Biblio

Bio-modalities are ideal for user authentication in Medical Cyber-Physical Systems. Various forms of bio-modalities, such as the face, iris, fingerprint, are commonly used for secure user authentication. Concurrently, various spoofing approaches have also been developed over time which can fail traditional bio-modality detection systems. Image synthesis with play-doh, gelatin, ecoflex etc. are some of the ways used in spoofing bio-identifiable property. Since the bio-modality detection sensors are small and resource constrained, heavy-weight detection mechanisms are not suitable for these sensors. Recently, Fog based architectures are proposed to support sensor management in the Medical Cyber-Physical Systems (MCPS). A thin software client running in these resource-constrained sensors can enable communication with fog nodes for better management and analysis. Therefore, we propose a fog-based security application to detect bio-modality spoofing in a Fog based MCPS. In this regard, we propose a machine learning based security algorithm run as an application at the fog node using a binarized multi-factor boosted ensemble learner algorithm coupled with feature selection. Our proposal is verified on real datasets provided by the Replay Attack, Warsaw and LiveDet 2015 Crossmatch benchmark for face, iris and fingerprint modality spoofing detection used for authentication in an MCPS. The experimental analysis shows that our approach achieves significant performance gain over the state-of-the-art approaches.

6LoWPAN networks involving wireless sensors consist of resource starving miniature sensor nodes. Since secured authentication of these resource-constrained sensors is one of the important considerations during communication, use of asymmetric key distribution scheme may not be the perfect choice to achieve secure authentication. Recent research shows that Lucky Thirteen attack has compromised Datagram Transport Layer Security (DTLS) with Cipher Block Chaining (CBC) mode for key establishment. Even though EAKES6Lo and S3K techniques for key establishment follow the symmetric key establishment method, they strongly rely on a remote server and trust anchor for secure key distribution. Our proposed Lightweight Authentication Protocol (LAUP) used a symmetric key method with no preshared keys and comprised of four flights to establish authentication and session key distribution between sensors and Edge Router in a 6LoWPAN environment. Each flight uses freshly derived keys from existing information such as PAN ID (Personal Area Network IDentification) and device identities. We formally verified our scheme using the Scyther security protocol verification tool for authentication properties such as Aliveness, Secrecy, Non-Injective Agreement and Non-Injective Synchronization. We simulated and evaluated the proposed LAUP protocol using COOJA simulator with ContikiOS and achieved less computational time and low power consumption compared to existing authentication protocols such as the EAKES6Lo and SAKES.