Increasingly complex cyber threats are pushing SOC analysts to ‘up their game’. It has become critical to quickly understand how an attacker has gained access, what techniques were used to breach your systems, where they have been, and what they have done. Capabilities such as Incident Correlation and leveraging the MITRE ATT&CK framework are being used to improve the SOC investigative processes.
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3 lessons energy and utility cyberattacks have taught
Posted on - by Carter Foster
Recent attacks indicate that energy and utility companies need to increase their security posture sooner rather than later. Because energy companies are so entwined with local and global operations, attackers can see significant financial gains, cause widespread infrastructure disruption, or steal coveted intellectual property.
Read moreMachine learning takes the guesswork out of network capacity planning
Posted on - by Carter Foster
It likely will come as no surprise that the machine learning (ML) market is expected to experience a compound annual growth rate of almost 40 percent through 2027 – when it’s estimated the value of the market will then be $117 billion. What may come as more of a surprise is that the top two ML use cases are risk management, followed by performance analysis and reporting.
Read moreWhy analyzing network flow data helps network performance
Posted on - by Carter Foster
When we talk about Plixer’s Network Performance Monitoring and Diagnostic (NPMD) platform, one of the key features that we highlight is that our solutions use network flow data instead of relying upon the data derived from packet capture. To understand why we’re so passionate about this unique differentiator, it’s useful to understand what network flow data is and how it benefits enterprise NetOps and SecOps teams.
Read moreNetwork intelligence with machine learning
Posted on - by Carter Foster
Whether you’re monitoring an enterprise network for performance or security, you need a tool to help collect and process data. Data is good to have, but it’s really just documentation unless you can put it to use. Almost every organization wonders how they can use data to improve network performance or security. Machine learning helps provide an answer to that question.
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