Attack detection and mitigation scheme through novel authentication model enabled optimized neural network in smart healthcare

References

• Al-Janabi, TA, and Al-Raweshidy HS. 2017. Optimised clustering algorithm-based centralised architecture for load balancing in IoT network. In Proceeding of International Symposium on Wireless Communication Systems (ISWCS), IEEE, p. 269–274.
   Google Scholar
• Alrashdi I, Alqazzaz A, Alharthi R, Aloufi E, Zohdy MA. Ming 2019. HFBAD: fog-based attack detection for IoT healthcare in smart cities. In 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) (pp. 0515–0522). IEEE.
   Google Scholar
• Ambarkar SS, Shekokar N. 2020. Toward smart and secure IoT based healthcare system. Internet of Things, Smart Computing and Technology: A Roadmap Ahead. 266:283–303.
   Google Scholar
• Andrea I, Chrysostomou C, Hadjichristofi G. 2015. Internet of Things: security vulnerabilities and challenges. In 2015 IEEE symposium on computers and communication (ISCC), pp. 180–187,
   Google Scholar
• Anuradha M, Jayasankar T, Prakash NB, Sikkandar MY, Hemalakshmi GR, Bharatiraja C, Britto ASF. 2021. IoT enabled cancer prediction system to enhance the authentication and security using cloud computing. Microprocess Microsyst. 80:103301.
   Web of Science ®Google Scholar
• Atzori L, Iera A, Morabito G. 2010. The Internet of Things: a survey. Comput Networks. 54(15):2787–2805.
   Web of Science ®Google Scholar
• Azimi S, Pahl C, Shirvani MH. 2021. Performance management in clustered edge architectures using particle swarm optimization. Cloud Computing and Services Science. 1399:233.
   Google Scholar
• Bagaa M, Taleb T, Bernabe JB, Skarmeta A. 2020. A machine learning security framework for IoT systems. IEEE Access. 8:114066–114077.
   Google Scholar
• Behzad S, Fotohi R, Balov JH, Rabipour MJ. 2018. An artificial immune based approach for detection and isolation misbehavior attacks in wireless networks. JCP. 13:705–720.
   Google Scholar
• Binu D, Kariyappa BS. 2021. Rider deep LSTM network for hybrid distance score-based Fault prediction in analog circuits. IEEE Trans Ind Electron. 68(10):10097–10106.
   Web of Science ®Google Scholar
• Daw-Tung L. 1997. Computer-access authentication with neural network based keystroke identity verification. In Proceedings of International Conference on Neural Networks (ICNN'97), vol. 1, p. 174–178.
   Google Scholar
• Deep G, Sidhu J, Mohana R. 2020. Role of Indian IT laws in smart healthcare devices in the intensive care unit in India. In 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC), pp. 1–5, IEEE,
   Google Scholar
• Dhumane AV, Prasad RS. 2019. Multi-objective fractional gravitational search algorithm for energy efficient routing in IoT. Wireless Netw. 25(1):399–413.
   Web of Science ®Google Scholar
• Edla DR, Tripathi D, Cheruku R, Kuppili V. 2018. An efficient multi-layer ensemble framework with BPSOGSA-based feature selection for credit scoring data analysis. Arab J Sci Eng. 43(12):6909–6928.
   Web of Science ®Google Scholar
• Fotohi R, Bari SF. 2020. A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms, J Supercomput. 76(9):6860–6827.
   Web of Science ®Google Scholar
• Fotohi R, Pakdel H. 2021. A lightweight and scalable physical layer attack detection mechanism for the Internet of Things (IoT) using hybrid security schema. Wireless Pers Commun. 119(4):3089–3018.
   Web of Science ®Google Scholar
• Fotouhi M, Bayat M, Das AK, Far HAN, Pournaghi SM, Doostari MA. 2020. A lightweight and secure two-factor authentication scheme for wireless body area networks in health-care IoT. Comput Networks. 177:107333.
   Web of Science ®Google Scholar
• G12EC dataset. 2022. https://www.kaggle.com/bjoernjostein/georgia-12lead-ecg-challenge-database.
   Google Scholar
• Goldberger A, Amaral L, Glass L, Hausdorff J, Ivanov PC, Mark R, Mietus JE, Moody GB, Peng CK, Stanley HE. (2000). PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. [Online]. 101 (23):e215–e220. https://physionet.org/content/mitdb/1.0.0/. Last accessed on 2021.
   PubMed Web of Science ®Google Scholar
• Goyal TK, Sahula V. 2016. Lightweight security algorithm for low power IoT devices. 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India.
   Google Scholar
• Kong F, Zhou Y, Xia B, Pan L. 2019. A security reputation model for IoT health data using S-AlexNet and dynamic game theory in cloud computing environment. Special Section On Data-Enabled Intelligence For Digital Health, IEEE, pp.1–9,
   Google Scholar
• Kore A, Patil S. 2020. IC-MADS: IoT enabled cross layer man-in-middle attack detection system for smart healthcare application. Wireless Pers Commun. 113(2):727–746.
   Web of Science ®Google Scholar
• Manikandan R, Patan R, Gandomi AH, Sivanesan P, Kalyanaraman H. 2020. Hash polynomial two factor decision tree using IoT for smart health care scheduling. Expert Syst Appl. 141:112924.
   Web of Science ®Google Scholar
• Mohapatra H, Debnath S, Rath AK, Landge PB, Gayen S, Kumar R. 2020. An efficient energy saving scheme through sorting technique for wireless sensor network. 8(8):4278–4286.
   Google Scholar
• Pakdel H, Fotohi R. 2021. A firefly algorithm based for power management in wireless sensor networks (WSNs). J Supercomput. 77(9):9411–9422.
   Web of Science ®Google Scholar
• Renuka K, Kumari S, Li X. 2019. Design of a secure three-factor authentication scheme for smart healthcare. J Med Syst. 43(5):1–12.
   Web of Science ®Google Scholar
• Roldán J, Boubeta-Puig J, Martínez JL, Ortiz G. 2020. Integrating complex event processing and machine learning: An intelligent architecture for detecting IoT security attacks. Expert Syst Appl. 149:113251.
   Web of Science ®Google Scholar
• Sahoo S, Mohanty S, Majhi B. 2021. A secure three factor based authentication scheme for health care systems using IoT enabled devices. J Ambient Intell Human Comput. 12(1):1419–1434.
   Web of Science ®Google Scholar
• Subasini CA, Karuppiah SP, Sheeba A, Padmakala S. 2021. Developing an attack detection framework for wireless sensor network-based healthcare applications using hybrid convolutional neural network. Trans Emerging Tel Tech. 32(11).
   Web of Science ®Google Scholar
• Suganthi S, D, R, Anitha V, Sureshkumar S, Harish S. Agalya 2020. End to end light weight mutual authentication scheme in IoT-based healthcare environment. J Reliable Intell Environ. 6(1):3–13.
   Google Scholar
• Tran-Dang H, Krommenacker N, Charpentier P, Kim D-S. 2020. Toward the Internet of Things for physical internet: perspectives and challenges. IEEE Internet Things J. 7(6):4711–4736.
   Web of Science ®Google Scholar
• Vaishnavi S, Sethukarasi T. 2021. SybilWatch: a novel approach to detect Sybil attack in IoT based smart health care. J Ambient Intell Human Comput. 12(6):6199–6115.
   Web of Science ®Google Scholar
• Wang Z, Luo N, Zhou P. 2020. GuardHealth: blockchain empowered secure data management and graph convolutional network enabled anomaly detection in smart healthcare. J Parallel Distrib Comput. 142:1–12.
   Web of Science ®Google Scholar
• Wen F, Susilo W, Yang G. 2013. A secure and effective anonymous user authentication scheme for roaming service in global mobility networks. Wireless Pers Commun. 73(3):993–1004.
   Web of Science ®Google Scholar
• Yuhui S. 2011. Brain storm optimization algorithm. In International conference in swarm intelligence, pp. 303–309.
   Google Scholar
• Zaminkar M, Fotohi R. 2020. SoS-RPL: securing Internet of Things against sinkhole attack using rpl protocol-based node rating and ranking mechanism. Wireless Pers Commun. 114(2):1287–1312.
   Web of Science ®Google Scholar