BinDaaS: Blockchain-Based Deep-Learning as-a-Service in Healthcare 4.0 Applications

Electronic Health Records (EHRs) allows patients to control, share, and manage their health records among family members, friends, and healthcare service providers. Thus, pri- vacy, confidentiality, and data consistency are major challenges in such an environment. Although, cloud-based EHRs addresses the aforementioned issues, but these are prone to malicious attacks, trust management, and non-repudiation among servers. Hence, blockchain-based EHR systems are preferable to create the trust, security, and privacy among healthcare users. Motivated from the aforementioned discussions, we proposes a framework called as Blockchain-Based Deep Learning as-a-Service (BinDaaS). It integrates blockchain and deep-learning techniques for sharing EHR records among multiple healthcare users and operates in two phases. In the first phase, an authentication and signature scheme is proposed based on lattices-based cryptography to resist collusion attacks among N-1 healthcare authorities from N. In the second phase, Deep Learning as-a-Service (DaaS) is used on stored EHR datasets to accurately predict future diseases based on current indicators and features of patient. The obtained results are compared using various parameters such as accuracy, end-to- end latency, mining time, and computation and communication costs in comparison to the existing state-of-the-art proposals.