all InfoSec news
DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution
Feb. 16, 2024, 5:10 a.m. | Mat\'ias P. Pizarro B., Dorothea Kolossa, Asja Fischer
cs.CR updates on arXiv.org arxiv.org
Abstract: Adversarial attacks can mislead automatic speech recognition (ASR) systems into predicting an arbitrary target text, thus posing a clear security threat. To prevent such attacks, we propose DistriBlock, an efficient detection strategy applicable to any ASR system that predicts a probability distribution over output tokens in each time step. We measure a set of characteristics of this distribution: the median, maximum, and minimum over the output probabilities, the entropy of the distribution, as well as …
adversarial adversarial attacks arxiv asr attacks audio automatic can clear cs.cr cs.lg cs.sd detection distribution eess.as recognition security security threat speech speech recognition strategy system systems target text threat
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
Senior - Penetration Tester
@ Deloitte | Madrid, España
Associate Cyber Incident Responder
@ Highmark Health | PA, Working at Home - Pennsylvania
Senior Insider Threat Analyst
@ IT Concepts Inc. | Woodlawn, Maryland, United States