Securing Personal Health Records in Cloud Computing: Patient-Centric and Fine-Grained Data Access Control in Multi-owner Settings
By Ming Li, Shucheng Yu, Kui Ren, Wenjing Lou. Security and Privacy in Communication Networks, 2010
602 citations recorded by the source corpus.
Online personal health record (PHR) enables patients to manage their own medical records in a centralized way, which greatly facilitates the storage, access and sharing of personal health data. With the emergence of cloud computing, it is attractive for the PHR service providers to shift their PHR applications and storage into the cloud, in order to enjoy the elastic resources and reduce the operational cost. However, by storing PHRs in the cloud, the patients lose physical control to their personal health data, which makes it necessary for each patient to encrypt her PHR data before uploading to the cloud servers. Under encryption, it is challenging to achieve fine-grained access control to PHR data in a scalable and efficient way. For each patient, the PHR data should be encrypted so that it is scalable with the number of users having access. Also, since there are multiple owners (patients) in a PHR system and every owner would encrypt her PHR files using a different set of cryptographic keys, it is important to reduce the key distribution complexity in such multi-owner settings. Existing cryptographic enforced access control schemes are mostly designed for the single-owner scenarios.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/a73d23988e854cb1d74c62f9d5af7589da56f70c
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Citations in the corpus
- Scalable and Secure Sharing of Personal Health Records in Cloud Computing Using Attribute-Based Encryption (2019, background): “(2) We clarify the proposed revocable MA-ABE scheme, and provide a formal security proof for it.”
- Authorized Private Keyword Search over Encrypted Data in Cloud Computing (2011, methodology): “Although the accesses to actual documents can be controlled by separate cryptographic enforced access control techniques such as attribute-based encryption [9], [39], [26], “0-1” search authorization may still lead to leakage of data owners’ sensitive information.”
- A Review on the State-of-the-Art Privacy-Preserving Approaches in the e-Health Clouds (2014, methodology): “Moreover, the approach presented in [49] is improved in terms of efficient management and on-demand user/attribute revocation.”
- Verifiable Privacy-Preserving Multi-Keyword Text Search in the Cloud Supporting Similarity-Based Ranking (2013, methodology): “To further enhance the search privacy, we propose two secure index schemes to meet the stringent privacy requirements under strong threat models, i.e., known ciphertext model and known background model.”
- A Decentralized Privacy-Preserving Healthcare Blockchain for IoT (2019, background): “The patient records should be consistent and available across institutional boundaries [18,19].”
- DACC: Distributed Access Control in Clouds (2011, methodology): “Using ABE, owners encrypt data with attributes that they possess and store the”
- Big Data and machine learning in radiation oncology: State of the art and future prospects. (2016, background): “Relevant healthcare professionals’ login procedures require scalable process with a significant cost, but they should certainly not be overlooked [18].”
- Fog computing security: a review of current applications and security solutions (2017, background): “Patient health records contain sensitive data and there are multiple points in any Fog platform where they can be compromised, such as by exploiting any system and application vulnerability, unauthorised data access while in storage or during transmission, malicious insiders threat and while sharing”
- A Decentralized Security Framework for Data Aggregation and Access Control in Smart Grids (2013, background): “model in data storage applications like clouds and smart grids [8], [11].”