Sungbin Park , Changbae Seo , Xueqiang Wang , Yeonjoon Lee , Seung-Hyun Seo
{"title":"店内专享:固定式商务设备的声学定位验证","authors":"Sungbin Park , Changbae Seo , Xueqiang Wang , Yeonjoon Lee , Seung-Hyun Seo","doi":"10.1016/j.jnca.2024.104028","DOIUrl":null,"url":null,"abstract":"<div><p>Over the past decade, the adoption of Internet of Things (IoT) devices has greatly revolutionized the retail and commerce industries. However, these devices are vulnerable to attacks, such as theft, which raises significant security and privacy concerns for business assets. Securing such business-owned devices is challenging, particularly due to the business contexts that require not only authenticating the devices but also verifying the environment in which the devices are located. In this study, we present a zero-effort authentication approach based on acoustic fingerprints, namely <em>AcousticAuth</em>. <em>AcousticAuth</em> enables a “verifier” device to authenticate and verify the work environment of multiple “prover” devices (e.g., kiosks) by extracting their acoustic fingerprints and direction information. Additionally, we adopt a novel method based on beamforming to expand the fingerprint space of the provers. We implemented a prototype of <em>AcousticAuth</em> using real-world IoT devices, and the evaluation of the prototype indicates that <em>AcousticAuth</em> is highly effective and achieves high sensitivity when authenticating different devices across environments. Our results demonstrate that <em>AcousticAuth</em> can accurately distinguish between different devices and the same model devices with the error rate of 0.03%, significantly enhancing the security of IoT devices in retail settings. <em>AcousticAuth</em> also distinguishes between the different environments with an error rate of 0.00%. Lastly, the system shows robustness against various acoustic interference scenarios, making it a practical solution for dynamic business environments. We not only introduce a novel security mechanism that pushes the limit of fingerprint-based authentication by expanding the fingerprint pool but also provide comprehensive insights into its implementation and performance, paving the way for more secure IoT deployments in the commercial sector.</p></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"232 ","pages":"Article 104028"},"PeriodicalIF":7.7000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exclusively in-store: Acoustic location authentication for stationary business devices\",\"authors\":\"Sungbin Park , Changbae Seo , Xueqiang Wang , Yeonjoon Lee , Seung-Hyun Seo\",\"doi\":\"10.1016/j.jnca.2024.104028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Over the past decade, the adoption of Internet of Things (IoT) devices has greatly revolutionized the retail and commerce industries. However, these devices are vulnerable to attacks, such as theft, which raises significant security and privacy concerns for business assets. Securing such business-owned devices is challenging, particularly due to the business contexts that require not only authenticating the devices but also verifying the environment in which the devices are located. In this study, we present a zero-effort authentication approach based on acoustic fingerprints, namely <em>AcousticAuth</em>. <em>AcousticAuth</em> enables a “verifier” device to authenticate and verify the work environment of multiple “prover” devices (e.g., kiosks) by extracting their acoustic fingerprints and direction information. Additionally, we adopt a novel method based on beamforming to expand the fingerprint space of the provers. We implemented a prototype of <em>AcousticAuth</em> using real-world IoT devices, and the evaluation of the prototype indicates that <em>AcousticAuth</em> is highly effective and achieves high sensitivity when authenticating different devices across environments. Our results demonstrate that <em>AcousticAuth</em> can accurately distinguish between different devices and the same model devices with the error rate of 0.03%, significantly enhancing the security of IoT devices in retail settings. <em>AcousticAuth</em> also distinguishes between the different environments with an error rate of 0.00%. Lastly, the system shows robustness against various acoustic interference scenarios, making it a practical solution for dynamic business environments. We not only introduce a novel security mechanism that pushes the limit of fingerprint-based authentication by expanding the fingerprint pool but also provide comprehensive insights into its implementation and performance, paving the way for more secure IoT deployments in the commercial sector.</p></div>\",\"PeriodicalId\":54784,\"journal\":{\"name\":\"Journal of Network and Computer Applications\",\"volume\":\"232 \",\"pages\":\"Article 104028\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Network and Computer Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1084804524002054\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Network and Computer Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1084804524002054","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Exclusively in-store: Acoustic location authentication for stationary business devices
Over the past decade, the adoption of Internet of Things (IoT) devices has greatly revolutionized the retail and commerce industries. However, these devices are vulnerable to attacks, such as theft, which raises significant security and privacy concerns for business assets. Securing such business-owned devices is challenging, particularly due to the business contexts that require not only authenticating the devices but also verifying the environment in which the devices are located. In this study, we present a zero-effort authentication approach based on acoustic fingerprints, namely AcousticAuth. AcousticAuth enables a “verifier” device to authenticate and verify the work environment of multiple “prover” devices (e.g., kiosks) by extracting their acoustic fingerprints and direction information. Additionally, we adopt a novel method based on beamforming to expand the fingerprint space of the provers. We implemented a prototype of AcousticAuth using real-world IoT devices, and the evaluation of the prototype indicates that AcousticAuth is highly effective and achieves high sensitivity when authenticating different devices across environments. Our results demonstrate that AcousticAuth can accurately distinguish between different devices and the same model devices with the error rate of 0.03%, significantly enhancing the security of IoT devices in retail settings. AcousticAuth also distinguishes between the different environments with an error rate of 0.00%. Lastly, the system shows robustness against various acoustic interference scenarios, making it a practical solution for dynamic business environments. We not only introduce a novel security mechanism that pushes the limit of fingerprint-based authentication by expanding the fingerprint pool but also provide comprehensive insights into its implementation and performance, paving the way for more secure IoT deployments in the commercial sector.
期刊介绍:
The Journal of Network and Computer Applications welcomes research contributions, surveys, and notes in all areas relating to computer networks and applications thereof. Sample topics include new design techniques, interesting or novel applications, components or standards; computer networks with tools such as WWW; emerging standards for internet protocols; Wireless networks; Mobile Computing; emerging computing models such as cloud computing, grid computing; applications of networked systems for remote collaboration and telemedicine, etc. The journal is abstracted and indexed in Scopus, Engineering Index, Web of Science, Science Citation Index Expanded and INSPEC.