Traditional authentication technologies usually perform identity authentication based on user information verification (e.g., entering the password) or biometric information (e.g., fingerprints). However, there are security risks when applying only these authentication methods. For example, if the password is compromised, it is unlikely to determine whether the user entering the password is legitimate. In this paper, we subdivide biometric information into physiological and behavioral information, and we propose a novel user authentication system, RF-Ubia, which utilizes the low-cost radio frequency identification (RFID) technology to capture unique biological or behavioral information rooted in the user and can be used in two schemes for user authentication.Consisting of an array of nine passive tags and a commercial RFID reader, RF-Ubia provides double assurance for security of identity authentication by combining user information and biometric characteristics. It first verifies the user’s password, and then identifies the biometric characteristics of the legitimate user. Due to the coupling effect among tags, any change in tag signal caused by the user’s touch will affect other tag signals at the same time. Since each user has different fingertip impedance, their touch will cause unique tag signal changes. Therefore, by combining biometric information, the tag array will uniquely identify users. The evaluation results show that RF-Ubia achieves excellent authentication performance with an average recognition rate of 93.8%.

Due to the ability to simultaneously interrogate multiple tags with a far operating distance, radio frequency identification (RFID) has been widely used in modern farms to improve management efficiency. In smart farm applications, how to quickly locate and search some specified items (e.g., animals) is a critical problem, for which tag searching can be used to solve the problem. While there are some works on tag searching, they are designed for static objects and cannot meet the time efficiency requirements where the searched animals’ movement brings challenges. In this paper, we propose SHIR, an efficient tag-searching protocol based on historical information reasoning, which can be applied in scenarios containing mobile tags that cannot be well handles in existing tag search protocols. By continuously counting the difference between the predicted reply signal and the actual signal received from tags for multiple rounds, SHIR avoids the waste of time slots and achieves high time efficiency. Furthermore, it can infer unverified tag status through historical information to speed up the search process. We further propose the Enhanced SHIR (ESHIR) protocol by filtering out the interference tags in the query area to avoid wasting time verifying interference tags. Compared with previous probabilistic approaches, SHIR gets accurate search results with no false positives. Extensive experimental results show that our best protocol can improve the time efficiency by up to 42% compared with the the-state-of-art solution.