A Blockchain-Based Consent Mechanism for Access to Fitness Data in the Healthcare Context

Alhajri, May; Rudolph, Carsten; Salehi, Seyedmohammad

doi:10.1109/access.2022.3154106

Cited by 14 publications

(5 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Alhajri et al [15] presented a novel framework for managing consent in the sharing of fitness data. The authors proposed a blockchain-based dynamic consent mechanism to mitigate privacy concerns associated with fitness tracker privacy policies.…”

Section: Related Workmentioning

confidence: 99%

A Reference Design Model to Manage Consent in Data Subjects-Centered Internet of Things Devices

Khatiwada,

Yang,

Lin

et al. 2024

IoT

View full text Add to dashboard Cite

Internet of Things (IoT) devices have changed how billions of people in the world connect and interact with each other. But, as more people use IoT devices, many questions arise about how these devices handle private data and whether they properly ask for permission when using it. Due to information privacy regulations such as the EU’s General Data Protection Regulation (GDPR), which requires companies to seek permission from data subjects (DS) before using their data, it is crucial for IoT companies to obtain this permission correctly. However, this can be really challenging in the IoT world because people often find it difficult to interact with and manage multiple IoT devices under their control. Also, the rules about privacy are not always clear. As such, this paper proposes a new model to improve how consent is managed in the world of IoT. The model seeks to minimize “consent fatigue” (when people get tired of always being asked for permission) and give DS more control over how their data are shared. This includes having default permission settings, being able to compare similar devices, and, in the future, using AI to give personalized advice. The model allows users to easily review and change their IoT device permissions if previous conditions are not met. It also emphasizes the need for easily understandable privacy rules, clear communication with users, and robust tracking of consent for data usage. By using this model, companies that provide IoT services can do a better job of protecting user privacy and managing DS consent. In addition, companies can more easily comply with data protection laws and build stronger relationships with their customers.

show abstract

Section: Related Workmentioning

confidence: 99%

A Reference Design Model to Manage Consent in Data Subjects-Centered Internet of Things Devices

Khatiwada,

Yang,

Lin

et al. 2024

IoT

View full text Add to dashboard Cite

show abstract

“…Its unique structure addresses different security issues in IoT networks. In [28], they use the unique consent mechanism of blockchains to secure user data privacy in wearable fitness devices. They aim to prove the feasibility of the trustworthiness of blockchains when fortifying the data privacy of wearable IoT device data.…”

Section: Blockchain For Wearable Iot Devicesmentioning

confidence: 99%

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Baucas

Spachos

Plataniotis

2023

IEEE Trans. Comput. Soc. Syst.

View full text Add to dashboard Cite

Over the years, the popularity and usage of wearable Internet of Things (IoT) devices in several healthcare services are increased. Among the services that benefit from the usage of such devices is predictive analysis, which can improve early diagnosis in e-health. However, due to the limitations of wearable IoT devices, challenges in data privacy, service integrity, and network structure adaptability arose. To address these concerns, we propose a platform using federated learning and private blockchain technology within a fog-IoT network. These technologies have privacy-preserving features securing data within the network. We utilized the fog-IoT network's distributive structure to create an adaptive network for wearable IoT devices. We designed a testbed to examine the proposed platform's ability to preserve the integrity of a classifier. According to experimental results, the introduced implementation can effectively preserve a patient's privacy and a predictive service's integrity. We further investigated the contributions of other technologies to the security and adaptability of the IoT network. Overall, we proved the feasibility of our platform in addressing significant security and privacy challenges of wearable IoT devices in predictive healthcare through analysis, simulation, and experimentation.

show abstract

“…In order to maintain a fair and reliable trading environment for smart grids, we have developed a modular, decentralised user management network (UMN) based on the Hyperledger Fabric framework (Hyperledger Fabric is an open-source blockchain framework hosted by The Linux Foundation that can be used as the basis for developing applications or solutions with a modular architecture, and its modular and versatile design can address a wide range of industry use cases, including education [39], healthcare [40], access control [41,42], IoT [43], logistics [44], supply chain [45] and more), which implements management, monitoring, and penalty functions for users involved in the smart grid. The network is designed to focus on managing user behaviour and reducing the harm caused by malicious behaviour.…”

Section: Design Overviewmentioning

confidence: 99%

Blockchain-Based Malicious Behaviour Management Scheme for Smart Grids

Xu,

Salehi Shahraki,

Rudolph

2023

Smart Cities

Self Cite

View full text Add to dashboard Cite

The smart grid optimises energy transmission efficiency and provides practical solutions for energy saving and life convenience. Along with a decentralised, transparent and fair trading model, the smart grid attracts many users to participate. In recent years, many researchers have contributed to the development of smart grids in terms of network and information security so that the security, reliability and stability of smart grid systems can be guaranteed. However, our investigation reveals various malicious behaviours during smart grid transactions and operations, such as electricity theft, erroneous data injection, and distributed denial of service (DDoS). These malicious behaviours threaten the interests of honest suppliers and consumers. While the existing literature has employed machine learning and other methods to detect and defend against malicious behaviour, these defence mechanisms do not impose any penalties on the attackers. This paper proposes a management scheme that can handle different types of malicious behaviour in the smart grid. The scheme uses a consortium blockchain combined with the best–worst multi-criteria decision method (BWM) to accurately quantify and manage malicious behaviour. Smart contracts are used to implement a penalty mechanism that applies appropriate penalties to different malicious users. Through a detailed description of the proposed algorithm, logic model and data structure, we show the principles and workflow of this scheme for dealing with malicious behaviour. We analysed the system’s security attributes and tested the system’s performance. The results indicate that the system meets the security attributes of confidentiality and integrity. The performance results are similar to the benchmark results, demonstrating the feasibility and stability of the system.

show abstract

A Blockchain-Based Consent Mechanism for Access to Fitness Data in the Healthcare Context

Cited by 14 publications

References 42 publications

A Reference Design Model to Manage Consent in Data Subjects-Centered Internet of Things Devices

A Reference Design Model to Manage Consent in Data Subjects-Centered Internet of Things Devices

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Blockchain-Based Malicious Behaviour Management Scheme for Smart Grids

Contact Info

Product

Resources

About