Using Machine Learning to Connect the Dots in Container Security

There is a weird, virtually universal truth about the relationship between technology and security. There is often an inverse relationship in which the more powerful, useful or convenient a technology is for the end user, the larger the risk it poses from a security perspective. The things that make it a great technology also expose it to potential exploit and compromise. This is definitely true when it comes to containers. Containers provide an alternative to virtual machines and allow organizations to streamline development and deployment of applications. Containers let developers virtualize a single application and break it into smaller, more manageable components. Containers enable applications that are more agile and more scalable and can be spread potentially across servers and throughout the infrastructure. Wei Lien Dang, VP of Product for StackRox, explains, The highly distributed, rapidly changing attack surfaces that containers present pose unique challenges for security operators. Effective threat detection requires identifying indicators of attack and compromise that may be spread out across the environment, and intelligently relating them to each other to discover potential threat vectors.

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