A Review of Blockchain Technology Based Techniques to Preserve Privacy and to Secure for Electronic Health Records

Research has been done to broaden the block chain’s use cases outside of finance since Bitcoin introduced it. One sector where block chain is anticipated to have a big influence is healthcare. Researchers and practitioners in health informatics constantly struggle to keep up with the advancement of this field's new but quickly expanding body of research. This paper provides a thorough analysis of recent studies looking into the application of block chain based technology within the healthcare sector. Electronic health records (EHRs) are becoming a crucial tool for health care practitioners in achieving these objectives and providing high-quality treatment. Technology and regulatory barriers, such as concerns about results and privacy issues, make it difficult to use these technologies. Despite the fact that a variety of efforts have been introduced to focus on the specific privacy and security needs of future applications with functional parameters, there is still a need for research into the application, security and privacy complexities, and requirements of block chain based healthcare applications, as well as possible security threats and countermeasures. The primary objective of this article is to determine how to safeguard electronic health records (EHRs) using block chain technology in healthcare applications. It discusses contemporary HyperLedgerfabrics techniques, Interplanar file storage systems with block chain capabilities, privacy preservation techniques for EHRs, and recommender systems

Blockchain in EU e-health - blocked by the barrier of data protection?

Compliance with data protection requirements is always a tricky business and even more intricate when it comes to cutting-edge technologies such as distributed ledger technology (DLT), better known as Block Chain Technology (BCT). These difficulties increase even more when the personal data concerned is accorded a special level of protection, as is the case with health data. The following article aims to describe and analyze the legal issues associated with this scenario. The focus here is on the European Union's (EU) General Data Protection Regulation (GDPR) 1, which took effect on May 25, 2018. Furthermore, the functionality of BCT and its possible fields of application in healthcare will be outlined

Wireless body sensor networks for health-monitoring applications

This is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. The publisher is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Smartphone: The Ultimate IoT and IoE Device

Internet of Things (IoT) and Internet of Everything (IoE) are emerging communication concepts that will interconnect a variety of devices (including smartphones, home appliances, sensors, and other network devices), people, data, and processes and allow them to communicate with each other seamlessly. These new concepts can be applied in many application domains such as healthcare, transportation, and supply chain management (SCM), to name a few, and allow users to get real-time information such as location-based services, disease management, and tracking. The smartphone-enabling technologies such as built-in sensors, Bluetooth, radio-frequency identification (RFID) tracking, and near-field communications (NFC) allow it to be an integral part of IoT and IoE world and the mostly used device in these environments. However, its use imposes severe security and privacy threats, because the smartphone usually contains and communicates sensitive private data. In this chapter, we provide a comprehensive survey on IoT and IoE technologies, their application domains, IoT structure and architecture, the use of smartphones in IoT and IoE, and the difference between IoT networks and mobile cellular networks. We also provide a concise overview of future opportunities and challenges in IoT and IoE environments and focus more on the security and privacy threats of using the smartphone in IoT and IoE networks with a suggestion of some countermeasures

Automated Model-based Attack Tree Analysis using HiP-HOPS

As Cyber-Physical Systems (CPS) grow increasingly complex and interact with external CPS, system security remains a nontrivial challenge that continues to scale accordingly, with potentially devastating consequences if left unchecked. While there is a significant body of work on system security found in industry practice, manual diagnosis of security vulnerabilities is still widely applied. Such approaches are typically resource-intensive, scale poorly and introduce additional risk due to human error. In this paper, a model-based approach for Security Attack Tree analysis using the HiP-HOPS dependability analysis tool is presented. The approach is demonstrated within the context of a simple web-based medical application to automatically generate attack trees, encapsulated as Digital Dependability Identities (DDIs), for offline security analysis. The paper goes on to present how the produced DDIs can be used to approach security maintenance, identifying security capabilities and controls to counter diagnosed vulnerabilities

An Approach for Managing Access to Personal Information Using Ontology-Based Chains

The importance of electronic healthcare has caused numerous changes in both substantive and procedural aspects of healthcare processes. These changes have produced new challenges to patient privacy and information secrecy. Traditional privacy policies cannot respond to rapidly increased privacy needs of patients in electronic healthcare. Technically enforceable privacy policies are needed in order to protect patient privacy in modern healthcare with its cross organisational information sharing and decision making. This thesis proposes a personal information flow model that specifies a limited number of acts on this type of information. Ontology classified Chains of these acts can be used instead of the "intended/business purposes" used in privacy access control to seamlessly imbuing current healthcare applications and their supporting infrastructure with security and privacy functionality. In this thesis, we first introduce an integrated basic architecture, design principles, and implementation techniques for privacy-preserving data mining systems. We then discuss the key methods of privacypreserving data mining systems which include four main methods: Role based access control (RBAC), Hippocratic database, Chain method and eXtensible Access Control Markup Language (XACML). We found out that the traditional methods suffer from two main problems: complexity of privacy policy design and the lack of context flexibility that is needed while working in critical situations such as the one we find in hospitals. We present and compare strategies for realising these methods. Theoretical analysis and experimental evaluation show that our new method can generate accurate data mining models and safe data access management while protecting the privacy of the data being mined. The experiments followed comparative kind of experiments, to show the ease of the design first and then follow real scenarios to show the context flexibility in saving personal information privacy of our investigated method

Enhancing Data Security in Healthcare IoT: An Innovative Blockchain-based Solution

The Internet of Things (IoT) has revolutionized the healthcare industry by enabling the seamless integration of medical devices, sensors, and data-driven applications. However, the large influx of sensitive healthcare data and the proliferation of linked devices have caused grave worries about data security and privacy. Traditional centralized security systems are unable to handle the changing threats and problems in the IoT healthcare setting. This study suggests a novel strategy for boosting data security in the healthcare industry that makes use of blockchain technology. The main goal of this research is to develop and deploy a trustworthy framework that safeguards private healthcare information in IoT networks. Blockchain, as a distributed and decentralized ledger, offers inherent security features such as immutability, transparency, and cryptographic mechanisms. In this research, it is suggested that healthcare data be gathered via the IoT and stored in the Interplanetary File System (IPFS) using Ethereum-based blockchain technology for data security. The suggested method creates a reliable environment for managing healthcare data by exploiting the special features of blockchain. The json and jpeg files are utilized five times on a distributed database housed on IPFS and a centralized database hosted on Firebase, and the upload and download times are recorded. For IoT-based healthcare systems, we have also investigated the cost and length of time required to implement smart contracts on blockchain platforms like Rinkeby, Binance, and Matic. This research suggests implementing the Blockchain platform in an IoT-based healthcare system to provide data confidentiality, integrity, and accessibility