SIEM

Featured Use Case: Why a Large US Utility Company Turned to MixMode to Address Utility Grid Vulnerabilities

A large utility company approached MixMode with the following scenario: The enterprise SOC was utilizing a shared SIEM application that was being utilized by several stakeholders: the networking team, the SCADA team, the dev-ops team, the compliance team and cybersecurity teams for “basic search and investigation of log files to meet regulatory compliance requirements”.

How Vendors Capitalize on SIEM’s Fundamental Flaws

Because the fundamental nature of SIEM requires infinite amounts of data, security teams are forced to constantly wrangle their network data and faced with an unmanageable number of false positive alerts. This means they have to devise efficient ways to collect, organize and store data, resulting in an incredible investment in human and financial resources.

The Case Against Using a Frankenstein Cybersecurity Platform

The cybersecurity market has, simply put, been cobbled together. A tangled web of non-integrated systems and alerts from siloed systems. Enterprises are now being forced to utilize a “Frankenstein” of stitched together tools to create a platform that might cover their security bases.

Improving on the Typical SIEM Model

Despite its inherent flaws, today’s SIEM software solutions still shine when it comes to searching and investigating log data. One effective, comprehensive approach to network security pairs the best parts of SIEM with modern, AI-driven predictive analysis tools. Alternatively, organizations can replace their outdated SIEM with a modern single platform self-learning AI solution.

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.

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.

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.

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.

NTA and NDR: The Missing Piece

Most SIEM vendors acknowledge the value of network traffic data for leading indicators of attacks, anomaly detection, and user behavior analysis as being far more useful than log data. Ironically, network traffic data is often expressly excluded from SIEM deployments, because the data ingest significantly increases the required data aggregation and storage costs typically 3-5x.

How the Role of the Modern Security Analyst is Changing

As organizations began to rely more heavily on networking to carry out their operations over the past decade, IT teams added security analyst positions. These professionals focused on network security and providing regulatory compliance oversight.  Over time, the role of the security analyst has expanded to include threat hunting tasks. That is, evaluating security platform …

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