Security measures have increased significantly in the last several years, and malicious actors have similarly advanced their techniques to keep pace, particularly with advances in attack methods such as fileless malware. Likewise, the security model of ‘serverless’ computing platforms like AWS Lambda are completely different from traditional computers. These itinerant computing concepts are not effectively secured by the traditional model of checking file hashes against known malware samples.
For a robust, modern defense, an adaptive monitoring solution that leverages machine learning to identify anomalous patterns indicative of an attack in its infancy is necessary to defend enterprise systems from cyberattacks.
Much of the groundwork for this has been laid over the last several years, with endpoint detection services analyzing system events. “Network connection opened, registry key modified, process created… You build this catalog of really security relevant behaviors. The challenge becomes to map known malicious behaviors that essentially do the same…
