{"title":"声学窃听攻击调查:原理、方法和进展","authors":"","doi":"10.1016/j.hcc.2024.100241","DOIUrl":null,"url":null,"abstract":"<div><div>In today’s information age, eavesdropping has been one of the most serious privacy threats in information security, such as exodus spyware (Rudie et al., 2021) and pegasus spyware (Anatolyevich, 2020). And the main one of them is acoustic eavesdropping. Acoustic eavesdropping (George and Sagayarajan, 2023) is a technology that uses microphones, sensors, or other devices to collect and process sound signals and convert them into readable information. Although much research has been done in this area, there is still a lack of comprehensive investigation into the timeliness of this technology, given the continuous advancement of technology and the rapid development of eavesdropping methods. In this article, we have given a selective overview of acoustic eavesdropping, focusing on the methods of acoustic eavesdropping. More specifically, we divide acoustic eavesdropping into three categories: motion sensor-based acoustic eavesdropping, optical sensor-based acoustic eavesdropping, and RF-based acoustic eavesdropping. Within these three representative frameworks, we review the results of acoustic eavesdropping according to the type of equipment they use and the physical principles of each. Secondly, we also introduce several important but challenging applications of these acoustic eavesdropping methods. In addition, we compared the systems that meet the requirements of acoustic eavesdropping in real-world scenarios from multiple perspectives, including whether they are non-intrusive, whether they can achieve unconstrained word eavesdropping, and whether they use machine learning, etc. The general template of our article is as follows: firstly, we systematically review and classify the existing eavesdropping technologies, elaborate on their working mechanisms, and give corresponding formulas. Then, these eavesdropping methods were compared and analyzed, and each method’s effectiveness and technical difficulty were evaluated from multiple dimensions. In addition to an assessment of the current state of the field, we discuss the current shortcomings and challenges and give a fruitful direction for the future of acoustic eavesdropping research. We hope to continue to inspire researchers in this direction.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A survey of acoustic eavesdropping attacks: Principle, methods, and progress\",\"authors\":\"\",\"doi\":\"10.1016/j.hcc.2024.100241\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In today’s information age, eavesdropping has been one of the most serious privacy threats in information security, such as exodus spyware (Rudie et al., 2021) and pegasus spyware (Anatolyevich, 2020). And the main one of them is acoustic eavesdropping. Acoustic eavesdropping (George and Sagayarajan, 2023) is a technology that uses microphones, sensors, or other devices to collect and process sound signals and convert them into readable information. Although much research has been done in this area, there is still a lack of comprehensive investigation into the timeliness of this technology, given the continuous advancement of technology and the rapid development of eavesdropping methods. In this article, we have given a selective overview of acoustic eavesdropping, focusing on the methods of acoustic eavesdropping. More specifically, we divide acoustic eavesdropping into three categories: motion sensor-based acoustic eavesdropping, optical sensor-based acoustic eavesdropping, and RF-based acoustic eavesdropping. Within these three representative frameworks, we review the results of acoustic eavesdropping according to the type of equipment they use and the physical principles of each. Secondly, we also introduce several important but challenging applications of these acoustic eavesdropping methods. In addition, we compared the systems that meet the requirements of acoustic eavesdropping in real-world scenarios from multiple perspectives, including whether they are non-intrusive, whether they can achieve unconstrained word eavesdropping, and whether they use machine learning, etc. The general template of our article is as follows: firstly, we systematically review and classify the existing eavesdropping technologies, elaborate on their working mechanisms, and give corresponding formulas. Then, these eavesdropping methods were compared and analyzed, and each method’s effectiveness and technical difficulty were evaluated from multiple dimensions. In addition to an assessment of the current state of the field, we discuss the current shortcomings and challenges and give a fruitful direction for the future of acoustic eavesdropping research. We hope to continue to inspire researchers in this direction.</div></div>\",\"PeriodicalId\":100605,\"journal\":{\"name\":\"High-Confidence Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"High-Confidence Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667295224000448\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"High-Confidence Computing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667295224000448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A survey of acoustic eavesdropping attacks: Principle, methods, and progress
In today’s information age, eavesdropping has been one of the most serious privacy threats in information security, such as exodus spyware (Rudie et al., 2021) and pegasus spyware (Anatolyevich, 2020). And the main one of them is acoustic eavesdropping. Acoustic eavesdropping (George and Sagayarajan, 2023) is a technology that uses microphones, sensors, or other devices to collect and process sound signals and convert them into readable information. Although much research has been done in this area, there is still a lack of comprehensive investigation into the timeliness of this technology, given the continuous advancement of technology and the rapid development of eavesdropping methods. In this article, we have given a selective overview of acoustic eavesdropping, focusing on the methods of acoustic eavesdropping. More specifically, we divide acoustic eavesdropping into three categories: motion sensor-based acoustic eavesdropping, optical sensor-based acoustic eavesdropping, and RF-based acoustic eavesdropping. Within these three representative frameworks, we review the results of acoustic eavesdropping according to the type of equipment they use and the physical principles of each. Secondly, we also introduce several important but challenging applications of these acoustic eavesdropping methods. In addition, we compared the systems that meet the requirements of acoustic eavesdropping in real-world scenarios from multiple perspectives, including whether they are non-intrusive, whether they can achieve unconstrained word eavesdropping, and whether they use machine learning, etc. The general template of our article is as follows: firstly, we systematically review and classify the existing eavesdropping technologies, elaborate on their working mechanisms, and give corresponding formulas. Then, these eavesdropping methods were compared and analyzed, and each method’s effectiveness and technical difficulty were evaluated from multiple dimensions. In addition to an assessment of the current state of the field, we discuss the current shortcomings and challenges and give a fruitful direction for the future of acoustic eavesdropping research. We hope to continue to inspire researchers in this direction.