platforms, their ideal role in a SOC today, and how they fall short as a threat detection tool in today’s modern cybersecurity environment.
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The Evolution of SIEM
It should be noted that SIEM platforms are exceptionally effective at what they initially were intended for: providing enterprise teams with a central repository of log information that would allow them to conduct search and investigation activities against machine-generated data. If this was all an enterprise cybersecurity team needed in 2020 to thwart attacks and stop bad actors from infiltrating their systems, SIEM would truly be the cybersecurity silver bullet that it claims to be.
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Whitepaper: The Failed Promises of SIEM
The fundamental SIEM flaws lie in the platform’s need for continual adjustment, endless data stores, and a tendency to create an overwhelming number of false positives. When organizations instead turn to a next-generation cybersecurity solution, which predicts behavior with an unsupervised (zero tuning) system, they are poised to save on both financial and human resources.
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How Data Normalization in Cybersecurity Impacts Regulatory Compliance
Complying with privacy regulations requires all organizations to have access to data on demand, wherever it lives on a network. With the unfathomable amount of data managed by most organizations operating in the finance space today, it can become a significant challenge to locate specific data across legacy systems and networks with countless connections online and off.
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Webinar: The Failed Promises of SIEM – What’s Next For Cybersecurity
The Security Operations Center (SOC) of today is fundamentally flawed. Currently enterprise cybersecurity spend is higher than ever, but despite multi-million dollar cybersecurity investments, organizations remain vulnerable to attacks. One of the major reasons for this is legacy SIEM deployments. More spend does not equal more security.
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3 Reasons Why a Rule-Based Cybersecurity Platform Will Always Fail
When it comes to advancements in cybersecurity, rule-based systems are holding the industry back. Relying on humans to constantly input and label rules in order to detect and stay ahead of threats is a bottleneck process that is setting security teams up for failure, especially with tools like SIEM, NDR, and NTA.
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Why Data Overload Happens and Why It Is a Problem for Cybersecurity Teams
Handling and managing data today has become unwieldy for IT teams on multiple fronts, but the security impact is especially troubling.
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Why SIEM Has Failed the Cybersecurity Industry
The time required for data processing, transition, aggregation, and the normalization does not allow real-time threat detection using today’s SIEM solutions. The only beneficiary of security through log aggregation is the SIEM vendor.
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Data Overload Problem: Data Normalization Strategies Are Expensive
Financial institutions spend five to ten million dollars each year managing data. A recent Computer Services Inc (CSI) study reveals that most banks expect to spend up to 40 percent of their budgets on regulatory compliance cybersecurity, often adopting expensive data normalization strategies.
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