A smart city ensures quality maintenance in diverse sectors, namely citizen safety, security, healthcare, transportation, and energy. Besides, data privacy and security have become an uprising concern for Electronic Health Records (EHR) in smart cities. This is because the EHR platforms are constantly getting cyber threats from cybercriminals. On the other hand, health insurance companies offer certain specific policies that require the association of patients' financial data with EHRs. Thus, additional security concern arises as fraudulent entities can alter these insurance policies. An extra challenge is triggered as patients need to validate their identities separately while communicating with different smart healthcare entities. This is because these healthcare facilities and insurance companies ought to ensure authenticity before offering any service for an individual. Hence, we have implemented a blockchain framework to safeguard patients' personal information and insurance policy. In this paper, we propose a solution for the healthcare system that provides data privacy and transparency. Furthermore, in the proposed system, insurance policies are incorporated in blockchain via the Ethereum platform and data privacy is shielded with cryptographic tools.

Data privacy is one of the intriguing problems in e-commerce site. For personal or business purposes, users have to disclose their private data to these e-commerce sites. Often such businesses use these highly sensitive data for computing artificial intelligence-driven analyses like recommendation generation without user consent. In the case of recommendation generation, data need to be analyzed at the business platforms. An automated personalization, based on artificial intelligence, on a list of products with respect to user interest is generated by a recommender system. However, the secure utilization of user data is absent in such systems. This paper proposes Private-Rec , a privacy-preserving platform for a recommendation system through the integration of artificial intelligence and blockchain. In Private-Rec , blockchain gives the user a secure environment through the distributed attribute in which data can be used with the required permission. Under this platform, users receive incentives (i.e., point, discount) from the recommended company for sharing their data to be used for computing recommendations. The Private-Rec platform has been studied empirically.

Cross-border data sharing for knowledge generation is a challenging research direction since an application may access personal data stored in countries different from the one where the application is accessed from. In this article, we propose a cross-border data sharing platform where a global cloud is built atop multiple security gateways that are set up in different countries. Once an application requests access to data from a particular country or region, the global cloud collects the data stored in local data hubs through that region's security gateway. While transferring the data to the global cloud, the security gateway records this transfer information on a blockchain maintained by the global cloud. When an application reports any misbehavior (e.g., providing wrong data type or incorrect data) against a security gateway, the global cloud verifies the claim by auditing the blockchain and punishes the misbehaving security gateway if the claim is true. In the case of false misbehavior report, the application itself will be punished by the global cloud. Thus, our platform provides an accountable data sharing function using blockchain that relies on a relaxed trust assumption on the data providers. We include five algorithms to handle data access request, data sharing, blockchain transaction, detecting, and punishing misbehaving entities. In the algorithms, we also introduce how the transaction takes place in the platform. Thus, the proposed platform is able to handle misbehaving data sender, data receiver, or any entity participating in the platform. We analyze our platform empirically by showing different graphs, which have been generated by a number of experiments on blockchain environment. We also delineate how the multilayer of signature (Elliptic Curve Digital Signature Algorithm) acts in our platform.