Fog-Driven Secure Authentication and Key Exchange Scheme for Wearable Health Monitoring System

Smart wearable devices, as a popular mobile device, have a broad market. Smart wearable medical devices implemented in wearable health monitoring systems can monitor the data pertaining to a patient’s body and let the patient know their own physical condition. In addition, these data can be stored, analyzed, and processed in the cloud to effectively prevent diseases. As an Internet-of-things technology, fog computing can process, store, and control data around devices in real time. However, the distributed attributes of fog nodes make the monitored body data and medical reports at risk of privacy disclosure. In this paper, we propose a fog-driven secure authentication and key exchange scheme for wearable health monitoring systems. Furthermore, we conduct a formal analysis using the Real-Oracle-Random model, Burrows–Abadi–Needham logic, and ProVerif tools and an informal analysis to perform security verification. Finally, a performance comparison with other related schemes shows that the proposed scheme has the best advantages in terms of security, computing overhead, and communication cost.

[1]  Athanasios V. Vasilakos,et al.  Design of secure key management and user authentication scheme for fog computing services , 2019, Future Gener. Comput. Syst..

[2]  Kim-Kwang Raymond Choo,et al.  Authenticated key agreement scheme for fog-driven IoT healthcare system , 2018, Wirel. Networks.

[3]  Jeng-Shyang Pan,et al.  An efficient surrogate-assisted hybrid optimization algorithm for expensive optimization problems , 2020, Inf. Sci..

[4]  Jeng-Shyang Pan,et al.  Improved ECC-Based Three-Factor Multiserver Authentication Scheme , 2021, Secur. Commun. Networks.

[5]  Chien-Ming Chen,et al.  An Anonymous Mutual Authenticated Key Agreement Scheme for Wearable Sensors in Wireless Body Area Networks , 2018, Applied Sciences.

[6]  Tanzeem Choudhury,et al.  Activity-aware ECG-based patient authentication for remote health monitoring , 2009, ICMI-MLMI '09.

[7]  Mohammad Shojafar,et al.  LACO: Lightweight Three-Factor Authentication, Access Control and Ownership Transfer Scheme for E-Health Systems in IoT , 2019, Future Gener. Comput. Syst..

[8]  Mou Dasgupta,et al.  An elliptic curve cryptography based enhanced anonymous authentication protocol for wearable health monitoring systems , 2019, International Journal of Information Security.

[9]  Xiong Li,et al.  Anonymous mutual authentication and key agreement scheme for wearable sensors in wireless body area networks , 2017, Comput. Networks.

[10]  Xiong Li,et al.  Secure and Efficient Two-Factor User Authentication Scheme with User Anonymity for Network Based E-Health Care Applications , 2016, Journal of Medical Systems.

[11]  Ran Canetti,et al.  The random oracle methodology, revisited , 2000, JACM.

[12]  Yi Luo,et al.  An Anonymous Authentication and Key Exchange Protocol in Smart Grid , 2021 .

[13]  Jeng-Shyang Pan,et al.  PaDE: An enhanced Differential Evolution algorithm with novel control parameter adaptation schemes for numerical optimization , 2019, Knowl. Based Syst..

[14]  Aneesh M. Koya,et al.  Anonymous hybrid mutual authentication and key agreement scheme for wireless body area network , 2018, Comput. Networks.

[15]  Yousaf Bin Zikria,et al.  A clogging resistant secure authentication scheme for fog computing services , 2021, Comput. Networks.

[16]  Fan Zhang,et al.  OPFKA: Secure and efficient Ordered-Physiological-Feature-based key agreement for wireless Body Area Networks , 2013, 2013 Proceedings IEEE INFOCOM.

[17]  Marimuthu Karuppiah,et al.  An efficient and secure remote user mutual authentication scheme using smart cards for Telecare medical information systems , 2018, Informatics in Medicine Unlocked.

[18]  Liping Zhang,et al.  Privacy Protection for E-Health Systems by Means of Dynamic Authentication and Three-Factor Key Agreement , 2018, IEEE Transactions on Industrial Electronics.

[19]  Yicheng Yu,et al.  An Extended Chaotic Map-Based Authentication and Key Agreement Scheme for Multi-Server Environment , 2021, Mathematics.

[20]  Marko Hölbl,et al.  A robust and efficient mutual authentication and key agreement scheme with untraceability for WBANs , 2019, Comput. Networks.

[21]  K.K. Venkatasubramanian,et al.  EKG-based key agreement in Body Sensor Networks , 2008, IEEE INFOCOM Workshops 2008.

[22]  Martín Abadi,et al.  A logic of authentication , 1989, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[23]  Ping Wang,et al.  Zipf’s Law in Passwords , 2017, IEEE Transactions on Information Forensics and Security.

[24]  Mu-En Wu,et al.  A secure authenticated and key exchange scheme for fog computing , 2020, Enterp. Inf. Syst..

[25]  Longhua Ma,et al.  Solar Wireless Sensor Network Routing Algorithm Based on Multi-Objective Particle Swarm Optimization , 2021, J. Inf. Hiding Multim. Signal Process..

[26]  Ajith Abraham,et al.  Digital watermarking with improved SMS applied for QR code , 2021, Eng. Appl. Artif. Intell..

[27]  Saru Kumari,et al.  Efficient and Privacy-Preserving Authentication Protocol for Heterogeneous Systems in IIoT , 2020, IEEE Internet of Things Journal.

[28]  Shehzad Ashraf Chaudhry Correcting “PALK: Password-based anonymous lightweight key agreement framework for smart grid” , 2021 .

[29]  Mohammad Masdari,et al.  Key management in wireless Body Area Network: Challenges and issues , 2017, J. Netw. Comput. Appl..

[30]  Weimin Zheng,et al.  Improved Authenticated Key Agreement Scheme for Fog-Driven IoT Healthcare System , 2021, Secur. Commun. Networks.

[31]  Gautam Srivastava,et al.  Hiding sensitive information in eHealth datasets , 2021, Future Gener. Comput. Syst..

[32]  Tu Trung Nguyen A Fuzzy Approach of Large Size Remote Sensing Image Clustering , 2020, J. Inf. Hiding Multim. Signal Process..