Statistically, you're probably not. Even those with cyber insurance often have policies that leave them exposed to certain types of breaches, regulatory fines and real-world financial losses.
Armed with security analytics tools, organizations can benefit from big data capabilities to analyze data and enhance detection with proactive alerts about potential malicious activity.
Thanks to a wealth of new capabilities, security operations teams that leverage a cutting-edge SIEM platform are better armed to defend their organizations from advanced and insider threats.
Collaborative industry partnerships, a hardened attack surface and a well-practiced incident response plan are all critical in the fight against emerging cybersecurity threats.
User behavior analytics (UBA) can help security teams uncover ignorant, negligent and malicious activity with advanced machine learning algorithms — but Rome wasn't built in a day.
To kick off October, we take a look back at what happened in cybersecurity in 2018 and a sneak peek at this year's National Cyber Security Awareness Month.
On Sept. 6, director Kelly Richmond Pope will discuss a case in which a small town official stole $53 million in public funds over two decades to illustrate the importance of managing insider threats.
Insider threats are not only the most common cause of cybersecurity risk, but also the costliest and hardest to detect.
Malicious actors outside your organization aren't always the only ones at fault for data breaches. Comprehensive employee security training is crucial to minimize the risk of insider threats.
Instead of replacing humans, machine learning will free up overworked IT analysts to focus on other tasks. However, the rising adoption of AI could expose companies to a new breed of insider threats.