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Efficient and Privacy-preserving Fog-assisted Health Data Sharing Scheme

Published:24 October 2019Publication History
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Abstract

Pervasive data collected from e-healthcare devices possess significant medical value through data sharing with professional healthcare service providers. However, health data sharing poses several security issues, such as access control and privacy leakage, as well as faces critical challenges to obtain efficient data analysis and services. In this article, we propose an efficient and privacy-preserving fog-assisted health data sharing (PFHDS) scheme for e-healthcare systems. Specifically, we integrate the fog node to classify the shared data into different categories according to disease risks for efficient health data analysis. Meanwhile, we design an enhanced attribute-based encryption method through combination of a personal access policy on patients and a professional access policy on the fog node for effective medical service provision. Furthermore, we achieve significant encryption consumption reduction for patients by offloading a portion of the computation and storage burden from patients to the fog node. Security discussions show that PFHDS realizes data confidentiality and fine-grained access control with collusion resistance. Performance evaluations demonstrate cost-efficient encryption computation, storage and energy consumption.

References

  1. Moreno Ambrosin, Mauro Conti, and Tooska Dargahi. 2015. On the feasibility of attribute-based encryption on smartphone devices. In Proceedings of the Annual Conference on IoT Challenges in Mobile and Industrial Systems (IoT-Sys’15). 49--54.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Diego F. Aranha and Conrado Porto Lopes Gouvea. 2013. RELIC. Retrieved May 2, 2018 from https://github.com/relic-toolkit/relic.Google ScholarGoogle Scholar
  3. Joakim Borgh, Edith Ngai, Börje Ohlman, and AdeelMohammad Malik. 2017. Employing attribute-based encryption in systems with resource constrained devices in an information-centric networking context. In Proceedings of the Global IoT Summit (GIoTS’17). 1--6.Google ScholarGoogle ScholarCross RefCross Ref
  4. Raphael Bost, RalucaAda Popa, Stephen Tu, and Shafi Goldwasser. 2015. Machine learning classification over encrypted data. In Proceedings of the Annual Network and Distributed System Security Symposium (NDSS’15). 1--14.Google ScholarGoogle ScholarCross RefCross Ref
  5. Yu Cao, Peng Hou, Donald Brown, Jie Wang, and Songqing Chen. 2015. Distributed analytics and edge intelligence: Pervasive health monitoring at the era of fog computing. In Proceedings of the Annual Conference on Mobidata. 43--48.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Min Chen, Yongfeng Qian, Jing Chen, Kai Hwang, Shiwen Mao, and Long Hu. 2016. Privacy protection and intrusion avoidance for cloudlet-based medical data sharing. IEEE Trans. Cloud Comput. (2016). DOI:10.1109/TCC.2016.2617382Google ScholarGoogle Scholar
  7. ChengKang Chu, ShermanSM Chow, WenGuey Tzeng, Jianying Zhou, and RobertH Deng. 2014. Key-aggregate cryptosystem for scalable data sharing in cloud storage. IEEE Trans. Parallel Distrib. Syst. 25, 2 (2014), 468--477.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Dan Dobre, Paolo Viotti, and Marko Vukolić. 2014. Hybris: Robust hybrid cloud storage. In Proceedings of the ACM Symposium on Cloud Computing (SoCC’14). 1--14.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Martin Dugas, Philipp Neuhaus, Alexandra Meidt, Justin Doods, Michael Storck, Philipp Bruland, and Julian Varghese. 2016. Portal of medical data models: Information infrastructure for medical research and healthcare. Database: The Journal of Biological Databases 8 Curation (Oxford) 2016, Article bav121 (2016). DOI:10.1093/database/bav121Google ScholarGoogle Scholar
  10. Yaniv Harel, Irad Ben Gal, and Yuval Elovici. 2017. Cyber security and the role of intelligent systems in addressing its challenges. ACM Trans. Intell. Syst. Technol. 8, 4 (2017), 49.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Cheng Huang, Rongxing Lu, Hui Zhu, Jun Shao, and Xiaodong Lin. 2016. FSSR: Fine-grained EHRs sharing via similarity-based recommendation in cloud-assisted eHealthcare system. In Proceedings of the Annual Conference of the ACM ASIA Conference on Computer and Communications Security (AisaCCS’16). 95--106.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jiawen Kang, Rong Yu, Xumin Huang, Maoqiang Wu, Sabita Maharjan, Shengli Xie, and Yan Zhang. 2018. Blockchain for secure and efficient data sharing in vehicular edge computing and networks. IEEE IoT J. 6, 3 (2018), 4660--4670. DOI:10.1109/JIOT.2018.2875542Google ScholarGoogle Scholar
  13. Eduard Kovacs. 2013. FDA Issues Alert Over Vulnerable Hospira Drug Pumps. Retrieved May 2, 2018 from http://www.securityweek.com/fda-issues-alert-over-vulnerable-hospira-drug-pumps.Google ScholarGoogle Scholar
  14. Jin Li, YanKit Li, Xiaofeng Chen, PatrickPC Lee, and Wenjing Lou. 2015. A hybrid cloud approach for secure authorized deduplication. IEEE Trans. Parallel Distrib. Syst. 26, 5 (2015), 1206--1216.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Jin Li, Yinghui Zhang, Xiaofeng Chen, and Yang Xiang. 2018. Secure attribute-based data sharing for resource-limited users in cloud computing. Comput. Secur. 72 (2018), 1--12.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Ming Li, Shucheng Yu, Yao Zheng, Kui Ren, and Wenjing Lou. 2013. Scalable and secure sharing of personal health records in cloud computing using attribute-based encryption. IEEE Trans. Parallel Distrib. Syst. 24, 1 (2013), 131--143.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Qing Liu, BryanP Yan, CheukMan Yu, YuanTing Zhang, and CarmenCY Poon. 2014. Attenuation of systolic blood pressure and pulse transit time hysteresis during exercise and recovery in cardiovascular patients. IEEE Trans. Biomed. Eng. 61, 2 (2014), 346--352.Google ScholarGoogle ScholarCross RefCross Ref
  18. W Liu and E. K. Park. 2014. Big data as an e-health service. In Proceedings of the International Conference on Computing, Networking and Communication (ICNC’14). 982--988.Google ScholarGoogle Scholar
  19. Ximeng Liu, Robert H. Deng, Yang Yang, Hieu N. Tran, and Shangping Zhong. Hybrid privacy-preserving clinical decision support system in fog--cloud computing. (unpublished).Google ScholarGoogle Scholar
  20. Ximeng Liu, Rongxing Lu, Jianfeng Ma, Le Chen, and Baodong Qin. 2016. Privacy-preserving patient-centric clinical decision support system on naive Bayesian classification. IEEE J. Biomed. Health Inf. 20, 2 (2016), 655--668.Google ScholarGoogle ScholarCross RefCross Ref
  21. Yi Liu, Yinghui Zhang, Jie Ling, and Zhusong Liu. 2017. Secure and fine-grained access control on e-healthcare records in mobile cloud computing. Fut. Gener. Comput. Syst. 78, 3 (2017).Google ScholarGoogle Scholar
  22. Xuhong Peng, Ju Ren, Liang She, Deyu Zhang, Jie Li, and Yaoxue Zhang. 2018. Boat: A block-streaming app execution scheme for lightweight iot devices. IEEE IoT J. 5, 3 (2018), 1816--1829.Google ScholarGoogle Scholar
  23. Aarathi Prasad, Xiaohui Liang, and David Kotz. 2014. Poster: Balancing disclosure and utility of personal information. In Proceedings of the International Conference on Mobile Systems, Applications, and Services (MobiSys’14). 380--381.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Amir Rahmani, Tuan Gia, Behailu Negash, Arman Anzanpour, Iman Azimi, Mingzhe Jiang, and Pasi Liljeberg. 2017. Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Fut. Gener. Comput. Syst. 78 (2017), 641--658.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Ju Ren, Hui Guo, Chugui Xu, and Yaoxue Zhang. 2017. Serving at the edge: A scalable IoT architecture based on transparent computing. IEEE Netw. 31, 5 (2017), 96--105.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Adi Shamir. 1979. How to share a secret. Commun. ACM 22, 11 (1979), 612--613.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Jian Shen, Tianqi Zhou, Xiaofeng Chen, Jin Li, and Willy Susilo. 2017. Anonymous and traceable group data sharing in cloud computing. IEEE Trans. Inf. Forens. Secur. 13, 4 (2017), 912--925.Google ScholarGoogle ScholarCross RefCross Ref
  28. Wenjuan Tang, Kuan Zhang, Ju Ren, Yaoxue Zhang, and Xuemin Shen. 2019. Flexible and efficient authenticated key agreement scheme for bans based on physiological features. IEEE Trans. Mobile Comput. 18, 4 (2019), 845--856.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Wenjuan Tang, Kuan Zhang, Deyu Zhang, Ju Ren, Yaoxue Zhang, and Xuemin Sherman Shen. 2019. Fog-enabled smart health: Toward cooperative and secure healthcare service provision. IEEE Commun. Mag. 57, 5 (2019), 42--48.Google ScholarGoogle ScholarCross RefCross Ref
  30. Yue Tong, Jinyuan Sun, Sherman Chow, and Pan Li. 2013. Towards auditable cloud-assisted access of encrypted health data. In Proceedings of the Annual Conference of the Canadian Nuclear Society. 514--519.Google ScholarGoogle Scholar
  31. Shulan Wang, Junwei Zhou, Joseph K. Liu, Jianping Yu, Jianyong Chen, and Weixin Xie. 2016. An efficient file hierarchy attribute-based encryption scheme in cloud computing. IEEE Trans. Inf. Forens. Secur. 11, 6 (2016), 1265--1277.Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Xinlei Wang, Jianqing Zhang, Eve M. Schooler, and Mihaela Ion. 2014. Performance evaluation of attribute-based encryption: Toward data privacy in the IoT. In Proceedings of the Annual Conference on IEEE International Conference on Communications (ICC’14). 725--730.Google ScholarGoogle ScholarCross RefCross Ref
  33. Brent Waters. 2011. Ciphertext-policy attribute-based encryption: An expressive, efficient, and provably secure realization. In Proceedings of the International Conference on Theory and Practice in Public Key Cryptography (PKC’11). 53--70.Google ScholarGoogle ScholarCross RefCross Ref
  34. Chugui Xu, Ju Ren, Yaoxue Zhang, Zhan Qin, and Kui Ren. 2017. Dppro: Differentially private high-dimensional data release via random projection. IEEE Trans. Inf. Forens. Secur. 12, 12 (2017), 3081--3093.Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Yang Xu, Ju Ren, Guojun Wang, Cheng Zhang, Jidian Yang, and Yaoxue Zhang. 2019. A blockchain-based non-repudiation network computing service scheme for industrial IoT. IEEE Trans. Industr. Inf. 15, 6 (2019), 3632--3641. DOI:10.1109/TII.2019.2897133Google ScholarGoogle ScholarCross RefCross Ref
  36. Zhongyuan Xu and ScottD Stoller. 2015. Mining attribute-based access control policies. IEEE Trans. Depend. Sec. Comput. 12, 5 (2015), 533--545.Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. JiJiang Yang, JianQiang Li, and Yu Niu. 2015. A hybrid solution for privacy preserving medical data sharing in the cloud environment. Fut. Gener. Comput. Syst. 43 (2015), 74--86.Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Kan Yang, Zhen Liu, Xiaohua Jia, and Xuemin Shen. 2016. Time-domain attribute-based access control for cloud-based video content sharing: A cryptographic approach. IEEE Trans. Multimed. 18, 5 (2016), 940--950.Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. LoYao Yeh, WoeiJiunn Tsaur, and HsinHan Huang. 2017. Secure IoT-based, incentive-aware emergency personnel dispatching scheme with weighted fine-grained access control. ACM Trans. Intell. Syst. Technol. 9, 1 (2017), 10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Hui Yin, Zheng Qin, Lu Ou, and Keqin Li. 2017. A query privacy-enhanced and secure search scheme over encrypted data in cloud computing. J. Comput. Syst. Sci. 90 (2017), 14--27.Google ScholarGoogle ScholarCross RefCross Ref
  41. Kuan Zhang, Xiaohui Liang, Jianbing Ni, Kan Yang, and Xuemin Shen. Exploiting social network to enhance human-to-human infection analysis without privacy leakage. (unpublished).Google ScholarGoogle Scholar
  42. Kuan Zhang, Kan Yang, Xiaohui Liang, Zhou Su, Xuemin Shen, and Henry H. Luo. 2015. Security and privacy for mobile healthcare networks: From a quality of protection perspective. IEEE Wireless Commun. 22, 4 (2015), 104--112.Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Lide Zhang, Birjodh Tiwana, Zhiyun Qian, Zhaoguang Wang, Robert P. Dick, ZhuoqingMorley Mao, and Lei Yang. 2010. Accurate online power estimation and automatic battery behavior based power model generation for smartphones. In Proceedings of the Annual Conference on International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS’10). 105--114.Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Shaobo Zhang, Xiong Li, Zhiyuan Tan, Tao Peng, and Guojun Wang. 2019. A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services. Fut. Gener. Comput. Syst. 94 (2019), 40--50.Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Yin Zhang, Meikang Qiu, ChunWei Tsai, MohammadMehedi Hassan, and Atif Alamri. 2017. Health-CPS: Healthcare cyber-physical system assisted by cloud and big data. IEEE Syst. J. 11, 1 (2017), 88--95.Google ScholarGoogle ScholarCross RefCross Ref
  46. Alicia L. Nobles, Ketki Vilankar, Hao Wu, and Laura E. Barnes. 2015. Evaluation of data quality of multisite electronic health record data for secondary analysis. In Proceedings of IEEE International Conference on Big Data (BigData'15). 2612--2620.Google ScholarGoogle Scholar

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          cover image ACM Transactions on Intelligent Systems and Technology
          ACM Transactions on Intelligent Systems and Technology  Volume 10, Issue 6
          Special Section on Intelligent Edge Computing for Cyber Physical and Cloud Systems and Regular Papers
          November 2019
          267 pages
          ISSN:2157-6904
          EISSN:2157-6912
          DOI:10.1145/3368406
          Issue’s Table of Contents

          Copyright © 2019 ACM

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          Publication History

          • Published: 24 October 2019
          • Accepted: 1 June 2019
          • Revised: 1 May 2019
          • Received: 1 March 2019
          Published in tist Volume 10, Issue 6

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