PSMPA: Patient Self-Controllable and Multi-Level Privacy-Preserving Cooperative Authentication in Distributedm-Healthcare Cloud Computing System

Zhou, Jun; Lin, Xiaodong; Dong, Xiaolei; Cao, Zhenfu

doi:10.1109/tpds.2014.2314119

Cited by 90 publications

(33 citation statements)

References 16 publications

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“…To overcome the privacy risk, the data were earlier anonymized, but still, there are chances of re-identification of individuals. To overcome this, various researchers 127,242,243,[285][286][287][288][289] have worked in this field and proposed schemes to provide searching and sharing capabilities of medical data, for instance, Li et al 288 utilized attribute-based encryption (ABE) to provide search ability for personal health records. 284 In EHR systems, the details of a patient are entered, which are utilized by the doctors for diagnosis of the disease.…”

Section: Encrypted Genomic Datamentioning

confidence: 99%

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Handa

Krishna

Aggarwal

2019

Concurrency and Computation

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Outsourcing confidential data to cloud storage leads to privacy challenges that can be reduced using encryption. However, with encryption in place, the utilization of the data is reduced, which leads to reduced quality of experience of the users. To overcome this, searchable encryption (SE) schemes are utilized, which allow the end users to retrieve the relevant documents from the cloud, for which various researchers have worked utilizing different techniques. Despite the popularity of the searchable encryption schemes, most of the surveys either do not provide or present an incomplete taxonomy of SE schemes. Hence, in this paper, we attempt to present a complete taxonomy/classification of the searchable encryption schemes in terms of the type of search, type of index, results retrieved, implementation type, multiplicity of users, and the technique used. From the literature, it is observed that inner product similarity is widely adopted by researchers to compute the similarity of the query and the document index as it provides both conjunctive and disjunctive searching (ie, have better search capability) but requires high search time (ie, have lower search efficiency). On the other hand, schemes based on binary comparisons exist, which require less search time (ie, have better search efficiency) but support only conjunctive searching (ie, have limited search capability). Thus, a major conclusion drawn from our work is that there is an imbalance between search capability and search efficiency, ie, in the existing schemes, search capability can be improved at the cost of search time only. Therefore, we suggest that one direction where researchers should work on is to provide a balance between search capability and search efficiency.

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Section: Encrypted Genomic Datamentioning

confidence: 99%

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Handa

Krishna

Aggarwal

2019

Concurrency and Computation

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“…Recently, Zhou et al [32] propose a secure text mining scheme, where a privacy-preserving data aggregation method is served as the building block to enable data training in cloud assisted e-healthcare system. Considering the data access problem, Zhou et al [33] propose a user-controlled multi-level cooperative authentication scheme to protect user's attribute information from disclosing during the data exchange.…”

Section: Related Workmentioning

confidence: 99%

Exploiting Social Network to Enhance Human-to-Human Infection Analysis without Privacy Leakage

Liang

Shen

2018

IEEE Trans. Dependable and Secure Comput.

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Human-to-human infection, as a type of fatal public health threats, can rapidly spread in a human population, resulting in a large amount of labor and health cost for treatment, control and prevention. To slow down the spread of infection, social network is envisioned to provide detailed contact statistics to isolate susceptive people who has frequent contacts with infected patients. In this paper, we propose a novel human-to-human infection analysis approach by exploiting social network data and health data that are collected by social network and e-healthcare technologies. We enable the social cloud server and health cloud server to exchange social contact information of infected patients and user's health condition in a privacy-preserving way. Specifically, we propose a privacy-preserving data query method based on conditional oblivious transfer to guarantee that only the authorized entities can query users' social data and the social cloud server cannot infer anything during the query. In addition, we propose a privacy-preserving classification-based infection analysis method that can be performed by untrusted cloud servers without accessing the users' health data. The performance evaluation shows that the proposed approach achieves higher infection analysis accuracy with the acceptable computational overhead. Index Terms-Social network, infection analysis, privacy preservation! 1545-5971 (c)

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“…Previous works have pursued security and privacy‐preservation in electronic health record systems. The authors in give an overview of algorithms that have been proposed for publishing structured patient data or data aggregation in a privacy‐preserving way.…”

Section: Related Workmentioning

confidence: 99%

Consent-based access control for secure and privacy-preserving health information exchange

Zhang

Bacchus

Lin

2016

Security Comm. Networks

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Electronic health record exchanges are crucial functions of modern healthcare systems. These components are fundamental in providing quality care and enable for a larger spectrum of services. A framework which protects patient information during data exchanges is essential for healthcare systems. To achieve security and privacy‐preservation for information exchange, we propose a consent‐based access control (CBAC) mechanism for healthcare systems. A consent is an authorization initiated by a patient for an intended data requester via an agreement between them. After obtaining the consent from the patient, a healthcare organization can gain access to the data, which is encrypted by a healthcare provider. This is achieved by a cryptographic primitive: conditional proxy re‐encryption. By doing so, patient medical data is protected against access of unauthorized parties, including public data center. Additionally, the proposed scheme achieves collusion resistance. Furthermore, mutual authentication and contextual privacy are attained. Performance evaluation demonstrates that the proposed CBAC scheme can achieve security and privacy preservation with high computational efficiency. Copyright © 2016 John Wiley & Sons, Ltd.

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PSMPA: Patient Self-Controllable and Multi-Level Privacy-Preserving Cooperative Authentication in Distributedm-Healthcare Cloud Computing System

Cited by 90 publications

References 16 publications

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Exploiting Social Network to Enhance Human-to-Human Infection Analysis without Privacy Leakage

Consent-based access control for secure and privacy-preserving health information exchange

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