In today’s threat landscape, malware infections rarely announce themselves through obvious warning signs. Modern attackers increasingly rely on stealth, persistence, and legitimate-looking network ...

In cybersecurity, anomaly detection in tabular data is essential for ensuring information security. While traditional machine learning and deep learning methods have shown some success, they continue ...

The emerging density in today’s urban environments requires a strong multi-camera architecture for real-time abnormality detection and behavior analysis. Most of the existing methods tend to fail in ...

Fidelis Network is an NDR security solution which offers full and deep internal visibility across all ports and protocols, with network traffic analysis and network behavior anomaly detection, which ...

Companies need greater network segmentation, sandboxes, firewalls, and anomaly detection to fight attackers, according to Cisco's 2024 Cybersecurity Readiness Index. Security readiness among ...

As I mentioned in a previous column, there’s a new set of draft documents from the Computer Security Resource Center of the U.S. National Institute of Standards and Technology (NIST). SP 800-94, ...

Network infrastructures that can be relied upon 24/7 are the backbone of any modern digital enterprise, business continuity, user experience or cybersecurity strategy. However, network management has ...

While intrusion-detection technologies are clearly not a hot new thing anymore, they are still the subject of active industry debate. Since the infamous “IDS Is Dead” piece was published by Gartner ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

Although the number and intensity of distributed denial-of-service attacks are on the rise, users are hard-pressed to find tangible new services to help thwart or defend against such assaults. However ...