Tag: User Behavior Analytics (UBA)

Industrial IoT technologies promise to revolutionize the automotive industry, but they also introduce new risks. What are the biggest threats auto companies face, and how can they mitigate them?

Insider threats are not only the most common cause of cybersecurity risk, but also the costliest and hardest to detect.

As cloud adoption increases, the IT skills gap widens and the threat landscape becomes more sophisticated, innovations in SIEM technology will revolutionize the way SOCs perform security analytics.

Without a data breach response plan, companies will find it difficult to disclose security incidents within 72 hours as required by the General Data Protection Regulation (GDPR).

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.

According to a recent insider threat report, 60 percent of risk assessments identified users who tried to bypass their employer's security measures using private or anonymous browsing.

Organizations need a privileged account management (PAM) solution that integrates seamlessly with the existing security environment — and helps security teams enforce least privilege policies.

Security analysts can maximize the effectiveness of their incident response capabilities by integrating disparate tools such as database firewalls and UBA with a strong SIEM solution.

A UBA solution powered by machine learning enables security teams to model normal behavior and track subtle changes in user activity to identify malicious insiders.

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.