Edge-centric multimodal authentication system using encrypted biometric templates

Abstract

Data security, complete system control, and missed storage and computing opportunities in personal portable devices are some of the major limitations of the centralized cloud environment. Among these limitations, security is a prime concern due to potential unauthorized access to private data. Biometrics, in particular, is considered sensitive data, and its usage is subject to the privacy protection law. To address this issue, a multimodal authentication system using encrypted biometrics for the edge-centric cloud environment is proposed in this study. Personal portable devices are utilized for encrypting biometrics in the proposed system, which optimizes the use of resources and tackles another limitation of the cloud environment. Biometrics is encrypted using a new method. In the proposed system, the edges transmit the encrypted speech and face for processing in the cloud. The cloud then decrypts the biometrics and performs authentication to confirm the identity of an individual. The model for speech authentication is based on two types of features, namely, Mel-frequency cepstral coefficients and perceptual linear prediction coefficients. The model for face authentication is implemented by determining the eigenfaces. The final decision about the identity of a user is based on majority voting. Experimental results show that the new encryption method can reliably hide the identity of an individual and accurately decrypt the biometrics, which is vital for errorless authentication.

Blockchain and IoT-Based Cognitive Edge Framework for Sharing Economy Services in a Smart City

“…Recent advancements in decentralized data transactions via Blockchain [5], [11], IoT [12], MEC and Fog Computing [2], [7], [30] and 5G device-to-device (D2D) communication capability [27] will allow secure sharing economy services wherein any number of entities within a mass crowd, such as in a smart city, can perform a multiparty transaction in a decentralized manner [6], [7], [24], [25]. For example, recent medical equipment, such as CT Scan machine, has embedded IoT devices that enable data processing locally and upload the results to Blockchain and off-chain nodes running at the nearby edge [3], [7], [9], [22], [24], [28], [31]. Two parties can securely perform any online activity or financial or business transaction [3], [13], [26], [37].…”

A Survey on Biometric Authentication Systems in Cloud to Combat Identity Theft

“…In this paper [23],the authors have proposed a privacy preserving biometric system with data encrypted and stored in the database located in the cloud. The correctness of the identification system is achieved first and secondly the privacy of very sensitive biometric information and secret values of keys is captured and preserved confidentially.…”

Untitled

“…The researchers argue in [26] the suitability of signature based authentication systems for the IoT devices whereby they presented three categories of signature based scheme namely, offline, online and behaviour. Some Gait recognition based authentication systems proposed for IoT devices are also in the literature [27]. A touch screen based authentication scheme is proposed in [28].…”