MediChainTM: A Secure Decentralized Medical Data Asset Management System

The set of distributed ledger architectures known as blockchain is best known for cryptocurrency applications such as Bitcoin and Ethereum. These permissionless block chains are showing the potential to be disruptive to the financial services industry. Their broader adoption is likely to be limited by the maximum block size, the cost of the Proof of Work consensus mechanism, and the increasing size of any given chain overwhelming most of the participating nodes. These factors have led to many cryptocurrency blockchains to become centralized in the nodes with enough computing power and storage to be a dominant miner and validator. Permissioned chains operate in trusted environments and can, therefore, avoid the computationally expensive consensus mechanisms. Permissioned chains are still susceptible to asset storage demands and non-standard user interfaces that will impede their adoption. This paper describes an approach to addressing these limitations: permissioned blockchain that uses off-chain storage of the data assets and this is accessed through a standard browser and mobile app. The implementation in the Hyperledger framework is described as is an example use of patient-centered health data management.Comment: 2018 IEEE Confs on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology, Congress on Cybermatic

Privacy-Preserving Statistical Analysis of Health Data Using Paillier Homomorphic Encryption and Permissioned Blockchain

Blockchain is a decentralized and peer-to-peer ledger technology that adds transparency, traceability, and immutability to data. It has shown great promise in mitigating the interoperability problem and privacy concerns in the de facto electronic health record anagement systems and has recently received increasing attention from the healthcare industry. Several blockchain-based and decentralized health data management mechanisms have been proposed to improve the quality of care delivery to patients. Apart from care delivery, health data has other important applications, such as education, regulation, research, public health improvement, and policy sup- port. However, existing privacy acts prohibit health institutions and providers from sharing patients\u27 data with third parties. Therefore, research institutions that con- duct research on private health data need a secure system that provides accurate analysis results while preserving patient privacy and minimizing the risks of data breaches. In this thesis, We propose a novel privacy-preserving method for statis- tical analysis of health data. We leveraged the blockchain technology and Paillier encryption algorithm to increase the accuracy of data analysis while preserving the privacy of patients. Smart contracts were used to carry out mathematical operations on the encrypted records in a secure manner. We were able to successfully deploy the proposed scheme on Hyperledger Fabric, a permissioned and consortium blockchain platform. Compared to the previous works, the proposed model enjoys the bene ts of a distributed blockchain-based environment, which include higher availability and enhanced data security. The experimental results show the feasibility of this method with a reasonable amount of time for regular queries. Blockchain is a decentralized and peer-to-peer ledger technology that adds transparency, traceability, and immutability to data. It has shown great promise in mitigating the interoperability problem and privacy concerns in the de facto electronic health record anagement systems and has recently received increasing attention from the healthcare industry. Several blockchain-based and decentralized health data management mechanisms have been proposed to improve the quality of care delivery to patients. Apart from care delivery, health data has other important applications, such as education, regulation, research, public health improvement, and policy sup- port. However, existing privacy acts prohibit health institutions and providers from sharing patients\u27 data with third parties. Therefore, research institutions that con- duct research on private health data need a secure system that provides accurate analysis results while preserving patient privacy and minimizing the risks of data breaches. In this thesis, We propose a novel privacy-preserving method for statis- tical analysis of health data. We leveraged the blockchain technology and Paillier encryption algorithm to increase the accuracy of data analysis while preserving the privacy of patients. Smart contracts were used to carry out mathematical operations on the encrypted records in a secure manner. We were able to successfully deploy the proposed scheme on Hyperledger Fabric, a permissioned and consortium blockchain platform. Compared to the previous works, the proposed model enjoys the bene ts of a distributed blockchain-based environment, which include higher availability and enhanced data security. The experimental results show the feasibility of this method with a reasonable amount of time for regular queries

Blockchain and Smart Contracts: The Need for Better Education

The study aims at understanding the current scenario of blockchain education and whether it is meeting the increasing demand of blockchain professionals in the job market. In addition, it also provided a comparison between Ethereum and Hyperledger and analyzed the one best suited for better academic curriculum design. By drawing from various sources of data, including journals, articles, reports, the study provided critical insights into the various aspects of a blockchain education. It assesses the existing curriculum on the blockchain that includes courses and programs from various renowned universities and business schools. The study reveals that although the courses are comprehensive in developing theoretical knowledge of the learner, it does not provide the scope for practical skill development. This gap reflects the skill-shortage of blockchain professionals in the job market. To address this, the research also provides some guidelines for developing a comprehensive pedagogical structure using Hyperledger technology. The discussion also highlights the benefits associated with Hyperledger and the way it can foster active learning among the learners. Finally, the researcher also provided the practical and theoretical implications of the study and assessed its limitations directing on the future course of research