scholarly journals Hiding Classification Rules for Data Sharing with Privacy Preservation

2005 ◽  
pp. 468-477 ◽  
Author(s):  
Juggapong Natwichai ◽  
Xue Li ◽  
Maria Orlowska
Keyword(s):  
Data Sharing ◽  
Privacy Preservation ◽  
Classification Rules

An SOA-Based Architecture to Share Medical Data with Privacy Preservation

2011 ◽  
Vol 2 (3) ◽  
pp. 11-26
Author(s):  
Mahmoud Barhamgi ◽  
Djamal Benslimane ◽  
Chirine Ghedira ◽  
Brahim Medjahed
Keyword(s):  
Web Services ◽  
Web Service ◽  
Data Sharing ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Medical Data ◽  
Query Rewriting ◽  
Healthcare Organizations ◽  
Privacy Constraints ◽  
Viable Approach

Recent years have witnessed a growing interest in using Web services as a reliable means for medical data sharing inside and across healthcare organizations. In such service-based data sharing environments, Web service composition emerged as a viable approach to query data scattered across independent locations. Patient data privacy preservation is an important aspect that must be considered when composing medical Web services. In this paper, the authors show how data privacy can be preserved when composing and executing Web services. Privacy constraints are expressed in the form of RDF queries over a mediated ontology. Query rewriting algorithms are defined to process those queries while preserving users’ privacy.

scholarly journals On Using Linear Diophantine Equations for in-Parallel Hiding of Decision Tree Rules

Entropy ◽  
2019 ◽  
Vol 21 (1) ◽  
pp. 66 ◽  
Author(s):  
Georgios Feretzakis ◽  
Dimitris Kalles ◽  
Vassilios S. Verykios
Keyword(s):  
Decision Tree ◽  
Electronic Commerce ◽  
Decision Trees ◽  
Data Sharing ◽  
Diophantine Equations ◽  
Classification Rules ◽  
Common Procedure ◽  
Linear Diophantine Equations ◽  
Look Ahead ◽  
Cryptographic Techniques

Data sharing among organizations has become an increasingly common procedure in several areas such as advertising, marketing, electronic commerce, banking, and insurance sectors. However, any organization will most likely try to keep some patterns as hidden as possible once it shares its datasets with others. This paper focuses on preserving the privacy of sensitive patterns when inducing decision trees. We adopt a record augmentation approach to hide critical classification rules in binary datasets. Such a hiding methodology is preferred over other heuristic solutions like output perturbation or cryptographic techniques, which limit the usability of the data, since the raw data itself is readily available for public use. We propose a look ahead technique using linear Diophantine equations to add the appropriate number of instances while maintaining the initial entropy of the nodes. This method can be used to hide one or more decision tree rules optimally.

scholarly journals A Hyperledger Fabric-Based System Framework for Healthcare Data Management

2021 ◽  
Vol 11 (24) ◽  
pp. 11693
Author(s):  
Qianyu Wang ◽  
Shaowen Qin
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Privacy Protection ◽  
Privacy Preservation ◽  
Privacy Preserving ◽  
Smart Contracts ◽  
Medical Practices ◽  
Healthcare Data ◽  
Blockchain Technology ◽  
Existing Data

This study examined the requirements for privacy-preserving and interoperability in healthcare data sharing and proposed a blockchain-based solution. The Hyperledger Fabric framework was adopted due to its enterprise-grade data processing capabilities and enhanced privacy protection functions. In addition to the Fabric’s built-in privacy-preserving functions, healthcare data-specific smart contracts with hierarchical access control were developed to strengthen privacy protection in data sharing. The proposed healthcare data-sharing framework is based on Australian medical practices with the aim to upgrade, rather than to replace, the existing data management models. The outcome of this study demonstrates the feasibility of applying blockchain technology to improve privacy-preservation while enhancing interoperability in healthcare data management.

An SOA-Based Architecture to Share Medical Data with Privacy Preservation

Cyber Crime ◽  
2013 ◽  
pp. 310-324
Author(s):  
Mahmoud Barhamgi ◽  
Djamal Benslimane ◽  
Chirine Ghedira ◽  
Brahim Medjahed
Keyword(s):  
Web Services ◽  
Web Service ◽  
Data Sharing ◽  
Service Composition ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Medical Data ◽  
Healthcare Organizations ◽  
Privacy Constraints ◽  
Viable Approach

Recent years have witnessed a growing interest in using Web services as a reliable means for medical data sharing inside and across healthcare organizations. In such service-based data sharing environments, Web service composition emerged as a viable approach to query data scattered across independent locations. Patient data privacy preservation is an important aspect that must be considered when composing medical Web services. In this paper, the authors show how data privacy can be preserved when composing and executing Web services. Privacy constraints are expressed in the form of RDF queries over a mediated ontology. Query rewriting algorithms are defined to process those queries while preserving users’ privacy.

Privacy preserving model-based authentication and data security in cloud computing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ankush Balaram Pawar ◽  
Dr. Shashikant U. Ghumbre ◽  
Dr. Rashmi M. Jogdand
Keyword(s):  
Cloud Computing ◽  
Data Sharing ◽  
Data Security ◽  
Privacy Preservation ◽  
Advanced Technology ◽  
Key Generation ◽  
Content Type ◽  
Preservation Method ◽  
Data Owner ◽  
Setup Phase

Purpose Cloud computing plays a significant role in the initialization of secure communication between users. The advanced technology directs to offer several services, such as platform, resources, and accessing the network. Furthermore, cloud computing is a broader technology of communication convergence. In cloud computing architecture, data security and authentication are the main significant concerns. Design/methodology/approach The purpose of this study is to design and develop authentication and data security model in cloud computing. This method includes six various units, such as cloud server, data owner, cloud user, inspection authority, attribute authority, and central certified authority. The developed privacy preservation method includes several stages, namely setup phase, key generation phase, authentication phase and data sharing phase. Initially, the setup phase is performed through the owner, where the input is security attributes, whereas the system master key and the public parameter are produced in the key generation stage. After that, the authentication process is performed to identify the security controls of the information system. Finally, the data is decrypted in the data sharing phase for sharing data and for achieving data privacy for confidential data. Additionally, dynamic splicing is utilized, and the security functions, such as hashing, Elliptic Curve Cryptography (ECC), Data Encryption Standard-3 (3DES), interpolation, polynomial kernel, and XOR are employed for providing security to sensitive data. Findings The effectiveness of the developed privacy preservation method is estimated based on other approaches and displayed efficient outcomes with better privacy factor and detection rate of 0.83 and 0.65, and time is highly reduced by 2815ms using the Cleveland dataset. Originality/value This paper presents the privacy preservation technique for initiating authenticated encrypted access in clouds, which is designed for mutual authentication of requester and data owner in the system.

Privacy Preservation in Patient Information Exchange (PIE) Systems based on Blockchain: System Design (Preprint)

2021 ◽  
Author(s):  
Sejong ­Lee ◽  
Jaehyeon Kim ◽  
Yongseok Kwon ◽  
Teasung Kim ◽  
Sunghyun Cho
Keyword(s):  
Access Control ◽  
Data Sharing ◽  
Medical Records ◽  
Information Exchange ◽  
Privacy Preservation ◽  
Medical Information ◽  
High Reliability ◽  
Medical System ◽  
Distributed Data ◽  
High Scalability

BACKGROUND Blockchain is a distributed storage technology that provides a powerful tamper-proof technique through a distributed ledger and decentralized network. Initially, blockchain was primarily used for cryptocurrency in the financial field. However, it has attracted attention in various fields such as media, logistics, and medical care. Notably, various studies are being conducted to use blockchain in the medical field, where data reliability and integrity are essential. Representative medical blockchain research includes decentralized medical system design, secure data sharing schemes, and access control for privacy-preservation while sharing electronic medical records (EMRs). OBJECTIVE Our goal is to design a blockchain-based EMR sharing system that provides high reliability and scalability so that electronic medical records can be shared safely and efficiently. The system protects patients' privacy in medical data through a medical information exchange process that includes data encryption and access control. METHODS We propose a blockchain-based EMR sharing system that allows patients to manage the medical records scattered across multiple hospitals and share them with other users. Our patient information exchange (PIE) chain protects the patient's EMR from security threats such as counterfeiting and privacy issues during data sharing. Also, it guarantees high scalability by using distributed data sharing methods to share regardless of the size or type of EMR quickly. To check the proposed system's performance, we performed a simulation of the EMR sharing process and compared it with previous works on blockchain-based medical systems. RESULTS The simulation model is implemented using Hyperledger Fabric, an open source blockchain framework. Experimental results show that it takes an average of 10.1 ms to download 1MB of EMR on the proposed system. Moreover, it provides high scalability as it can rapidly share various data, regardless of size and type. The proposed system proposes a distributed ledger structure and a security level-based access control scheme to prevent data forgery attacks by a malicious user and unauthorized access. Moreover, it ensures high reliability by preventing data loss and privacy leakage due to sniffing and spoofing attacks with a data re-encryption scheme. CONCLUSIONS This paper proposes the PIE system, a Medical system that guarantees high reliability and scalability. The PIE system protects the EMR of the Patient created in the medical service process from threats such as personal information leakage and forgery. Through the distributed data sharing process based on blockchain, the EMR of the Patient can be quickly shared regardless of the data size. Our contribution paves the way for a patient-centered EMR sharing environment to integrate and manage patient medical information through the proposed blockchain-based Medical system.

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