Security and Privacy Problems in Voice Assistant Applications: A Survey

Autor:	Li, Jingjin, chen, Chao, Pan, Lei, Azghadi, Mostafa Rahimi, Ghodosi, Hossein, Zhang, Jun
Rok vydání:	2023
Předmět:	Computer Science - Cryptography and Security Computer Science - Machine Learning Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	Voice assistant applications have become omniscient nowadays. Two models that provide the two most important functions for real-life applications (i.e., Google Home, Amazon Alexa, Siri, etc.) are Automatic Speech Recognition (ASR) models and Speaker Identification (SI) models. According to recent studies, security and privacy threats have also emerged with the rapid development of the Internet of Things (IoT). The security issues researched include attack techniques toward machine learning models and other hardware components widely used in voice assistant applications. The privacy issues include technical-wise information stealing and policy-wise privacy breaches. The voice assistant application takes a steadily growing market share every year, but their privacy and security issues never stopped causing huge economic losses and endangering users' personal sensitive information. Thus, it is important to have a comprehensive survey to outline the categorization of the current research regarding the security and privacy problems of voice assistant applications. This paper concludes and assesses five kinds of security attacks and three types of privacy threats in the papers published in the top-tier conferences of cyber security and voice domain. Comment: 5 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2304.09486 Zobrazit plný text záznamu View this record from Arxiv