Integrity Shield: Ensuring Real-time Data Integrity in Healthcare IoT with Isolation Forest Anomaly Detection

Authors

  • Sudhanshu Maurya Associate Professor CSE, Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune
  • Yahya Al Balushi Senior Lecturer, System Engineering Department Military Technological College, Muscat, Oman
  • Jyoti Kharade Associate Professor, Bharati Vidyapeeth's Institute of Management and Information Technology, Navi Mumbai, India
  • Jagadeesh B N Assistant Professor, Department of ISE, RNS Institute of Technology, Bangalore, India
  • Pavithra G Associate Professor, Department of Electronics & Communication Engineering, Dayananda Sagar College of Engineering (DSCE), Shavigemalleshwara Hills, Bangalore, Karnataka, India
  • Achyutha Prasad N Professor, Department of Computer Science and Engineering, East West Institute of Technology, Bangalore, India

Keywords:

Healthcare, Internet of things, Machine learning, SVM

Abstract

The healthcare sector has been greatly transformed by the Internet of Things (IoT) which brings opportunities, for monitoring and management of patient health. However, there are challenges in ensuring the reliability and authenticity of the amount of healthcare data transmitted through IoT devices. In this paper we suggest an approach called” Machine Learning Based Data Integrity Assurance for Healthcare IoT” to tackle these challenges. Our proposed algorithm utilizes machine learning techniques to detect anomalies and potential tampering attempts in time thus guaranteeing the trustworthiness and dependability of healthcare data collected from IoT devices. By establishing data profiles and continuously monitoring data streams our algorithm can adjust to evolving data patterns. Promptly identify any issues related to data integrity. Moreover, through trust-based data fusion our algorithm takes into account the trust level associated with each device in order to appropriately assess their contributions. With its adaptability, scalability and cost effectiveness our solution holds promise in enhancing the security and integrity of healthcare data, within IoT based healthcare systems.

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Published

07.02.2024

How to Cite

Maurya, S. ., Balushi, Y. A. ., Kharade, J. ., B N, J. ., G, P. ., & Prasad N, A. . (2024). Integrity Shield: Ensuring Real-time Data Integrity in Healthcare IoT with Isolation Forest Anomaly Detection. International Journal of Intelligent Systems and Applications in Engineering, 12(15s), 409 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4764

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Research Article