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Efficient Partially Policy-Hidden CP-ABE for IoT Assisted Smart Health

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Advances in Artificial Intelligence and Security (ICAIS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1424))

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Abstract

With the rapid advancements of Internet of Things (IoT) technologies, wearable devices assisted cloud-based smart health (s-health) has become the promising solution to improve the quality and convenience of healthcare. However, the privacy preserving and data security has not been perfectly addressed. In past few years, ciphertext-policy attribute-based encryption (CP-ABE) proposed as a flexible and powerful cryptographic primitive to realize one-to-many encryption and fine-grained access control has been regarded as a promising solution to the security problem in cloud. But in traditional CP-ABE, the attribute values in access policy are presented in cleartext. This will easily divulge the privacy of the data owners (patients). So in this paper, we propose a efficient partially policy-hidden CP-ABE scheme (PPH-CP-ABE), which can effectively hide the attribute values in ciphertext to protect the sensitive information in access policy. Our access policy in our PPH-CP-ABE scheme can supports both AND and OR gates which is based on the Linear Secret Sharing Scheme (LSSS). And our PPH-CP-ABE scheme is more efficient and lightweight than the other CP-ABE schemes with hidden policies. Furthermore, we give a rigorous security proof and analysis to state that our scheme is selectively indistinguishable secure under chosen plaintext attacks (selectively IND-CPA secure) and resistant to the off-line dictionary attacks. Through comparison with the state-of-art schemes from the perspective of functionality and efficiency, it is easily to observe that our scheme is more practical, secure and efficient in the real s-health scenarios.

This work was supported in part by NSFC with No. 61520106007, the Natural Science Foundation of China under Grant U1936101 and the 13th Five-Year Plan of National Cryptography Development Fund for Cryptographic Theory of China under Grant MMJJ20170204.

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Authors and Affiliations

  1. School of Information and Software Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, 610054, China

    Zhishuo Zhang, Wei Zhang, Hanxiang Zhuang & Zhiguang Qin

  2. Fujian Normal University, Fuzhou, Fujian, China

    Yu Sun

Authors
  1. Zhishuo Zhang
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  2. Wei Zhang
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  3. Hanxiang Zhuang
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  4. Yu Sun
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  5. Zhiguang Qin
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Correspondence to Zhiguang Qin .

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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Zhang, Z., Zhang, W., Zhuang, H., Sun, Y., Qin, Z. (2021). Efficient Partially Policy-Hidden CP-ABE for IoT Assisted Smart Health. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1424. Springer, Cham. https://doi.org/10.1007/978-3-030-78621-2_52

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  • DOI: https://doi.org/10.1007/978-3-030-78621-2_52

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