A Secure and Privacy-Aware Smart Health System with Secret Key Leakage Resilience

Zhang, Yinghui; Lang, Pengzhen; Zheng, Dong; Yang, Menglei; Guo, Rui

doi:10.1155/2018/7202598

Cited by 13 publications

(8 citation statements)

References 58 publications

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“…To address privacy concerns and the security of data in smart health, the authors of [10] presented a secure s-health system built on a leakage-resilient anonymous Hierarchical Identity-Based Encryption (HIBE) plot in a limited leakage display which ensured a patient's protection despite the fact that the key was halfway spilled. This has permitted a safe transmission of information.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Data Privacy and Anonymization Algorithms for Smart Health Applications

Fakeeroodeen

Beeharry

2021

SN COMPUT. SCI.

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In line with the concept of Smart cities and Smart World, there have been bewildering developments in the field of Internet of Things (IoT) and Big Data Analytics where one most noteworthy territory is that of Smart Health. Private Health data are required to be transmitted over wireless communication systems where the main problem arising is that of data security and privacy. Various algorithms have been implemented to achieve data privacy. In this work, k-anonymity, differential privacy, k-map,-diversity and a hybrid of the three algorithms combined with ℓ-diversity have been analyzed using algorithms running on a raspberry pi (edge) for a breast cancer dataset. The results demonstrated a difference in using stand-alone algorithms in terms of output anonymized dataset, execution time, information loss, risk analysis, and statistical analysis. If solely based on its execution time, the hybrids took less than 20 s in comparison to the stand-alone taking nearly 90 s, leading to conclusion that hybrid algorithms are much more suitable in terms of efficiency. Having the option to share anonymized information quicker will reduce financial and admin costs indicating that hybrids should be the main focus even if all algorithms fulfilled their objective of achieving data privacy.

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Section: Related Workmentioning

confidence: 99%

Hybrid Data Privacy and Anonymization Algorithms for Smart Health Applications

Fakeeroodeen

Beeharry

2021

SN COMPUT. SCI.

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“…In the smart healthcare system, patients are paying more and more attention to the security of private information. Zhang et al [10,11,12,13] has done in-depth research and proposed privacy-preserving access control systems by adopting attribute-based encryption techniques to improve the security of smart healthcare. However, the techniques are complex and unfeasible in practice.…”

Section: Introductionmentioning

confidence: 99%

Identity-Based Encryption with Filtered Equality Test for Smart City Applications

Yang

Wang

2019

Sensors

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With the growth of the urban population, the rapid development of smart cities has become the focus of urban regional development. Smart medical care is an indispensable part of smart city construction, which promotes the development of the medical industry. However, the security of data and timely service are the current problems faced by intelligent medical systems. Based on the public key encryption with filtered equality test and identity-based cryptography, an identity-based encryption with the filtered equality test (IBE-FET) is proposed for smart healthcare, in which a data receiver can use the private key and the message set to generate a warrant and send it to the cloud server. A cloud server can verify the equality between ciphertexts without decryption and check whether the encrypted message belongs to the same message set. Furthermore, the security analysis shows that the proposed scheme satisfies one-way security against the chosen identity and ciphertext attack in the random oracle model under the computational bilinear Diffie-Hellman assumption. The performance comparison shows that the scheme is feasible and practical in real life.

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“…This scheme has strong practical value. To solve the privacy of the patients, Zhang et al [17] proposed a secure smart health system. In this system, data owner can securely share data to resistance the leakage attacks.…”

Section: Introductionmentioning

confidence: 99%

A Distributed Access Control with Outsourced Computation in Fog Computing

Wang

et al. 2019

Security and Communication Networks

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With the rapid development of information technology and the Internet of Things Technology (IOT), data security and healthy privacy are getting a lot of attention. In order to store, access, and share electronic health records, storage of this data is transferred to a third-party-cloud server. The security and privacy of electronic health records stored at date center or cloud server are not guaranteed. Before being sent to date center or cloud server, this data should be encrypted. Designing an efficient and secure fine-grained access control strategy for personal health records is facing enormous challenges. Security and privacy for electronic health records are very important because the electronic health data which plays an important role in medical server and treatment is directly associated with a particular patient. Attribute-based encryption (ABE) can effectively achieve fine-grained access control. However, the computation of bilinear pairings requires a large amount of computation overhead in ABE scheme. In order to decrease the computational overhead and ensure the confidentiality of electronic health records, a distributed fine-grained access control scheme with outsourced computation for IOT is proposed in this paper. Little calculation is executed by the receiver and sender in our proposed scheme. Outsourcing computing reduces the computing burden. The analyses of safety and performance show that our proposed scheme is safe and effective compared with previous schemes.

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A Secure and Privacy-Aware Smart Health System with Secret Key Leakage Resilience

Cited by 13 publications

References 58 publications

Hybrid Data Privacy and Anonymization Algorithms for Smart Health Applications

Hybrid Data Privacy and Anonymization Algorithms for Smart Health Applications

Identity-Based Encryption with Filtered Equality Test for Smart City Applications

A Distributed Access Control with Outsourced Computation in Fog Computing

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