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 ...

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 ...

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 ...

Identifying anomalies in the operations of computer systems that control critical safety and security functions calls for extensive expertise, and the actions required need to be tested, analysed 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 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

Rohith Vegesna is a software engineer specializing in secure, cloud-connected fueling systems, with a strong focus on IoT, real-time monitoring, and cybersecurity.