Artificial intelligence is reshaping cybersecurity, but much of that progress has focused on cloud and enterprise ...

Violations of security policies within a computer or network are symbolic of the need for robust intrusion detection. From attackers accessing systems from the internet or authorized users conducting ...

Intrusion detection systems (IDS) and anomaly detection techniques are critical components of modern cybersecurity, enabling the identification of malicious activities and system irregularities in ...

In the insideAI News Research Highlights column we take a look at new and upcoming results from the research community for data science, machine learning, AI and deep learning. Our readers need to get ...

Are you aware that your API gateway, a vital component of modern software architecture, is also one of the most vulnerable points in a network? Shockingly, a 2022 survey by Statista revealed that most ...

Radiflow360 unified, AI-enhanced, OT cybersecurity platform provides visibility, risk management and incident response for mid-sized industrial enterprises. It’s supported by an AI analyst assistant ...

Anomaly detection in the context of data science is detecting a data sample that is out of the ordinary and does not fit into the general data pattern (or an outlier). This deviation can result from a ...

Phil Goldstein is a former web editor of the CDW family of tech magazines and a veteran technology journalist. He lives in Washington, D.C., with his wife and their animals: a dog named Brenna, and ...

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms ...

Enterprise security faces a watershed as AI tools mature from passive analytics to autonomous operatives in both offense and defense. To date, traditional ...