SecurityWeek

AI Fuels ‘Industrial’ Cybercrime as Time-to-Exploit Shrinks to Hours

Industrialized cybercrime delivers attacks with greater scale, speed and success. Defenders must match this with use of AI ...
TMCnet

Bramridge Trust Unveiled: Should You Join Bramridge Trust? Features, Performance, Fees & Real User Insights!

Introduction – What Is Bramridge Trust? Bramridge Trust is presented as a modern digital trading and investment ...
IEEE

Evaluating Adversarial Resilience of Deep Reinforcement Learning Algorithms for Network Intrusion Detection

Abstract: Recent advancements in the field of cybersecurity has allowed for greater defensive technologies. The application of machine learning and artificial intelligence in cybersecurity has allowed ...
Scientific Research Publishing

Attack Detection and Alarming System on IOT Facilities Using Random Forest Enabled-Correlation Based Clustering (RF-CBC) Technique ()

1 Department of Mathematical and Computer Sciences, Faculty of Science, University of Medical Sciences, Ondo, Nigeria. 2 Department of Computer Science, University of New Haven, West Haven, USA. 3 ...
IEEE

Unsupervised Real-Time In-Kernel Intrusion Detection System Using Autoencoders and eBPF

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 ...
GitHub

Network Intrusion Detection

Cyberattacks are escalating at a staggering rate globally. Intrusion prevention systems continuously monitor network traffic, looking for possible malicious incidents, containing the threat and ...