Microsoft

Undermining the trust boundary: Investigating a stealthy intrusion through third-party compromise

Microsoft Incident Response investigated an attack operated through legitimate and trusted administrative mechanisms to blend ...
IEEE

An Explainable Hybrid Deep Learning Framework for Network Intrusion Detection Using Feature-Guided CNN Models

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 ...
IEEE

Intrusion Detection and Mitigation System for Smart Inverters Based on Machine Learning and Environmental Sensors

Abstract: The rapid expansion of renewable energy deployment has accelerated the adoption of smart inverters in solar farms. However, their reliance on communication networks introduces cybersecurity ...
Devdiscourse

IoT threat detection moves to transparent, decentralized AI systems

A new study published in Frontiers in Computer Science introduces a decentralized cybersecurity model that combines federated ...
Scientific Research Publishing

Sommer, R. and Paxson, V. (2010) Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. 2010 IEEE Symposium on Security and Privacy, Oakland, 16 ...

ABSTRACT: Cybersecurity has emerged as a global concern, amplified by the rapid expansion of IoT devices and the growing digitization of systems. In this context, traditional security solutions such ...
militarnyi

Ukraine Develops FENEK Acoustic Drone Detection System

Ukraine has unveiled a new acoustic drone detection system ‘FENEK’ designed to support mobile AA fire teams and enhance the protection of critical infrastructure. In an interview with Militarnyi, a ...