Understanding how threat hunting differs from reactive security provides a deeper understanding of the role, while hinting at how it will evolve in the future.

Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current ...

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

Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...

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 ...

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 ...

Abstract: Traditional intrusion detection systems (IDSs), leveraging machine learning (ML) algorithms, have improved the detection accuracy of unknown attacks by continuously updating ML models but ...

Abstract: Network Intrusion Detection Systems (NIDS) are widely used to secure modern networks, but deploying accurate and scalable Machine Learning (ML)-based detection in high-speed environments ...

1 Department of Computer Science and Engineering, Oakland University, Rochester, MI, USA. 2 Department of Computer Science, Kettering University, Flint, MI, USA. Intelligent vehicles require strong ...