Machine learning systems like A12 are designed to augment human analysis with cognitive intelligence, enabling IT professionals to reduce false positives.
The emergence of cognitive computing is driving the future of security, enabling human analysts to make better decisions when responding to data breaches.
Cybersecurity leaders hope to use cognitive security solutions to improve detection and incident response capabilities and reduce false positives.
Respondents to an IBV survey identified incident response speed as the most pressing security challenge. Cognitive security tools can close the gap.
The NSF is sponsoring an attempt to build a malware chip capable of detecting anomalies in system processes and alerting local security software.
Cognitive security solutions will help IT analysts tackle long-term strategic issues rather than firefighting against the overwhelming volume of threats.
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.