This IDS focuses on detecting intrusion attempts by matching patterns in network data (such as suspicious strings in payloads or requests). It integrates the Knuth-Morris-Pratt (KMP) string-search ...

Recently, there have been significant research for developing network intrusion detection systems (NIDSs) to detect malicious activities by using deep learning. However, the effectiveness of deep ...

IDPS-ESCAPE (Intrusion Detection and Prevention Systems for Evading Supply Chain Attacks and Post-compromise Effects), part of the CyFORT project: open-source SOAR system powered by a dedicated ...

Omnilert’s latest report reveals a significant financial burden from gun violence and emphasizes the critical need for enhanced safety measures in public spaces.

Abstract: In the era of zero trust security models and next-generation networks (NGN), the primary challenge is that network nodes may be untrusted, even if they have been verified, necessitating ...

Data-centric security is an approach to information security that emphasizes protecting the data itself rather than focusing ...

Remember the good old days of IT? Back when firewalls were like bouncers at a nightclub, and security was a sleepy corner in ...

In today’s digital landscape, managing your IP address is crucial for maintaining a stable and secure online presence.

Neural networks have revolutionized the fields of artificial intelligence (AI) and machine learning by providing a flexible, ...