Detecting Anomalous Behavior to Secure the EnterpriseCA's Sumeet Mathur on Discovering Vulnerabilities Using Data Science
Applying data science to detect anomalous behavior playing a bigger role in securing enterprises, says Sumeet Mathur, vice president at CA Technologies.
See Also: Beginners Guide to Observability
As the threat surface extends to new applications, APIs and privileged users, security practitioners are on the lookout for new ways to discover these vulnerabilities in real time, he says.
"Security practitioners have the challenge of detecting these behavioral patterns and stepping up security, given the whole slew of application and user identities coming into play in this application economy," he says. "Hence there is a need to deploy appropriate models which enhance organizational security."
In a video interview at Information Security Media Group's recently Fraud & Breach Prevention Summit in Bengaluru, Mathur discusses:
- How data science is being used to discover vulnerabilities in real time;
- Putting the principles of data science in the business context to secure critical data;
- Analyzing anomalous data and setting up a policy to segregate data.
Mathur is vice president, software engineering at CA Technologies, where he leads product development for the cybersecurity suite. He has 22 years of experience in building teams and software at scale in the cloud, big data and cybersecurity domains in the U.S. and India. Previously, he has held leadership roles at Cisco Systems and Nortel. Mathur also holds multiple patents.