IT professionals are beginning to adopt cognitive security solutions to help them speed up response times and identify threats more effectively.
IT professionals are turning to machine learning solutions to help them reduce the rate of false positives and monitor huge volumes of data in real time.
According to a recent survey conducted by the IBM Institute of Business Value (IBV), the era of cognitive security may be coming sooner than we think.
IBM demoed the integration of Watson for Cyber Security with QRadar, designed to improve the quality and velocity of security analysis, at World of Watson.
Few truly understand how spam filters work, but nearly every internet user benefits from the security they provide on a daily basis.
Machine learning is an invaluable analytical tool, but problems can arise from its inability to reason beyond the scope of its classification algorithms.
Machine learning relies on data acquisition and classification of examples to help security teams and threat analysts reduce the rate of false positives.
IBM recently acquired IRIS Analytics and its security system, which is designed to combat real-time payment fraud with the help of machine learning.
2015 had a lot of cybersecurity challenges, but many of these incidents have set up 2016 to be a year of opportunities for individuals and enterprises.
Here's a look at Steffen Rendle's theory on factorization machines — including how they could be used to assist data scientists in the future.