Smart Contract-Enabled Secure Sharing of Health Data for a Mobile Cloud-Based E-Health System

Chinnasamy, P.; Albakri, Ashwag; Khan, Mudassir; Raja, A.; Kiran, Ajmeera; Babu, J. Chinna

doi:10.3390/app13063970

Cited by 44 publications

(11 citation statements)

References 22 publications

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“…Blockchain-based access control mechanisms have been implemented to secure the access shared resources. The public key infrastructure is widely used for authentication where a user public key can be leveraged to authorize the access if this public key is specified in the authorized policy list [23]. To secure access to healthcare data in emergency situations, the smart contracts are leveraged to implement the Role-Based Access Control (RBAC) model [24].…”

Section: A Access Control Mechanismsmentioning

confidence: 99%

Blockchain-Based Authorization Mechanism for Educational Social Internet of Things

Dallel,

Ayed,

Tahar

2024

IEEE Access

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The Social Internet of Things (SIoT) paradigm has been integrated in the education domain to enable educational IoT devices to establish social relationships and exchange academic services. Nonetheless, the social relationships are not adapted to the educational context where devices must be socially linked based on their academic roles and activities. Furthermore, the exchange of services raises the requirement to implement an access control mechanism. In SIoT, social constraints such as the social relationship type and contact frequency are critical requirements to make an access decision. However, these constraints cannot be specified using the eXtensible Access Control Markup Language (XACML) standard as device attributes nor as contextual conditions. In this paper, we propose an Educational Social Internet of Things (EducationalSIoT) platform implemented as an application-specific blockchain where we define new social relationships for educational devices. To control the access to the academic services, we suggest extending the XACML policy model by considering the social requirements, and accordingly, we adjust the policy evaluation process and suggest priority-based combining algorithms. Additionally, our platform ensures the delegation of access permission by defining delegation policies and controlling the delegation operation with consideration of the social features. The simulation results show that by integrating social features, an access request is evaluated in 0.22ms and a delegation request is evaluated in 0.32ms. Finally, we guarantee that our platform is protected against the man-in-the-middle and replay attacks.

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Section: A Access Control Mechanismsmentioning

confidence: 99%

Blockchain-Based Authorization Mechanism for Educational Social Internet of Things

Dallel,

Ayed,

Tahar

2024

IEEE Access

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“…1) Field of application. It encompasses various typical application fields, including Business/Finance Management, Energy, Governance, Healthcare, Industrial Management, Smart Cities/Smart Homes, Transport, and others [17], [26], [50]- [52] (see Figure 7). 2) Scenario.…”

Section: ) Extraction Criteriamentioning

confidence: 99%

“…This criterion outlines different FN configurations, encompassing base stations, cloudlets, gateways, micro data centers, MEC nodes, routers, servers, switches, virtual machines, virtual switches, vehicles, and other customized designs. Each node type corresponds to specific functionalities and roles within the FC architecture, contributing to the ecosystem's overall efficiency and performance [8], [17], [50], [54]. 3) Node Tasks.…”

Section: ) Use Case It Outlines Specific Instances or Examplesmentioning

confidence: 99%

“…It involves securely and efficiently sharing data among participants, ensuring trust, and maintaining integrity through methods such as consensus and encryption. Techniques like storing hash values in blockchain and cross-chain sharing ensure reliable data exchange in diverse IoT/FC systems [50], [54]. 3) Validation.…”

Section: ) Precision the Level Of Detail And Accuracy In Modelmentioning

confidence: 99%

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Exploring the Synergy of Fog Computing, Blockchain, and Federated Learning for IoT Applications: A Systematic Literature Review

Solis,

Marcelo Parra-Ullauri,

Kertesz

2024

IEEE Access

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The proliferation of Internet of Things (IoT) applications poses formidable challenges in managing data processing, privacy, and security. In response, technologies such as Fog Computing (FC), Blockchain (BC), and Federated Learning (FL) have emerged as promising solutions. Combining these technologies can broaden their scope, and impose novel challenges. This paper conducts a Systematic Literature Review (SLR) to investigate their integration within the IoT domain, systematically evaluating the current state-of-the-art by analyzing 40 papers against 38 extraction criteria, encompassing technical characteristics specific to FC, BC, FL, or their integration. The findings offer insights into the advantages, challenges, opportunities, and limitations of this integration, addressing data processing, privacy, and security concerns in IoT. By filling a research gap and directly examining FC, BC, and FL interoperability across architectural layers, this study contributes to knowledge expansion in the field. This paper proposes a novel framework for implementing FL and BC within FC environments for IoT applications, alongside a comprehensive synthesis of existing literature, distinguishing it from previous research efforts. Furthermore, it offers valuable insights into the current landscape, identifies research needs, and proposes future research directions. The framework and literature synthesis provided allow readers to access customized information on FC-BC-FL integration, aiding in designing and implementing robust IoT solutions.

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“…With the development of virtual communication, users can safely communicate and share information with other systems worldwide [1]. Cryptography is a key topic for secure data transfer.…”

Section: Introductionmentioning

confidence: 99%

On the Cryptanalysis of a Simplified AES Using a Hybrid Binary Grey Wolf Optimization

Rizk-Allah,

Abdulkader,

Elatif

et al. 2023

Mathematics

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Cryptosystem cryptanalysis is regarded as an NP-Hard task in modern cryptography. Due to block ciphers that are part of a modern cipher and have nonlinearity and low autocorrelation in their structure, traditional techniques and brute-force attacks suffer from breaking the key presented in traditional techniques, and brute-force attacks against modern cipher S-AES (simplified-advanced encryption standard) are complex. Thus, developing robust and reliable optimization with high searching capability is essential. Motivated by this, this paper attempts to present a novel binary hybridization algorithm based on the mathematical procedures of the grey wolf optimizer (GWO) and particle swarm optimization (PSO), named BPSOGWO, to deal with the cryptanalysis of (S-AES). The proposed BPSOGWO employs a known plaintext attack that requires only one pair of plaintext–ciphertext pairs instead of other strategies that require more pairs (i.e., it reduces the number of messages needed in an attack, and secret information such as plaintext-ciphertext pairs cannot be obtained easily). The comprehensive and statistical results indicate that the BPSOGWO is more accurate and provides superior results compared to other peers, where it improved the cryptanalysis accurateness of S-AES by 82.5%, 84.79%, and 79.6% compared to PSO, GA, and ACO, respectively. Furthermore, the proposed BPSOGWO retrieves the optimal key with a significant reduction in search space compared to a brute-force attack. Experiments show that combining the suggested fitness function with HPSOGWO resulted in a 109-fold reduction in the search space. In cryptanalysis, this is a significant factor. The results prove that BPSOGWO is a promising and effective alternative to attack the key employed in the S-AES cipher.

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Smart Contract-Enabled Secure Sharing of Health Data for a Mobile Cloud-Based E-Health System

Cited by 44 publications

References 22 publications

Blockchain-Based Authorization Mechanism for Educational Social Internet of Things

Blockchain-Based Authorization Mechanism for Educational Social Internet of Things

Exploring the Synergy of Fog Computing, Blockchain, and Federated Learning for IoT Applications: A Systematic Literature Review

On the Cryptanalysis of a Simplified AES Using a Hybrid Binary Grey Wolf Optimization

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