all InfoSec news
SATBA: An Invisible Backdoor Attack Based On Spatial Attention
March 6, 2024, 5:11 a.m. | Huasong Zhou, Xiaowei Xu, Xiaodong Wang, Leon Bevan Bullock
cs.CR updates on arXiv.org arxiv.org
Abstract: Backdoor attack has emerged as a novel and concerning threat to AI security. These attacks involve the training of Deep Neural Network (DNN) on datasets that contain hidden trigger patterns. Although the poisoned model behaves normally on benign samples, it exhibits abnormal behavior on samples containing the trigger pattern. However, most existing backdoor attacks suffer from two significant drawbacks: their trigger patterns are visible and easy to detect by backdoor defense or even human inspection, …
abnormal ai security arxiv attack attacks attention backdoor backdoor attack cs.cr cs.cv datasets hidden network neural network novel patterns security threat training trigger
More from arxiv.org / cs.CR updates on arXiv.org
Jobs in InfoSec / Cybersecurity
CyberSOC Technical Lead
@ Integrity360 | Sandyford, Dublin, Ireland
Cyber Security Strategy Consultant
@ Capco | New York City
Cyber Security Senior Consultant
@ Capco | Chicago, IL
Sr. Product Manager
@ MixMode | Remote, US
Corporate Intern - Information Security (Year Round)
@ Associated Bank | US WI Remote
Senior Offensive Security Engineer
@ CoStar Group | US-DC Washington, DC