An automated security analytics platform can help understaffed security teams sift through threat data more efficiently and focus on more critical tasks.
In the Industry 4.0 era, mainframe security is supported by four key areas: big data, analytics, human-machine interaction and cognitive computing.
To deliver the level of personalization today's prosumers demand, utilities must support their energy security strategies with predictive analytics.
Given the growing number of connected devices, organizations are beginning to leverage IoT data analytics to drive better decision-making.
User entity behavioral analysis (UEBA) can provide analysts with actionable insights and early warnings of threats, much like a canary in a coal mine.
Intelligent Code Analytics: Increasing Application Security Testing Coverage With Cognitive Computing
With intelligent code analytics, developers can use machine learning to mark up APIs and bring application security testing to the next level.
Automation and analytics can help IT professionals speed up and solidify their data protection programs and prepare for regulatory audits.
Big data solutions can aggregate, index and analyze many types of data to produce advanced business insights. This makes them juicy targets for fraudsters.
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.
The challenge of protecting your brand is growing as ransomware and other targeted attacks become increasingly frequent and complex.