Tag: Security Analytics

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.

With intelligent code analytics, developers can use machine learning to mark up APIs and bring application security testing to the next level.

IBM Security was recognized as a leader in the first ever Forrester Security Analytics Wave, earning the highest scores in solution strength and vision.

For our RSA wrap-up, we summarized some key points and takeaways about emerging trends such as the IoT, security analytics and the IT skills shortage.

Automation and analytics can help IT professionals speed up and solidify their data protection programs and prepare for regulatory audits.

IBM QRadar Network Insights enables security professionals to analyze historical threat data and identify indicators of malicious activity in real time.

Big data solutions can aggregate, index and analyze many types of data to produce advanced business insights. This makes them juicy targets for fraudsters.