Data science is playing a fundamental role in a more dynamic approach to cybersecurity, says Jim Routh, CISO of Aetna, who stresses the importance of applying machine learning to front-line data security controls. Routh will be a featured speaker at the ISMG Security Summit in New York Aug. 14-15.
To have any hope of keeping up "with the exponential rise in variants in malware," organizations must reduce their attack surface, in part by using technology designed to learn what attacks look like and respond as quickly as possible, says Cylance's Anton Grashion.
Security experts warn that hackers could one day make use of machine learning and AI to make their attacks more effective. Thankfully, says Cybereason's Ross Rustici, that doesn't appear to have happened yet, although network-penetration attacks are getting more automated than ever.
Incident response challenge: How to deliver actionable information to security analysts to enable them to better triage? "The quicker you can detect and respond to an incident, the more you're likely to be able to contain and minimize the risk associate with it," says IBM's Mike Spradbery.
One of the key lessons offered at ISMG's Fraud & Breach Prevention Summit, held June 12-13 in Bengaluru, was the need for security practitioners to have a better perception of threats and risks so they can build successful detection and defense mechanisms.
Leading the latest edition of the ISMG Security Report: Our exclusive report on an Australian criminal investigation into a company that apparently swiped cryptocurrency using a software backdoor. Also, cutting through the hype on artificial intelligence and machine learning.
Companies offering cybersecurity products are using the terms "artificial intelligence" and "machine learning" in many different ways. But the real meanings of the terms are far more nuanced than marketing hyperbole would lead us to believe, says Grant Wernick of Insight Engines.