DeBackdoor is a new framework designed to detect stealthy backdoor attacks on deep learning models before deployment. It functions under real-world constraints, requiring limited data and only black-box access. Utilizing a Simulated Annealing optimization algorithm, DeBackdoor effectively identifies various attack types, outperforming existing methods and enhancing security for safety-critical applications.
Surging DDoS attack rates show no sign of slowing down – here’s why
Recent research shows a significant increase in DDoS attacks since the beginning of last year. The number of these attacks has risen dramatically, indicating a
