Machine learning (ML) is a subset of Artificial Intelligence (AI), which enables machines and software to automatically learn from historical data to generate accurate output without being programmed to do so. Many leading organizations today have incorporated machine learning into their daily processes for business intelligence. But the ability of machine learning can be altered by threat actors to be malicious, causing systems to malfunction, or to execute an attack.

To protect the business, security teams need to be able to detect and respond to threats fast. The problem is the average organization generates massive amounts of data every day. Information floods into the Security Operations Center (SOC) from network tools, security tools, cloud services, threat intelligence feeds, and other sources. Reviewing and analyzing all this data in a reasonable amount of time has become a task that is well beyond the scope of human efforts.

The power of the CrowdStrike Falcon® platform lies in its ability to detect and protect customers from new and unknown threats by leveraging the power of the cloud and expertly built machine learning (ML) models. In real-world conditions and in independent third-party evaluations, Falcon’s on-sensor and cloud ML capabilities consistently achieve excellent results across Windows, Linux and macOS platforms.

Trustwave’s MailMarshal received a major update this month with the addition of PageML to the Blended Threat Module. The BTM enables the email security solution to conduct in-depth, real-time scans when a URL in an email is clicked to determine if the URL is malicious. PageML boosts the BTM’s ability to detect malicious URLs by one-third by applying machine learning techniques to page content in real time. The new scanning feature is named PageML, short for Page Machine Learning.

Deep learning is a core part of CrowdStrike’s arsenal of machine learning (ML) techniques, and we are constantly innovating in this area to boost the performance of our ML models. However, ML can consume large amounts of computing resources. To minimize the computing load and its associated costs, we strive to optimize performance and resource utilization for our models as well as address any safety issues related to the use of third-party tools.

With news headlines like “A massive ransomware attack hit hundreds of businesses” becoming common, concern about malware has never been higher. High-profile examples of malware like DarkSide, REvil have been profiled so many times that not only cybersecurity professionals are on edge — every organization that has on-premises or in-the-cloud workloads is concerned.