While at times the number of food safety recalls seems to be rising, in most cases, the recalls are smaller in lot size and ...

Monday cybersecurity recap on evolving threats, trusted tool abuse, stealthy in-memory attacks, and shifting access patterns.

Attackers aren't breaking into your house; they’re using your own spare key to hide in plain sight. We need to stop assuming ...

Real-time network traffic analysis Rule-based intrusion detection Alert generation for suspicious activities Logging and reporting of detected intrusions before the installation run "ifconfig" get the ...

Abstract: Intrusion Detection Systems (IDS) are critical for identifying and mitigating potential security threats within network traffic. However, traditional IDS solutions often struggle with ...

ABSTRACT: Local Area Networks (LANs) are critical to organizational infrastructure, yet they remain highly vulnerable to sophisticated cyber threats such as insider misuse, ARP spoofing, privilege ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Abstract: Cybersecurity risks have evolved in the linked digital terrain of today into more complex, frequent, and varied forms. Conventional intrusion detection systems sometimes find it difficult to ...

This project implements an Intrusion Detection System using machine learning algorithms to detect malicious network activities. It analyzes network traffic patterns, packet headers, and flow data to ...

The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based defenses have ...