Process Mining Error Detection for Securing the IoT System
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How to Cite

Shakya, Subarna. 2020. “Process Mining Error Detection for Securing the IoT System”. Journal of ISMAC 2 (3): 147-53. https://doi.org/10.36548/jismac.2020.3.002.

Keywords

— Anomaly Detection
— Data Mining
— Process Mining
— Internet of Things
— Security Management
Published: 08-07-2020

Abstract

As the use of Internet-of-Things in day to lives increases, its connection with objects and use of sensors has increased in number largely. These objects are also integrated with the internet, enabling its application in many more complex systems. Though efforts have been implemented to protect the security management, there are some major challenges faced by system because of the limited resources, heterogeneity and complexity of the system. This gives way to detecting the various attacks by characterizing the IoT system. Using a novel architecture with appropriate components, we have proposed a prototype of our concept that is used to determine the performance of the system by means of real-time input from the industries by extensive experimentation.

References

  1. Duraipandian, M. (2019). Performance Evaluation of Routing Algorithm for Manet Based on the Machine.
  2. K. Delaney and E. Levy, “Connected Futures Cisco Research : IoT Value : Challenges, Breakthroughs, and Best Practices.” Cisco System Report, May 2017.
  3. M. Zaman and C. Lung, “Evaluation of Machine Learning Techniques for Network Intrusion Detection,” in Proceedings of the IEEE/IFIP International Network Operations and Management Symposium (NOMS 2018), April 2018, pp. 1–5.
  4. M. Antonakakis, T. April, M. Bailey, M. Bernhard, E. Bursztein, J. Cochran, Z. Durumeric, J. A. Halderman, L. Invernizzi, M. Kallitsis et al., “Understanding the Mirai Botnet,” in Proceedings of the USENIX Security Symposium, 2017, pp. 1092–1110.
  5. Shakya, S. (2020). Performance Analysis of Wind Turbine Monitoring Mechanism Using Integrated Classification and Optimization Techniques. Journal of Artificial Intelligence, 2(01), 31-41.
  6. E. Bertino and N. Islam, “Botnets and Internet of Things Security,” Computer, vol. 50, no. 02, pp. 76–79, feb 2017.
  7. He, Z., Wu, Q., Wen, L., & Fu, G. (2019). A process mining approach to improve emergency rescue processes of fatal gas explosion accidents in Chinese coal mines. Safety science, 111, 154-166.
  8. C. Kolias, G. Kambourakis, A. Stavrou, and J. Voas, “DDoS in the IoT: Mirai and Other Botnets,” Computer, vol. 50, no. 7, pp. 80–84, 2017.
  9. Haoxiang, W., & Smys, S. (2020). Soft Computing Strategies for Optimized Route Selection in Wireless Sensor Network. Journal of Soft Computing Paradigm (JSCP), 2(01), 1-12.
  10. Ghasemi, M., & Amyot, D. (2020). From event logs to goals: a systematic literature review of goal-oriented process mining. Requirements Engineering, 25(1), 67-93.
  11. Adithya, M., Scholar, P. G., & Shanthini, B. (2020). Security Analysis and Preserving Block-Level Data DE-duplication in Cloud Storage Services. Journal of trends in Computer Science and Smart technology (TCSST), 2(02), 120-126.
  12. L. Rouch, J. François, F. Beck, and A. Lahmadi, “A Universal Controller to Take Over a Z-Wave Network,” in Proceedings of Black Hat Europe, 2017, pp. 1–9.