SIOTEHR: Secure IoT based EHR Scheme in Blockchain Ecosystem

In the present era, the number of illnesses and traumas is steadily rising. In addition, COVID-19 is still spreading in waves. Therefore EHRs (Electronic Health Records) has become a necessity now which can be used to access a patient's prior medical records through the EHR system. India is still falling behind the rest of the globe in the adoption and use of EHR. The IoT-based EHR aids in patient monitoring and enables the doctor to treat the patient right away if necessary. The goal of the EHR system will fail if the central server, which was the system's defined point of failure, fails or is compromised. In this situation, security is a major concern. In this work, we suggest adopting the blockchain technology to resolve this. We created a SIoTEHR (Secure IoT Based EHR) system that is fully decentralized, secure, traceable, auditable, private, and trustworthy by utilizing a private Ethereum Blockchain

Reliable Techniques for Providing Secure Access Control for Cloud Storage on Mobile Devices

This research focuses on the development of a credible access control method for mobile device cloud storage. The proposed method involves a six-step process, including user registration and login, key generation, data encryption and upload, authentication theory between mobile devices, and data download and decryption. The method incorporates the use of mobile TPM (Trusted Platform Module) chips to ensure trust chain transmission during key exchange. Additionally, encryption based on elliptic curve cryptography is employed to reduce the key length and facilitate secure key sharing among multiple mobile devices. The proposed method offers enhanced security and reliability compared to conventional data encryption methods provided by cloud storage service providers, with minimal interaction data and increased confidence level. It holds significant practical value and exhibits a wide range of potential applications in the field of cloud storage security technology

Cybersecurity Technologies for Protecting Social Medical Data in Public Healthcare Environments

The growing digitization of healthcare systems has made safeguarding sensitive social medical data a crucial priority. The primary objective of this study is to utilize sophisticated cybersecurity technologies, particularly machine learning (ML) algorithms, to improve the security of Electronic Health Records (EHR) in public healthcare settings. The proposed approach presents an innovative technique that merges the advantages of isolation forest and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) [IF-DBSCAN]algorithms for anomaly detection, achieving an impressive accuracy rate of 0.968. The study examines the difficulties presented by the distinct characteristics of healthcare data, which includes both medical and social information. The inadequacy of conventional security measures has necessitated the incorporation of sophisticated machine learning algorithms to detect abnormal patterns that may indicate potential security breaches. The hybrid model, which combines isolation forest and DBSCAN, seeks to overcome the constraints of current anomaly detection techniques by offering a resilient and precise solution specifically designed for the healthcare domain. The isolation forest is highly proficient at isolating anomalies by leveraging the inherent attributes of normal data, whereas DBSCAN is adept at detecting clusters and outliers within densely populated data regions. The integration of these two algorithms is anticipated to augment the overall anomaly detection capabilities, thereby strengthening the cybersecurity stance of healthcare systems. The proposed method is subjected to thorough evaluation using real-world datasets obtained from public healthcare environments. The accuracy rate of 0.968 demonstrates the effectiveness of the hybrid approach in accurately differentiating between normal and anomalous activities in EHR data. The research makes a valuable contribution to the field of cybersecurity in healthcare and also tackles the increasing concerns related to the privacy and reliability of social medical data. This research introduces an innovative method for protecting social medical data in public healthcare settings. It utilizes a sophisticated combination of isolation forest and DBSCAN to detect anomalies. The method\u27s high accuracy in the evaluation highlights its potential to greatly improve cybersecurity in healthcare systems, thereby guaranteeing the confidentiality and integrity of sensitive patient information. DOI: https://doi.org/10.52710/seejph.48

Build A Secure Healthcare System Based On the Metadata of Patient Information

Building a secure healthcare system based on metadata involves several key steps to ensure that patient information remains confidential and secure. Metadata refers to information about data, such as the time and date of creation, author, and location, rather than the content of the data itself. In this paper, there are many steps that considered when building a secure healthcare system based on metadata: we begin with defining metadata standards: Establishing metadata standards for healthcare data can help ensure consistency and interoperability across different systems. This can include standards for data elements, data formats, and data models. Implement access controls: Access controls should be implemented to restrict access to sensitive patient data. Role-based access control can be used to limit access to specific data based on job responsibilities. Use encryption: Encryption can be used to protect patient data from unauthorized access. Data encryption should be implemented at rest and in transit to protect data at all times. Secure storage: Patient data should be stored securely, including backups and archives. Secure storage can help prevent data loss and unauthorized access. We obtain a perfect time for processing compare with other resources and perfect time for check the metadata  and hyperlink of patient's information

Health Block: A Blockchain Based Secure Healthcare Data Storage and Retrieval System for Cloud Computing

Data in healthcare domain is highly sensitive in nature. Besides, there is need for maintaining integrity of such data. Blockchain technology has emerged to solve the problem of data integrity and non-repudiation with immutable storage in distributed repository. Thus secure data storage and retrieval in cloud environments is made possible using blockchain implementation. There are many existing healthcare systems with blockchain integration found in the literature. However, there is need for a system that supports complete set of operations that are governed by smart contracts. Another important consideration is that end users should be able to operate healthcare system without the need for knowledge of blockchain technology. Towards this end, in this paper, we proposed a Blockchain based secure healthcare data storage and retrieval system known as HealthBlock for cloud computing environments. We defined smart contract with underlying structures and functions using Solidity language for Ethereum blockchain platform. We also proposed and implemented an algorithm known as Healthcare Transactions over Blockchain (HToB). This algorithm supports secure blockchain based data storage and retrieval governed by smart contracts. Our system is evaluated using user-friendly web based client application. The experimental results showed that our system is able to ensure data integrity and non-repudiation besides reaping all benefits of blockchain technology

Enhancing the Security and Privacy of eHealth Records through Blockchain-based Management: A Comprehensive Framework

Progress in information technology is transforming the healthcare sector with the goal of enhancing medical services, diagnostics, and continuous monitoring through wearable devices, among other benefits, while also lowering expenses. This digital transformation enhances the convenience of computing, storing, and retrieving medical records, ultimately leading to improved treatment experiences for patients. Electronic health record systems have come under fire for centralized control, faults, and attack points with transferring data custodians. These systems are frequently utilized for the interchange of health information among healthcare stakeholders. The main objective is to overcome information asymmetry and data breaches commonly encountered in the Electronic Health Record (EHR) system. This study introduces a decentralized and trustless architecture aimed at securely storing patients' medical records and granting access to authorized individuals, including healthcare providers and patients themselves. The research primarily focuses on bolstering the security and privacy of healthcare data management systems using blockchain technology. To address the issue of blockchain scalability, an off-chain scaling approach is proposed, utilizing an underlying medium to store large volumes of data. This is achieved through the integration of Elliptic Curve Cryptography (ECC) and the Interplanetary File System (IPFS). The proposed system provides a secure and efficient method for storing and sharing sensitive healthcare data while ensuring confidentiality and data integrity

Enhancing healthcare services through cloud service: a systematic review

Although cloud-based healthcare services are booming, in-depth research has not yet been conducted in this field. This study aims to address the shortcomings of previous research by analyzing all journal articles from the last five years using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) systematic literature review methodology. The findings of this study highlight the benefits of cloud-based healthcare services for healthcare providers and patients, including enhanced healthcare services, data security, privacy issues, and innovative information technology (IT) service delivery models. However, this study also identifies challenges associated with using cloud services in healthcare, such as security and privacy concerns, and proposes solutions to address these issues. This study concludes by discussing future research directions and the need for a complete solution that addresses the conflicting requirements of the security, privacy, efficiency, and scalability of cloud technologies in healthcare

Secure-Medishare: A Comprehensive Secure Medical Data-Sharing System Using Blockchain, Watermarking, Steganography, And Optimized Hybrid Cryptography

Medical data plays a crucial role in healthcare, enabling accurate diagnosis, treatment planning, and research. However, the secure sharing of sensitive medical data and images remains a significant challenge. Existing techniques often fall short in terms of protecting data integrity, confidentiality, and authenticity. To address these limitations, this paper introduces Secure-Medishare, a novel secure medical data-sharing system that integrates blockchain technology, watermarking, steganography, and enhanced cryptography. The proposed Secure-Medishare system aims to provide robust security mechanisms for medical data sharing. Unlike centralized systems, which are susceptible to single points of failure and unauthorized access, Secure-Medishare utilizes blockchain technology to ensure decentralized and tamper-resistant storage and sharing of medical data. Secure-Medishare employs watermarking for data integrity and authentication and steganography for confidential transmission of metadata, ensuring authenticity, privacy, and confidentiality of medical data. Furthermore, an optimized hybrid cryptography technique is implemented to secure the transmission and storage of medical data, safeguarding confidentiality and privacy. Secure-Medishare offers several advantages over existing techniques. It provides enhanced security and privacy protection, efficient data sharing and retrieval, and improved trust among healthcare providers. The system ensures the integrity and authenticity of medical data, preventing unauthorized modifications or tampering. Additionally, the decentralized nature of blockchain technology reduces the risk of data breaches and single points of failure. Experimental results show that Secure-Medishare generates hashes quickly, taking only 65 milliseconds for 100 blocks. Optimized hybrid cryptography used in Secure-Medishare also outperforms other cryptography combinations, with encryption and decryption times of 5.635 seconds for 96-bit data. These findings highlight the efficiency and effectiveness of Secure-Medishare for secure medical data and image sharing. The experimental evaluation confirms that Secure-Medishare is a reliable and robust solution for secure medical data sharing in healthcare environments