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


  • 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


Healthcare, Internet of things, Machine learning, SVM


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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Boris Pervan; David G. Lawrence; Clark E. Cohen; Bradford W. Parkinson; ”Parity Space Methods for Autonomous Fault Detection and Exclusion Using GPS Carrier Phase”, PROCEEDINGS OF POSITION, LOCATION AND NAVIGATION SYMPOSIUM ..., 1996.

Andreas Kamilaris; Feng Gao; Francesc X. Prenafeta-Boldu; Muhammad Intizar Ali; ”Agri-IoT: A Semantic Framework for Internet of Thingsenabled Smart Farming Applications”, 2016 IEEE 3RD WORLD FORUM ON INTERNET OF THINGS (WF-IOT), 2016.

Menachem Domb; Elisheva Bonchek-Dokow; Guy Leshem; ”Lightweight Adaptive Random-Forest for IoT Rule Generation and Execution”, J. INF. SECUR. APPL., 2017

Mattia Antonini; Massimo Vecchio; Fabio Antonelli; Pietro Ducange; Charith Perera; ”Smart Audio Sensors in The Internet of Things Edge for Anomaly Detection”, IEEE ACCESS, 2018.

Abdulwahab Alazeb; Brajendra Panda; ”Ensuring Data Integrity in Fog Computing Based Health-Care Systems”, 2019.

Aditya Vikram; ”Anomaly Detection in Network Traffic Using Unsupervised Machine Learning Approach”, 2020 5TH INTERNATIONAL CONFERENCE ON COMMUNICATION AND ..., 2020.

Rozhin Yasaei; Felix Hernandez; Mohammad Abdullah Al Faruque; ”IoT-CAD: Context-Aware Adaptive Anomaly Detection in IoT Systems Through Sensor Association”, 2020 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER AIDED ..., 2020.

Gautami Tripathi; Mohd Abdul Ahad; Sara Paiva; ”SMS: A Secure Healthcare Model for Smart Cities”, ELECTRONICS, 2020.

Ruifeng Duo; Xiaobo Nie; Ning Yang; Chuan Yue; Yongxiang Wang; ”Anomaly Detection and Attack Classification for Train Real-Time Ethernet”, IEEE ACCESS, 2021.

icha Dridi; Ch´erifa Boucetta; Seif Eddine Hammami; Hossam Afifi; Hassine Moungla; ”STAD: Spatio-Temporal Anomaly Detection Mechanism for Mobile Network Management”, IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2021.

Raihan Bin Mofidul; Md Morshed Alam; Md Habibur Rahman; Yeong Min Jang; "Real-Time Energy Data Acquisition, Anomaly Detection, and Monitoring System: Implementation of A Secured, Robust, and Integrated Global IIoT Infrastructure with Edge and Cloud AI", SENSORS (BASEL, SWITZERLAND), 2022.

Keshav Sood; Mohammad Reza Nosouhi; Neeraj Kumar; A. Gaddam; Bohao Feng; Shui Yu; "Accurate Detection of IoT Sensor Behaviors in Legitimate, Faulty and Compromised Scenarios", IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2023.

Mudita Uppal; Deepali Gupta; Amena Mahmoud; M. Elmagzoub; Adel Sulaiman; Mana Saleh Al Reshan; A. Shaikh; Sapna Juneja; "Fault Prediction Recommender Model for IoT Enabled Sensors Based Workplace", SUSTAINABILITY, 2023.

Mattia Antonini; Miguel Pincheira; Massimo Vecchio; Fabio Antonelli; "An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments", SENSORS (BASEL, SWITZERLAND), 2023.

Aleksandr N Grekov; Aleksey A Kabanov; Elena V Vyshkvarkova; Valeriy V Trusevich; "Anomaly Detection in Biological Early Warning Systems Using Unsupervised Machine Learning", SENSORS (BASEL, SWITZERLAND), 2023.

Marek Wadinger; Michal Kvasnica; "Adaptable and Interpretable Framework for Novelty Detection in Real-Time IoT Systems", ARXIV-CS.LG, 2023.

Lei Bo; Shangqing Yang; Yang Liu; Yanwen Wang; Zihang Zhang; "Research on The Data Validity of A Coal Mine Solid Backfill Working Face Sensing System Based on An Improved Transformer", SCIENTIFIC REPORTS, 2023.

Ida Bagus Krishna Yoga Utama; Radityo Fajar Pamungkas; Muhammad Miftah Faridh; Yeong Min Jang; "Intelligent IoT Platform for Multiple PV Plant Monitoring", SENSORS (BASEL, SWITZERLAND), 2023.

Cheryl Lee; Tianyi Yang; Zhuangbin Chen; Yuxin Su; Michael R. Lyu; "Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion", ARXIV-CS.SE, 2023.

Engy El-Shafeiy; Maazen Alsabaan; Mohamed I Ibrahem; Haitham Elwahsh; "Real-Time Anomaly Detection for Water Quality Sensor Monitoring Based on Multivariate Deep Learning Technique", SENSORS (BASEL, SWITZERLAND), 2023.

T. H. Aldhyani; Mohammad Ayoub Khan; M. Almaiah; Noha Alnazzawi; A. K. Hwaitat; A. Elhag; Rami Shehab; Ali Saleh ِAlshebami; "A Secure Internet of Medical Things Framework for Breast Cancer Detection in Sustainable Smart Cities", ELECTRONICS, 2023.

Deepika Sirohi; Neeraj Kumar; Prashant Singh Rana; Sudeep Tanwar; Rahat Iqbal; Mohammad Hijjii; "Federated Learning for 6G-enabled Secure Communication Systems: A Comprehensive Survey", ARTIFICIAL INTELLIGENCE REVIEW, 2023.

Tsu-Yang Wu; Qian Meng; Yeh-Cheng Chen; S. Kumari; Chien‐Ming Chen; "Toward A Secure Smart-Home IoT Access Control Scheme Based on Home Registration Approach", MATHEMATICS, 2023.

Sista Venkata Naga Veerabhadra Sai Sudeep, S. Venkata Kiran, Durgesh Nandan, Sanjeev Kumar, An Overview of Biometrics and Face Spoofing Detection, In: Kumar A., Mozar S. (eds) ICCCE 2020. Lecture Notes in Electrical Engineering, Springer, Singapore, 698, 2021, 871-881.

Y. Sasi Supritha Devi, T. Kesava Durga Prasad, Krishna Saladi, Durgesh Nandan, Analysis of precision agriculture technique by using machine learning and IOT, In: Pant M., Kumar Sharma T., Arya R., Sahana B., Zolfagharinia H. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, Springer, Singapore. 2020/6, 1154, 859-867.

Lakshmi Mounika, P., Konda Babu, A., Nandan, D. (2021). Effective Data Acquisition with Sensors Through IoT Application: A Succinct Study. In: Kumar, A., Mozar, S. (eds) ICCCE 2020. Lecture Notes in Electrical Engineering, vol 698. Springer, Singapore.




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



Research Article