A critical literature review of security and privacy in smart home healthcare schemes adopting IoT & blockchain: Problems, challenges and solutions

Blockchain Research and Applications, Год журнала: 2023, Номер 5(2), С. 100178 - 100178

Опубликована: Дек. 20, 2023

Protecting private data in smart homes, a popular Internet-of-Things (IoT) application, remains significant security and privacy challenge due to the large-scale development distributed nature of IoT networks. Recently, healthcare has leveraged home systems, thereby compounding concerns terms confidentiality sensitive by extension owner. However, PoA-based Blockchain DLT emerged as promising solution for protecting from indiscriminate use preserving individuals residing IoT-enabled homes. This review elicits some concerns, issues, problems that have hindered adoption blockchain (BCoT) domains suggests requisite solutions using aging-in-place scenario. Implementation issues with BCoT were examined well combined challenges can pose when utilised gains. The study discusses recent findings, opportunities, barriers, provide recommendations could facilitate continuous growth application healthcare. Lastly, then explored potential permission an applicable consent-based model decision-making information disclosure process, including publisher-subscriber contracts fine-grained access control ensure secure processing sharing, ethical trust personal disclosure, direction. proposed authorisation framework guarantee ownership, conditional management, scalable tamper-proof storage, more resilient system against threat models such interception insider attacks.

Язык: Английский

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An automated privacy-preserving self-supervised classification of COVID-19 from lung CT scan images minimizing the requirements of large data annotation

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 2, 2025

This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier homomorphic encryption (PHE) to prevent third-party attacks during training. The FL-SSL based employs two publicly available scan datasets which are considered as labeled and an unlabeled dataset. dataset is split into three subsets assumed be collected hospitals. Training done using the Bootstrap Your Own Latent (BYOL) contrastive SSL VGG19 encoder followed by attention CNN blocks (VGG19 + CNN). input processed selecting largest portion of each automated selection approach 64 × size utilized reduce computational complexity. Healthcare privacy issues addressed collaborative training across decentralized secure aggregation PHE, underscoring effectiveness this approach. Three used train local BYOL model, together optimizes central encoder. employed (updated CNN), resulting in accuracy 97.19%, precision 97.43%, recall 98.18%. reliability framework's performance demonstrated through statistical analysis five-fold cross-validation. efficacy proposed further showcased showing its on distinct modality datasets: skin cancer, breast chest X-rays. In conclusion, offers promising solution accurate diagnosis X-rays, preserving overcoming challenges scarcity

Язык: Английский

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Secure and Decentralized Collaboration in Oncology: A Blockchain Approach to Tumor Segmentation

2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), Год журнала: 2024, Номер unknown, С. 1681 - 1686

Опубликована: Июль 2, 2024

Язык: Английский

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The Recurrent Neural Networks: Algorithm Driven Alchemy of Machine Learning into Precision Therapeutics for Today and Tomorrow

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Method for storing and managing medical big data by integrating lightweight image classification models

Journal of Radiation Research and Applied Sciences, Год журнала: 2025, Номер 18(2), С. 101332 - 101332

Опубликована: Фев. 6, 2025

Язык: Английский

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Improved blockchain-based ECDSA batch verification scheme

Frontiers in Blockchain, Год журнала: 2025, Номер 8

Опубликована: Фев. 13, 2025

Introduction Blockchain technology has attracted much attention due to its decentralization, transparency and security. Initially applied in the financial field, it now expanded various fields such as Internet of Things (IoT), electronic cash healthcare. However, open nature blockchain raised potential security concerns about sensitive transaction data, increasing number transactions requires low-latency solutions. Most applications still rely on lightweight Elliptic Curve Digital Signature Algorithm (ECDSA). Due complex operations vectorized multiplication modular inversion, this may introduce significant additional overhead. Methods To address these issues, a new scheme named KTP-ECDSA is proposed. This based improved two-parameter (TP-ECDSA) KGLP algorithm. In both signing verification processes, eliminates inverse reduces scalar multiplications during stage by using batch verification. Result The experimental results show that, compared with traditional ECDSA, achieved speed increase over 50% independent verification, significantly improving efficiency signature Discussion By adopting algorithm digital method, multiple signatures can be verified simultaneously, thus reducing computational burden single-verification method. greatly increases overall throughput improves resource utilization efficiency.

Язык: Английский

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Enhancing Healthcare Data Security: Computational Efficiency of Blockchain-Based Digital Signatures

Lecture notes in networks and systems, Год журнала: 2025, Номер unknown, С. 445 - 456

Опубликована: Янв. 1, 2025

Язык: Английский

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IDHG-ECC-integrated Diffie Hellman Galois–elliptic-curve cryptography for enhancing EHR data security

Journal of Information Security and Applications, Год журнала: 2025, Номер 90, С. 104024 - 104024

Опубликована: Март 11, 2025

Язык: Английский

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A Scoping Review of the Use of Blockchain to Support Medical Imaging Data Sharing Across Multiple Healthcare Institutions

Communications in computer and information science, Год журнала: 2025, Номер unknown, С. 411 - 420

Опубликована: Янв. 1, 2025

Язык: Английский

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TwoFish‐Integrated Blockchain for Secure and Optimized Healthcare Data Processing in IoT‐Edge‐Cloud System

Transactions on Emerging Telecommunications Technologies, Год журнала: 2025, Номер 36(3)

Опубликована: Март 1, 2025

ABSTRACT Large‐scale healthcare systems face significant challenges in ensuring security and privacy when sharing vast amounts of data across various e‐health entities. Existing studies often struggle with high processing costs, latency, energy consumption, delayed response times. To address these issues, this research proposes a novel Blockchain‐Assisted Improved Puma Edge Computing Network (BA‐IPEN) for efficient secure management. The proposed model integrates three key modules: collection at the IoT layer, edge storage cloud layer. Patient physiological are gathered from sensors transmitted to devices through remote gateway devices. At Modified Optimization Algorithm (POA) is employed maximize resource utilization while minimizing consumption latency. Additionally, computing performs preprocessing tasks such as missing filtering normalization extract valuable insights raw sensor data, thereby enhancing overall performance. For storage, TwoFish used. This algorithm encrypts collected bolstering security. Blockchain technology ensures tamper‐proof records transparent access restrictions by providing decentralized immutable ledger securely storing cloud. Extensive experiments demonstrate effectiveness BA‐IPEN model, revealing reductions computational cost latency cloud‐based storage. Experimental results also confirm superiority over traditional mechanisms, showcasing improvements performance indicators reduced consumption.

Язык: Английский

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