all InfoSec news
Distributional Black-Box Model Inversion Attack with Multi-Agent Reinforcement Learning
April 23, 2024, 4:11 a.m. | Huan Bao, Kaimin Wei, Yongdong Wu, Jin Qian, Robert H. Deng
cs.CR updates on arXiv.org arxiv.org
Abstract: A Model Inversion (MI) attack based on Generative Adversarial Networks (GAN) aims to recover the private training data from complex deep learning models by searching codes in the latent space. However, they merely search a deterministic latent space such that the found latent code is usually suboptimal. In addition, the existing distributional MI schemes assume that an attacker can access the structures and parameters of the target model, which is not always viable in practice. …
adversarial agent arxiv attack box code cs.cr cs.lg data deep learning found gan generative generative adversarial networks networks private recover search space training training data
More from arxiv.org / cs.CR updates on arXiv.org
Jobs in InfoSec / Cybersecurity
Information Security Engineers
@ D. E. Shaw Research | New York City
Technology Security Analyst
@ Halton Region | Oakville, Ontario, Canada
Senior Cyber Security Analyst
@ Valley Water | San Jose, CA
Sr. Staff Firmware Engineer – Networking & Firewall
@ Axiado | Bengaluru, India
Compliance Architect / Product Security Sr. Engineer/Expert (f/m/d)
@ SAP | Walldorf, DE, 69190
SAP Security Administrator
@ FARO Technologies | EMEA-Portugal