SANS Institute Reveals That Automated Threat Detection Helps Fulfill Protection Goals of Critical Security Controls — SANS Report States Data Science and Machine Learning Complement and Improve Traditional Security Methods to Meet Security Goals Defined within the Critical Security Controls

SAN JOSE, Calif., Dec. 8, 2015 — Vectra® Networks, the leader in real-time detection of in-progress cyber-attacks, today with the SANS Institute, announced that recent findings by SANS reveal that automated network threat detection using data science, machine learning and behavioral analysis can complement or improve traditional security methods to fulfill goals defined within the Critical Security Controls (CSCs).

“Automated threat detection is making inroads to identify new patterns, detect events that may not match a specific signature, and determine behavioral abnormalities,” wrote Barbara Filkins, senior SANS analyst, in the white paper, “The Expanding Role of Data Analytics in Threat Detection.”

The CSCs were developed through federal and community efforts, coordinated by the SANS Institute and are maintained by the Center for Internet Security (CIS). Designed to mitigate modern attack profiles, they provide recommended actions for cyber defense to stop today’s most pervasive and dangerous attacks. A principle benefit of the CSCs is their prioritization and focus on a small number of actions that offer high payoff results.

“The Critical Security Controls enable organizations to develop a best-in-class security strategy and architecture,” said Sean O’Connor, assistant chief information officer at Worcester Polytechnic Institute. “It is good to see innovative solution providers like Vectra collaborate with SANS to enable security architects to integrate their technology.”

“The Critical Security Controls enable organizations to ensure they implement essential hygiene to manage risks,” said Jane Lute, CEO of the Center for Internet Security. “What I like about Vectra is that it has the ability to sit within the network and look for anomalous behavior — not just dependent on what it’s seen before but looking at how the network is operating, recognize it in real time, and allow mitigation to proceed in real time.”

The SANS white paper, titled “The Expanding Role of Data Analytics in Threat Detection,” is available for download at http://info.vectranetworks.com/data-analytics-in-threat-detection.

The Vectra automated threat management software delivers real-time detection and analysis of active network breaches. Vectra uses a patent-pending combination of data science, machine learning and behavioral analysis to detect malicious behavior inside networks. Its technology picks up where perimeter security leaves off by providing deep, continuous analysis of both internal and Internet-bound network traffic to automatically detect all phases of a breach as attackers attempt to spy, spread, and steal within a network.

Via: enterprise-security-today