Now, the biggest change involves incorporating AI tools to speed analysis and catch anomalies or outliers that humans could miss. “There have been very significant improvements around deep ...

Abstract: Anomaly detection (AD) is typically regarded as an unsupervised learning task, where the training data either do not contain any anomalous samples or contain only a few unlabeled anomalous ...

Running a SOC often feels like drowning in alerts. Every morning, dashboards light up with thousands of signals; some urgent, many irrelevant. The job is to find the real threats fast enough to keep ...

Microsoft on Tuesday unveiled the expansion of its Sentinel Security Incidents and Event Management solution (SIEM) as a unified agentic platform with the general availability of the Sentinel data ...

Abstract: The rapid proliferation of IoT technologies intensifies network anomaly detection challenges because of high-dimensional and redundant data. To address this issue, we propose causal gray ...