A secure fuzzy extractor based biometric key authentication scheme for body sensor network in Internet of Medical Things Abstract   Body sensor network (BSN) is largely utilized in IoMT to attain easier access of patientxe2x80x99s data remotely without much cost by connecting the various biosensors. However, there is a security threat in accessing the BSN because of hacking issues. Hence, In order to secure the most sensitive details of the patient, secured fuzzy extractor combined with fuzzy vault is developed in this approach with an objective of providing more security using biometric key authentication scheme. Initially, preprocessing is done to remove the noise in ECG signal using the adaptive filtering.Secured Fuzzy extractor is designed for extracting the features like QRS,PR and QT interval and the private key generation for authentication process is based on these features only. Because of unique features of each ECG, private key canxe2x80x99t be hacked easily. Along with private key values, a set of random chaff points are generated using polynomial construction principle and are stored with a checksum vector in a separate fuzzy vault set. In the authentication phase, the data in the fuzzy set will be checked with checksum values to detect missing data in the communication. The IP address of the device will be used as the public key for estimating the bit rate of sensors at decoding phase. The security of the system depends mainly on the hash function. In our proposed method, the hash variable value is independent of the hash functions to enhance the network security. This variation in hashing does not affect the latency or delay of our proposed technique. The proposed fuzzy extractor based biometric key authentication scheme achieved enhanced results such as 40% reduced data loss, 20% reduced energy consumption and reduced delay when compared to previous encoding techniques.

Leakageresilient biometricbased remote user authentication with fuzzy extractors Abstract   Fuzzy extractors convert biometrics and other noisy data into a cryptographic key for security applications such as remote user authentication. Leakage attacks, such as side channel attacks, have been extensively modelled and studied in the literature. However, to the best of our knowledge, leakage attacks to biometricbased remote user authentication with fuzzy extractors have never been studied rigorously. In this paper, we propose a generic framework of leakageresilient and privacypreserving biometricbased remote user authentication that allows an authorized user to securely authenticate herself to a remote authentication server using her biometrics. In particular, the authorized user relies only on her secret biometrics to perform a valid authentication xe2x80x94 which is suitable for user authentications in a crossplatform setting.