Secure and Trustable Electronic Medical Records Sharing using Blockchain

Electronic medical records (EMRs) are critical, highly sensitive private information in healthcare, and need to be frequently shared among peers. Blockchain provides a shared, immutable and transparent history of all the transactions to build applications with trust, accountability and transparency. This provides a unique opportunity to develop a secure and trustable EMR data management and sharing system using blockchain. In this paper, we present our perspectives on blockchain based healthcare data management, in particular, for EMR data sharing between healthcare providers and for research studies. We propose a framework on managing and sharing EMR data for cancer patient care. In collaboration with Stony Brook University Hospital, we implemented our framework in a prototype that ensures privacy, security, availability, and fine-grained access control over EMR data. The proposed work can significantly reduce the turnaround time for EMR sharing, improve decision making for medical care, and reduce the overall costComment: AMIA 2017 Annual Symposium Proceeding

AnonyControl: Control Cloud Data Anonymously with Multi-Authority Attribute-Based Encryption

Cloud computing is a revolutionary computing paradigm which enables flexible, on-demand and low-cost usage of computing resources. However, those advantages, ironically, are the causes of security and privacy problems, which emerge because the data owned by different users are stored in some cloud servers instead of under their own control. To deal with security problems, various schemes based on the Attribute- Based Encryption (ABE) have been proposed recently. However, the privacy problem of cloud computing is yet to be solved. This paper presents an anonymous privilege control scheme AnonyControl to address the user and data privacy problem in a cloud. By using multiple authorities in cloud computing system, our proposed scheme achieves anonymous cloud data access, finegrained privilege control, and more importantly, tolerance to up to (N -2) authority compromise. Our security and performance analysis show that AnonyControl is both secure and efficient for cloud computing environment.Comment: 9 pages, 6 figures, 3 tables, conference, IEEE INFOCOM 201

Homo Datumicus : correcting the market for identity data

Effective digital identity systems offer great economic and civic potential. However, unlocking this potential requires dealing with social, behavioural, and structural challenges to efficient market formation. We propose that a marketplace for identity data can be more efficiently formed with an infrastructure that provides a more adequate representation of individuals online. This paper therefore introduces the ontological concept of Homo Datumicus: individuals as data subjects transformed by HAT Microservers, with the axiomatic computational capabilities to transact with their own data at scale. Adoption of this paradigm would lower the social risks of identity orientation, enable privacy preserving transactions by default and mitigate the risks of power imbalances in digital identity systems and markets

InShopnito: an advanced yet privacy-friendly mobile shopping application

Mobile Shopping Applications (MSAs) are rapidly gaining popularity. They enhance the shopping experience, by offering customized recommendations or incorporating customer loyalty programs. Although MSAs are quite effective at attracting new customers and binding existing ones to a retailer's services, existing MSAs have several shortcomings. The data collection practices involved in MSAs and the lack of transparency thereof are important concerns for many customers. This paper presents inShopnito, a privacy-preserving mobile shopping application. All transactions made in inShopnito are unlinkable and anonymous. However, the system still offers the expected features from a modern MSA. Customers can take part in loyalty programs and earn or spend loyalty points and electronic vouchers. Furthermore, the MSA can suggest personalized recommendations even though the retailer cannot construct rich customer profiles. These profiles are managed on the smartphone and can be partially disclosed in order to get better, customized recommendations. Finally, we present an implementation called inShopnito, of which the security and performance is analyzed. In doing so, we show that it is possible to have a privacy-preserving MSA without having to sacrifice practicality