Blockchain in healthcare applications: Research challenges and opportunities

An exhaustive survey on security and privacy issues in Healthcare 4.0

Introduction I: Multimedia Input Analysis II: Multimedia Presentation Design III: Automated Graphic Design IV: Automated Layout V: User and Discourse Modeling VI: Model Based Interfaces VII: Agent Interfaces VIII: Evaluation

Readings in Intelligent User Interfaces

Blockchain technology has been gaining visibility owing to its ability to enhance the security, reliability, and robustness of distributed systems. Several areas have benefited from research based on this technology, such as finance, remote sensing, data analysis, and healthcare. Data immutability, privacy, transparency, decentralization, and distributed ledgers are the main features that make blockchain an attractive technology. However, healthcare records that contain confidential patient data make this system very complicated because there is a risk of a privacy breach. This study aims to address research into the applications of the blockchain healthcare area. It sets out by discussing the management of medical information, as well as the sharing of medical records, image sharing, and log management. We also discuss papers that intersect with other areas, such as the Internet of Things, the management of information, tracking of drugs along their supply chain, and aspects of security and privacy. As we are aware that there are other surveys of blockchain in healthcare, we analyze and compare both the positive and negative aspects of their papers. Finally, we seek to examine the concepts of blockchain in the medical area, by assessing their benefits and drawbacks and thus giving guidance to other researchers in the area. Additionally, we summarize the methods used in healthcare per application area and show their pros and cons.

A Survey of Blockchain-Based Strategies for Healthcare

Blockchain in healthcare applications requires robust security and privacy mechanism for high-level authentication, interoperability and medical records sharing to comply with the strict legal requirements of the Health Insurance Portability and Accountability Act of 1996. Blockchain technology in the healthcare industry has received considerable research attention in recent years. This study conducts a review to substantially analyse and map the research landscape of current technologies, mainly the use of blockchain in healthcare applications, into a coherent taxonomy. The present study systematically searches all relevant research articles on blockchain in healthcare applications in three accessible databases, namely, ScienceDirect, IEEE and Web of Science, by using the defined keywords 'blockchain', 'healthcare' and 'electronic health records' and their variations. The final set of collected articles related to the use of blockchain in healthcare application is divided into three categories. The first category includes articles (i.e. 43/58 scientific articles) that attempted to develop and design healthcare applications integrating blockchain, particularly those on new architecture, system designs, framework, scheme, model, platform, approach, protocol and algorithm. The second category includes studies (i.e., 6/58 scientific articles) that attempted to evaluate and analyse the adoption of blockchain in the healthcare system. Finally, the third category comprises review and survey articles (i.e., 6/58 scientific articles) related to the integration of blockchain into healthcare applications. The final articles for review are discussed on the basis of five aspects: (1) year of publication, (2) nationality of authors, (3) publishing house or journal, (4) purpose of using blockchain in health applications and the corresponding contributions and (5) problem types and proposed solutions. Additionally, this study provides identified motivations, open challenges and recommendations on the use of blockchain in healthcare applications. The current research contributes to the literature by providing a detailed review of feasible alternatives and identifying the research gaps. Accordingly, researchers and developers are provided with appealing opportunities to further develop decentralised healthcare applications through a comprehensive discussion of about the importance of blockchain and its integration into various healthcare applications.

A Systematic Review for Enabling of Develop a Blockchain Technology in Healthcare Application: Taxonomy, Substantially Analysis, Motivations, Challenges, Recommendations and Future Direction.

Big data security and privacy in healthcare: A Review

Mobile Agent (MA) paradigm for data aggregation in wireless sensor networks (WSNs) presents a distributed computing paradigm which has proved its efficiency in comparison to the traditional client–server computing paradigm. In terms of energy consumption and overall time response, MA computing paradigm presents a better alternative. Instead of sending the collected data to the sink as in client/server, MA moves to sensor nodes (SNs) for data collection. For MA, to move among SNs, an itinerary should be planned before the migration. Many approaches have been proposed to solve the problem, but all approaches did not take into consideration the fault tolerance problem, even though WSNs are prone to failure. In this respect, we propose Energy efficient and fault tolerant distributed algorithm for data aggregation in wireless sensor networks (EFTA) to plan the itinerary for MA and another alternative itinerary in case of node(s) failure. Our algorithm adopts a clustering method to group SNs in clusters then plans the itinerary among those clusters efficiently. Also an alternative itinerary based fault tolerance is proposed. Simulation results show that our algorithm performs better than other existing ones.

Energy efficient and fault tolerant distributed algorithm for data aggregation in wireless sensor networks

Security model for Big Healthcare Data Lifecycle

Mobile agent (MA)-based wireless sensor networks present a good alternative to the traditional client/server paradigm. Instead of sending the data gathered by each node to the sink as in client/server, MAs migrate to the sensor nodes (SNs) to collect data, thus reducing energy consumption and bandwidth usage. For MAs, to migrate among SNs, an itinerary should be planned before the migration. Many approaches have been proposed to solve the problem of itinerary planning for MAs, but all of these approaches are based on the assumption that MAs visit all SNs. This assumption, however, is inefficient because of the increasing size of the MAs after visiting each node. Also, in case of node(s) failure, as it is often the case in WSNs, the MAs may not be able to migrate among SNs. None of the proposed approaches takes into consideration the problem of fault tolerance. In this paper, we propose multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks (MAEF) to plan itineraries for MAs. This can be achieved by grouping nodes in clusters and planning itineraries efficiently among cluster heads (CHs) only. What is more, an alternative itinerary is planned in case of node(s) failure. The simulation result clearly shows that our novel approach performs better than the existing ones.

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Multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks

The problem of information overload on the Internet increased the need for personalized information retrieval (PIR) systems capable of providing information that corresponds to the user interests. Although, for most people, the word personalization comes with trust issues and privacy concerns. Since giving the user a personalized browsing experience usually comes at the cost of his privacy. Thus, most people are afraid of using such applications. To address this issue, we propose a new model for privacy protection in PIR systems. Our model aims at achieving a trade-off between the personalization quality and the privacy risk, to keep the latter under control. We have studied the assets and drawbacks of the existing profile-based PIR structures, from a privacy protection perspective, along with the possible privacy threats in this field in a threat modeling approach. The model we propose is based on the vector space model and targets profile-based PIR systems. It uses query expansion and re-ranking algorithms on the client-side to ensure personalization quality. While privacy protection is ensured during the personalization process, by taking into consideration the user’s privacy requirements, and through encryption. We use the Advanced Encryption Standard (AES) algorithm to protect user data at-rest and a fully homomorphic encryption (FHE) scheme for data in-transit and in-use protection. To prove the feasibility and efficiency of our model, this paper includes a proof-of-concept implementation with proper experimental results.

Mostafa Saadi

Papers

Big data security and privacy in healthcare: A Review

Energy efficient and fault tolerant distributed algorithm for data aggregation in wireless sensor networks

Security model for Big Healthcare Data Lifecycle

Multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks

PAPIR: privacy-aware personalized information retrieval