Tag: Behavioral Analytics

Cloud gaming service Steam pulled a game from its library on July 30 after users reported that it was actually a cryptojacking scam.

Instead of seeking financial gains with ransom demands, threat actors are now aiming to steal central processing unit (CPU) and graphics processing unit (GPU) resources to facilitate cryptojacking.

When users are granted inappropriate access to privileged accounts, they open the entire IT environment to vulnerabilities — and make it easier for malicious actors to infiltrate corporate networks.

Business leaders often rush to migrate corporate assets to cloud environments to boost productivity and lower costs, but adopting cloud services without proper oversight can put data at risk.

To defend their confidential data from increasingly sophisticated cybercriminals, security teams must leverage machine learning to perform analytical tasks that are too tedious for humans to complete.

IT decision-makers need to evolve beyond two-factor authentication and design new ways to make the user verification process intelligent and risk-aware.

There is no silver bullet to thwart the KRACK vulnerability, but a security intelligence platform can help analysts become security superheroes.

New account fraud is rising in popularity among cybercriminals due to the frequency with which users are opening new online banking accounts.

User entity behavioral analysis (UEBA) can provide analysts with actionable insights and early warnings of threats, much like a canary in a coal mine.

Machine learning is an invaluable analytical tool, but problems can arise from its inability to reason beyond the scope of its classification algorithms.