Analysis of Adversarial Attacks against Speaker Recognition System

Abstract

Voice user interface (VUI) is being widely utilized these days. Speaker  recognition system are popular in  applications like smart home and smart devices using like alexa , google  assistant ,google home these are easy to use from remote control  from involving deep neural network . Literature shows that implementation of attacks against these voice control like alexa google assistant are been attacked by virus and how to protect future directions. In numerous security-delicate applications and administrations, a speaker An imperative approach to perceiving a speaker has arisen a recognizable proof framework. The principal constant, unavoidable, and strong ill-disposed attack on a cutting edge profound brain organization deep neural network (DNN) based voice acknowledgment framework is proposed in this examination. The Deep nueral networks based speaker distinguishing proof framework would perceive any selected speaker as any objective (i.e., enemy wanted) speaker name by applying a sound free thinker worldwide bother to their voice input.We further work on our attack's versatility by mimicking sound contortions incited by actual over-the-air transmission and registering room motivation reaction (RIR). With a high assault achievement pace of more than 90%, an examination utilizing a public dataset of 200  English speakers demonstrates the viability and strength of our proposed method. This assault is 100x quicker than other non-widespread assaults.