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All issues Volume 430 (2023) E3S Web Conf., 430 (2023) 01152 References
Open Access
Issue
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
Article Number 01152
Number of page(s) 16
DOI https://doi.org/10.1051/e3sconf/202343001152
Published online 06 October 2023
  1. Singh and B. Sikdar, “Adversarial Attack and Defence Strategies for Deep-Learning-Based IoT Device Classification Techniques,” in IEEE Internet of Things Journal, vol. 9, no. 4, pp. 2602-2613, 15 Feb.15, 2022, doi: 10.1109/JIOT.2021.3138541. [CrossRef] [Google Scholar]
  2. M. A. Al-Garadi, A. Mohamed, A. K. Al-Ali, X. Du, I. Ali and M. Guizani, “A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security,” in IEEE Communications Surveys & Tutorials, vol. 22, no. 3, pp. 1646-1685, 2020, doi: 10.1109/COMST.2020.2988293. [CrossRef] [Google Scholar]
  3. Q. Zhang, J. -H. Cho, T. J. Moore and I. -R. Chen, “Vulnerability-Aware Resilient Networks: Software Diversity-Based Network Adaptation,” in IEEE Transactions on Network and Service Management, vol. 18, no. 3, pp. 3154-3169, Sept. 2021, doi: 10.1109/TNSM.2020.3047649. [CrossRef] [Google Scholar]
  4. H. Xu, W. Yu, D. Griffith and N. Golmie, “A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective,” in IEEE Access, vol. 6, pp. 78238-78259, 2018, doi: 10.1109/ACCESS.2018.2884906. [CrossRef] [Google Scholar]
  5. C. Garrido-Hidalgo, D. Hortelano, L. Roda-Sanchez, T. Olivares, M. C. Ruiz and V. Lopez, “IoT Heterogeneous Mesh Network Deployment for Human-in-the-Loop Challenges Towards a Social and Sustainable Industry 4.0,” in IEEE Access, vol. 6, pp. 28417-28437, 2018, doi: 10.1109/ACCESS.2018.2836677. [CrossRef] [Google Scholar]
  6. O. B. Mora-Sánchez, E. López-Neri, E. J. Cedillo-Elias, E. Aceves-Martínez and V. M. Larios, “Validation of IoT Infrastructure for the Construction of Smart Cities Solutions on Living Lab Platform,” in IEEE Transactions on Engineering Management, vol. 68, no. 3, pp. 899-908, June 2021, doi: 10.1109/TEM.2020.3002250. [CrossRef] [Google Scholar]
  7. Yin, Chuanlong, et al. “A deep learning approach for intrusion detection using recurrent neural networks.” IEEE Access 5 (2017): 21954-21961. [CrossRef] [Google Scholar]
  8. P. Ferrari et al., “On the Use of LoRaWAN and Cloud Platforms for Diversification of Mobility-as-a-Service Infrastructure in Smart City Scenarios,” in IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-9, 2022, Art no. 5501109, doi: 10.1109/TIM.2022.3144736. [CrossRef] [Google Scholar]
  9. Lasi, Heiner, et al. “Industry 4.0.” Business & information systems engineering 6.4 (2014). [Google Scholar]
  10. M. Aazam, S. Zeadally and K. A. Harras, “Deploying Fog Computing in Industrial Internet of Things and Industry 4.0,” in IEEE Transactions on Industrial Informatics, vol. 14, no. 10, pp. 4674-4682, Oct. 2018, doi: 10.1109/TII.2018.2855198. [CrossRef] [Google Scholar]
  11. C. -C. Lin and J. -W. Yang, “Cost-Efficient Deployment of Fog Computing Systems at Logistics Centers in Industry 4.0,” in IEEE Transactions on Industrial Informatics, vol. 14, no. 10, pp. 4603-4611, Oct. 2018, doi: 10.1109/TII.2018.2827920. [CrossRef] [Google Scholar]
  12. Peralta, Goiuri, et al. “Fog computing based efficient IoT scheme for the Industry 4.0.” 2017 IEEE international workshop of electronics, control, measurement, signals and their application to mechatronics (ECMSM). IEEE, 2017. [Google Scholar]
  13. Kilkki, Kalevi, et al. “A disruption framework.” Technological Forecasting and Social Change 129 (2018). [Google Scholar]
  14. Sejdovic, Suad, and Natalja Kleiner. “Proactive and dynamic event-driven disruption management in the manufacturing domain.” 2016 IEEE 14th International Conference on Industrial Informatics (INDIN). IEEE, 2016. [Google Scholar]
  15. Modarresi, Amir, and James PG Sterbenz. “Toward resilient networks with fog computing”, IEEE, 2017. [Google Scholar]
  16. Sterbenz, James PG, et al. “Redundancy, diversity, and connectivity to achieve multilevel network resilience, survivability, and disruption tolerance invited paper”, Telecommunication Systems 56.1 (2014). [Google Scholar]
  17. Madhu Bhukya, et al. “Intrusion detection models for IOT networks via deep learning approaches.” Measurement: Sensors 25 (2023): 100641. [CrossRef] [Google Scholar]
  18. J. P. Sterbenz, D. Hutchison, E. K. C, etinkaya, A. Jabbar, J. P. Rohrer, M. Scholler, and P. Smith, “Resilience and survivability in commu- ¨nication networks: Strategies, principles, and survey of disciplines,” Computer Networks, vol. 54, no. 8, pp. 1245–1265, 2010. [CrossRef] [Google Scholar]
  19. Zanella, N. Bui, A. Castellani, L. Vangelista, and M. Zorzi, “Internetof things for smart cities”, IEEE Internet of Things Journal, vol. 1,pp. 22–32, Feb 2014. [CrossRef] [Google Scholar]
  20. D. Clark, K. Sollins, J. Wroclawski, D. Katabi, J. Kulik, X. Yang,R. Braden, T. Faber, A. Falk, V. Pingali, M. Handley, and N. Chiappa, “New arch: Future generation Internet architecture”, technical report,DARPA, MIT, ISI, February 2003. [Google Scholar]
  21. Madhu, Bhukya, and M. Venu Gopalachari. “Classification of the Severity of Attacks on Internet of Things Networks.” Sentiment Analysis and Deep Learning: Proceedings of ICSADL 2022. Singapore: Springer Nature Singapore, 2023. 411-424. [Google Scholar]
  22. Al-Fuqaha, Ala, et al. “Internet of things: A survey on enabling technologies, protocols, and applications”, IEEE communications surveys & tutorials 17.4 (2015). [Google Scholar]
  23. Reinike, William J. “The US Financial System as a Network: Insights and Implications for Hybrid Warfare”, Naval Postgraduate School, 2020. [Google Scholar]
  24. Feldman, Zohar, et al. “Proactive event processing in action: a case study on the proactive management of transport processes (industry article)”, Proceedings of the 7th ACM international conference on Distributed event-based systems. 2013. [Google Scholar]
  25. Metzger, Andreas, Rod Franklin, and Yagil Engel. “Predictive monitoring of heterogeneous service-oriented business networks: The transport and logistics case”, 2012 Annual SRII Global Conference. IEEE, 2012. [Google Scholar]
  26. Yan, Jianzhuo, et al. “Rainfall forecast model based on the tabnet model”, Water 13.9 (2021). [Google Scholar]
  27. Engel, Yagil, and Opher Etzion. “Towards proactive event-driven computing”, Proceedings of the 5th ACM international conference on Distributed event-based system. 2011. [Google Scholar]
  28. Kaluža, Boštjan, et al. “An agent-based approach to care in independent living”, International joint conference on ambient intelligence. Springer, Berlin, Heidelberg, 2010. [Google Scholar]
  29. Brzezinski, Jack R., and George J. Knafl. “Logistic regression modeling for context-based classification”, Proceedings. Tenth International Workshop on Database and Expert Systems Applications. DEXA 99. IEEE, 1999. [Google Scholar]

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