arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2303.02503cs.CRcs.LG
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使用Wi-Fi无线电波传输和机器学习的零努力双因素认证

Zero-Effort Two-Factor Authentication Using Wi-Fi Radio Wave Transmission and Machine Learning

North Carolina A&T State University(北卡罗来纳农工州立大学)

Ali Abdullah S. AlQahtani, Thamraa Alshayeb

摘要:

在线存储的敏感信息的激增凸显了对安全高效的用户身份验证方法的迫切需求。为了解决这个问题,本文提出了一种新的零努力双因素身份验证(2FA)的方法,结合用户环境的独特特征和机器学习(ML),以确认他们的身份。我们提出的方法利用Wi-Fi无线电波传输和ML算法来分析信标帧特征和来自Wi-Fi接入点的接收信号强度指示符(RSSI)值,以确定用户的位置。目的是提供一种安全有效的认证方法,而无需额外的硬件或软件。使用树莓派设备开发了原型,并进行了实验,以证明所提出的方法的有效性和实用性。结果表明,该系统可以显着提高敏感信息在金融,医疗保健,零售等行业的安全性。这项研究揭示了Wi-Fi无线电波和RSSI值作为用户身份验证手段的潜力,以及ML识别无线信号模式以实现安全目的的能力。所提出的系统在彻底改变2FA和用户认证领域方面具有很大的潜力,为安全和无缝访问敏感信息提供了一个新时代。

英文摘要:

The proliferation of sensitive information being stored online highlights the pressing need for secure and efficient user authentication methods. To address this issue, this paper presents a novel zero-effort two-factor authentication (2FA) approach that combines the unique characteristics of a users environment and Machine Learning (ML) to confirm their identity. Our proposed approach utilizes Wi-Fi radio wave transmission and ML algorithms to analyze beacon frame characteristics and Received Signal Strength Indicator (RSSI) values from Wi-Fi access points to determine the users location. The aim is to provide a secure and efficient method of authentication without the need for additional hardware or software. A prototype was developed using Raspberry Pi devices and experiments were conducted to demonstrate the effectiveness and practicality of the proposed approach. Results showed that the proposed system can significantly enhance the security of sensitive information in various industries such as finance, healthcare, and retail. This study sheds light on the potential of Wi-Fi radio waves and RSSI values as a means of user authentication and the power of ML to identify patterns in wireless signals for security purposes. The proposed system holds great promise in revolutionizing the field of 2FA and user authentication, offering a new era of secure and seamless access to sensitive information.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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