all InfoSec news
CorruptEncoder: Data Poisoning based Backdoor Attacks to Contrastive Learning
March 4, 2024, 5:10 a.m. | Jinghuai Zhang, Hongbin Liu, Jinyuan Jia, Neil Zhenqiang Gong
cs.CR updates on arXiv.org arxiv.org
Abstract: Contrastive learning (CL) pre-trains general-purpose encoders using an unlabeled pre-training dataset, which consists of images or image-text pairs. CL is vulnerable to data poisoning based backdoor attacks (DPBAs), in which an attacker injects poisoned inputs into the pre-training dataset so the encoder is backdoored. However, existing DPBAs achieve limited effectiveness. In this work, we take the first step to analyze the limitations of existing backdoor attacks and propose new DPBAs called CorruptEncoder to CL. CorruptEncoder …
arxiv attacker attacks backdoor backdoor attacks cs.cr cs.cv cs.lg data data poisoning dataset general image images inputs poisoning purpose text training trains vulnerable
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