Zero-Effort Two-Factor Authentication Using Wi-Fi Radio Wave Transmission and Machine Learning
This addresses the need for secure and efficient authentication without extra hardware or software, though it appears incremental as it builds on existing Wi-Fi and ML techniques for a specific application.
The paper tackled the problem of secure user authentication by proposing a zero-effort two-factor authentication method using Wi-Fi radio wave transmission and machine learning to analyze beacon frames and RSSI values for location-based identity confirmation, with a prototype demonstrating effectiveness in enhancing security for industries like finance and healthcare.
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.