Abstract
Current advances in technology have led to the emergence of networks of small and low-cost devices that incorporate sensors with embedded processing and limited wireless communication capabilities. IoT is used in healthcare for monitoring patients via wearable sensors for measuring many physiological information. These collected information’s can be stored, processed, and make it available to doctors to give a consultation at any time which improves the efficiency of the traditional medical systems. Indeed, due to multiple design faults and a lack of effective security measures in healthcare equipment and applications, the healthcare industry based in IoT is increasingly confronting security challenges and threats. For this reason, big security measures should be taken to ensure that patients’ data can only be accessed by legitimate users. In this chapter, we offer a comprehensive overview of many potential attacks and explore their implications. In addition, we examine and debate the existing security solutions proposed for healthcare systems.
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References
Goyal, S., Sharma, N., Bhushan, B., Shankar, A., & Sagayam, M. (2021). IoT enabled technology in secured healthcare: Applications, challenges and future directions. In A. E. Hassanien, A. Khamparia, D. Gupta, K. Shankar, & A. Slowik (Eds.), Cognitive internet of medical things for smart healthcare (Studies in systems, decision and control) (Vol. 311). Springer. https://doi.org/10.1007/978-3-030-55833-8_2
Bhushan, B., & Sahoo, G. (2020). Requirements, protocols, and security challenges in wireless sensor networks: An industrial perspective. In Handbook of computer networks and cyber security (pp. 683–713). Springer. https://doi.org/10.1007/978-3-030-22277-2_27
Othman, S. B., Bahattab, A. A., Trad, A., & Youssef, H. (2019). LSDA: Lightweight secure data aggregation scheme in healthcare using IoT. In 10th International Conference on Information Systems and Technologies, Lecce, Italy, Dec 28, 2019–Dec 30, 2019, Tunisia. https://doi.org/10.1145/3447568.3448530.
Othman, S. B., Bahattab, A. A., Trad, A., et al. (2015). Confidentiality and integrity for data aggregation in WSN using homomorphic encryption. Wireless Personal Communications, 80, 867–889. https://doi.org/10.1007/s11277-014-2061-z
Soufiene, B. O., Bahattab, A. A., Trad, A., & Youssef, H. (2019). RESDA: Robust and efficient secure data aggregation scheme in healthcare using the IoT. In 2019 International Conference on Internet of Things, Embedded Systems and Communications (IINTEC) (pp. 209–213). IINTEC. https://doi.org/10.1109/IINTEC48298.2019.9112125
Onesimu, J. A., Karthikeyan, J., & Sei, Y. (2021). An efficient clustering-based anonymization scheme for privacy-preserving data collection in IoT based healthcare services. Peer-to-Peer Networking and Applications, 14, 1629–1649. https://doi.org/10.1007/s12083-021-01077-7
Almalki, F. A., & Soufiene, B. O. (2021). EPPDA: An efficient and privacy-preserving data aggregation scheme with authentication and authorization for iot-based healthcare applications. Wireless Communications and Mobile Computing, 2021, 5594159. 18 pages. https://doi.org/10.1155/2021/5594159
Arul, R., Al-Otaibi, Y. D., Alnumay, W. S., et al. (2021). Multi-modal secure healthcare data dissemination framework using blockchain in IoMT. Personal and Ubiquitous Computing. https://doi.org/10.1007/s00779-021-01527-2
Kumar, M., & Chand, S. (2020). A secure and efficient cloud-centric internet-of-medical-things-enabled smart healthcare system with public verifiability. IEEE Internet of Things Journal, 7(10), 10650–10659. https://doi.org/10.1109/JIOT.2020.3006523
Almalki, F. A., Othman, S. B., Almalki, F. A., & Sakli, H. (2021). EERP-DPM: Energy efficient routing protocol using dual prediction model for healthcare using IoT. Journal of Healthcare Engineering, 2021, 9988038, 15 pages. https://doi.org/10.1155/2021/9988038
Soufiene, B. O., Bahattab, A. A., Trad, A., & Youssef, H. (2020). PEERP: An priority-based energy-efficient routing protocol for reliable data transmission in healthcare using the IoT. Procedia Computer Science, 175, 373–378. https://doi.org/10.1016/j.procs.2020.07.053
Goyal, S., Sharma, N., Kaushik, I., & Bhushan, B. (2021). Blockchain as a solution for security attacks in named data networking of things. In Security and privacy issues in IoT devices and sensor networks, 211–243. https://doi.org/10.1016/B978-0-12-821255-4.00010-9.
Saxena, S., Bhushan, B., & Ahad, M. A. (2021). Blockchain based solutions to secure IoT: Background, integration trends and a way forward. Journal of Network and Computer Applications, 181, 103050. https://doi.org/10.1016/j.jnca.2021.103050
Haque, A. K., Bhushan, B., & Dhiman, G. (2021). Conceptualizing smart city applications: Requirements, architecture, security issues, and emerging trends. Expert Systems. https://doi.org/10.1111/exsy.12753
Kumar, A., Abhishek, K., Bhushan, B., & Chakraborty, C. (2021). Secure access control for manufacturing sector with application of Ethereum blockchain. Peer-to-Peer Networking and Applications, 14, 3058–3074. https://doi.org/10.1007/s12083-021-01108-3
Bhushan, B., Sahoo, C., Sinha, P., & Khamparia, A. (2020). Unification of blockchain and internet of Things (BIoT): Requirements, working model, challenges and future directions. Wireless Networks, 27, 55–90. https://doi.org/10.1007/s11276-020-02445-6
Bhushan, B., Sinha, P., Sagayam, K. M., & Onesimu, J. A. (2021). Untangling blockchain technology: A survey on state of the art, security threats, privacy services, applications and future research directions. Computers & Electrical Engineering, 90, 106897. https://doi.org/10.1016/j.compeleceng.2020.106897
Paul, A., Pinjari, H., Hong, W.-H., Seo, H. C., & Rho, S. (2018). Fog computing-based IoT for health monitoring system. Journal of Sensors, 2018, 1386470., 7 pages. https://doi.org/10.1155/2018/1386470
Kraemer, F. A., Braten, A. E., Tamkittikhun, N., & Palma, D. (2017). Fog computing in healthcare–A review and discussion. IEEE Access, 5, 9206–9222. https://doi.org/10.1109/ACCESS.2017.2704100
Awaisi, K. S., Hussain, S., Ahmed, M., Khan, A. A., & Ahmed, G. (2020). Leveraging IoT and fog computing in healthcare systems. IEEE Internet of Things Magazine, 3(2), 52–56. https://doi.org/10.1109/IOTM.0001.1900096
Ijaz, M., Li, G., Lin, L., Cheikhrouhou, O., Hamam, H., & Noor, A. (2021). Integration and applications of fog computing and cloud computing based on the internet of things for provision of healthcare Services at Home. Electronics, 10, 1077. https://doi.org/10.3390/electronics10091077
Qi, Q., & Tao, F. (2019). A smart manufacturing service system based on edge computing, fog computing, and cloud computing. IEEE Access, 7, 86769–86777. https://doi.org/10.1109/ACCESS.2019.2923610
Wang, T., & Chen, H. (2017). SGuard: A lightweight SDN safe-guard architecture for DoS attacks. China Communications, 14(6), 113–125. https://doi.org/10.1109/CC.2017.7961368
Fu, J., Liu, Y., Chao, H., Bhargava, B. K., & Zhang, Z. (2018). Secure data storage and searching for industrial IoT by integrating fog computing and cloud computing. IEEE Transactions on Industrial Informatics, 14(10), 4519–4528. https://doi.org/10.1109/TII.2018.2793350
Wang, T., Chen, H., Cheng, G., & Lu, Y. (2018). SDNManager: A safeguard architecture for SDN DoS attacks based on bandwidth prediction. Security and Communication Networks, 2018, 7545079., 16 pages. https://doi.org/10.1155/2018/7545079
Wang, T., & Chen, H. (2021). A lightweight SDN fingerprint attack defense mechanism based on probabilistic scrambling and controller dynamic scheduling strategies. Security and Communication Networks, 2021, 6688489., 23 pages. https://doi.org/10.1155/2021/6688489
Shu, Z., Wan, J., Li, D., et al. (2016). Security in software-defined networking: Threats and countermeasures. Mobile Networks and Applications, 21, 764–776. https://doi.org/10.1007/s11036-016-0676-x
Ahvar, E., Ahvar, S., Raza, S. M., Manuel Sanchez Vilchez, J., & Lee, G. M. (2021). Next generation of SDN in cloud-fog for 5G and beyond-enabled applications: Opportunities and challenges. Network, 1, 28–49. https://doi.org/10.3390/network1010004
Li, Y., Su, X., Ding, A. Y., Lindgren, A., Liu, X., Prehofer, C., Riekki, J., Rahmani, R., Tarkoma, S., & Hui, P. (2020). Enhancing the internet of things with knowledge-driven software-defined networking technology: Future perspectives. Sensors, 20, 3459. https://doi.org/10.3390/s20123459
Kamboj, P., Khare, S., & Pal, S. (2021). User authentication using Blockchain based smart contract in role-based access control. Peer-to-Peer Networking and Applications, 14, 2961–2976. https://doi.org/10.1007/s12083-021-01150-1
Patil, P., Sangeetha, M., & Bhaskar, V. (2021). Blockchain for IoT access control, security and privacy: A review. Wireless Personal Communications, 117, 1815–1834. https://doi.org/10.1007/s11277-020-07947-2
Mubarakali, A. (2021). An efficient authentication scheme using blockchain technology for wireless sensor networks. Wireless Personal Communications. https://doi.org/10.1007/s11277-021-08212-w
Ren, Y., Zhao, Q., Guan, H., et al. (2020). A novel authentication scheme based on edge computing for blockchain-based distributed energy trading system. Journal on Wireless Communications and Networking, 2020, 152. https://doi.org/10.1186/s13638-020-01762-w
Andola, N. R., Yadav, V. K., et al. (2021). SpyChain: A lightweight Blockchain for authentication and anonymous authorization in IoD. Wireless Personal Communications, 119, 343–362. https://doi.org/10.1007/s11277-021-08214-8
Kuzlu, M., Fair, C., & Guler, O. (2021). Role of artificial intelligence in the internet of things (IoT) cybersecurity. Discov Internet Things, 1, 7. https://doi.org/10.1007/s43926-020-00001-4
Meneghello, F., Calore, M., Zucchetto, D., Polese, M., & Zanella, A. (2019). IoT: Internet of threats? A survey of practical security vulnerabilities in real IoT devices. IEEE Internet of Things Journal, 6(5), 8182–8201. https://doi.org/10.1109/JIOT.2019.2935189
Farivar, F., Haghighi, M. S., Jolfaei, A., & Alazab, M. (2020). Artificial intelligence for detection, estimation, and compensation of malicious attacks in nonlinear cyber-physical systems and industrial IoT. IEEE Transactions on Industrial Informatics, 16(4), 2716–2725. https://doi.org/10.1109/TII.2019.2956474
Wang, S., & Qiao, Z. (2019). Robust pervasive detection for adversarial samples of artificial intelligence in IoT environments. IEEE Access, 7, 88693–88704. https://doi.org/10.1109/ACCESS.2019.2919695
Liang, F., Hatcher, W. G., Liao, W., Gao, W., & Yu, W. (2019). Machine learning for security and the internet of things: The good, the bad, and the ugly. IEEE Access, 7, 158126–158147. https://doi.org/10.1109/ACCESS.2019.2948912
Kumar, M., & Chand, S. (2021). MedHypChain: A patient-centered interoperability hyperledger-based medical healthcare system: Regulation in COVID-19 pandemic. Journal of Network and Computer Applications, 179, 102975. https://doi.org/10.1016/j.jnca.2021.102975
Li, J., Jin, J., Lyu, L., Dong, Y., Yang, Y., Gao, L., & Shen, C. (2021). A fast and scalable authentication scheme in IOT for smart living. Future Generation Computer Systems, 117, 125–137. https://doi.org/10.1016/j.future.2020.11.006
Sharmila, A. H., & Jaisankar, N. (2020). E-MHMS: Enhanced MAC-based secure delay-aware healthcare monitoring system in WBAN. Cluster Computing, 23, 1725–1740. https://doi.org/10.1007/s10586-020-03121-2
Sangeetha Priya, N., Sasikala, R., Alavandar, S., et al. (2018). Security aware trusted cluster based routing protocol for wireless body sensor networks. Wireless Personal Communications, 102, 3393–3411. https://doi.org/10.1007/s11277-018-5374-5
Haseeb, K., Islam, N., Saba, T., Rehman, A., & Mehmood, Z. (2020). LSDAR: A light-weight structure based data aggregation routing protocol with secure internet of things integrated next-generation sensor networks. Sustainable Cities and Society, 54, 101995. https://doi.org/10.1016/j.scs.2019.101995
Sachin, D., Chinmay, C., Jaroslav, F., Rashmi, G., Arun, K. R., & Subhendu, K. P. (2021). SSII: Secured and high-quality steganography using intelligent hybrid optimization algorithms for IoT. IEEE Access, 9, 1–16. https://doi.org/10.1109/ACCESS.2021.3089357
Chinmay, C., & Arij, N. A. (2021). Intelligent internet of things and advanced machine learning techniques for COVID-19. EAI Endorsed Transactions on Pervasive Health and Technology, 21(26), e1. https://doi.org/10.4108/eai.28-1-2021.168505
Chinmay, C. (2020). Joel JPC Rodrigues, A comprehensive review on device-to-device communication paradigm: Trends, challenges and applications. Springer: International Journal of Wireless Personal Communications, 114, 185–207. https://doi.org/10.1007/s11277-020-07358-3
Chinmay, C. (2019). Performance analysis of compression techniques for chronic wound image transmission under smartphone-enabled tele-wound network. International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, 10(2), 1–20.
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Othman, S.B., Almalki, F.A., Sakli, H. (2022). Internet of Things in the Healthcare Applications: Overview of Security and Privacy Issues. In: Chakraborty, C., Khosravi, M.R. (eds) Intelligent Healthcare. Springer, Singapore. https://doi.org/10.1007/978-981-16-8150-9_9
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