Trust-Based Communication Systems for Internet of Things Applications. Группа авторов
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and Security, Leshan, 2013, pp. 663-667, doi: 10.1109/CIS.2013.145.
3. Deebak, B. D., and Fadi Al-Turjman. “A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks.” Ad Hoc Networks 97 (2020): 102022.
4. Santos-González, Iván, Alexandra Rivero-García, Mike Burmester, Jorge Munilla, and Pino Caballero-Gil. “Secure lightweight password authenticated key exchange for heterogeneous wireless sensor networks.” Information Systems 88 (2020): 101423.
5. Wang, G., B. Lee, J. Ahn, and G. Cho. “A UAV-assisted CH election framework for secure data collection in wireless sensor networks.” Future Generation Computer Systems 102 (2020): 152-162.
6. Jha, Suresh Kumar, Niranjan Panigrahi, and Anil Gupta. “Security Threats for Time Synchronization Protocols in the Internet of Things.” In Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm, pp. 495-517. Springer, Cham, 2020.
7. Tewari, Aakanksha, and Brij B. Gupta. “Secure Timestamp-Based Mutual Authentication Protocol for IoT Devices Using RFID Tags.” International Journal on Semantic Web and Information Systems (IJSWIS) 16, no. 3 (2020): 20-34.
8. Julie, E. Golden, and Y. Harold Robinson. “Security and Privacy Issues in Wireless Sensor Networks.” In IoT and Analytics for Agriculture, pp. 187-210. Springer, Singapore, 2020.
9. Siddiqui, Shams Tabrez, Shadab Alam, Riaz Ahmad, and Mohammed Shuaib. “Security Threats, Attacks, and Possible Countermeasures in Internet of Things.” In Advances in Data and Information Sciences, pp. 35-46. Springer, Singapore, 2020.
10. Das, Santosh Kumar, Sourav Samanta, Nilanjan Dey, and Rajesh Kumar. Design Frameworks for Wireless Networks. Springer, 2020. Mahdavinejad, Mohammad & Rezvan, Mohammadreza & Barekatain, Mohammadamin & Adibi, Peyman & Barnaghi, Payam & Sheth, Amit. “Machine learning for Internet of Things data analysis: A survey. Digital Communications and Networks”. (2017). 10.1016/j.dcan.2017.10.002.
11. Ullo, Silvia Liberata, and G. R. Sinha. “Advances in Smart Environment Monitoring Systems Using IoT and Sensors.” Sensors 20.11 (2020): 3113.
12. Qolomany, Basheer, et al. “Leveraging machine learning and big data for smart buildings: A comprehensive survey.” IEEE Access 7 (2019): 90316-90356.
13. Desarkar, Anindita, and Ajanta Das. “Big-Data Analytics, Machine Learning Algorithms and Scalable/Parallel/Distributed Algorithms.” Internet of Things and Big Data Technologies for Next Generation Healthcare. Springer, Cham, 2017. 159-197.
14. Tam, Wai Cheong, Thomas Cleary, and Eugene Yujun Fu. “Generating Synthetic Sensor Data to Facilitate Machine Learning Paradigm for Prediction of Building Fire Hazard.” Suppression, Detection and Signaling Research and Applications Symposium (2019 SUPDET). 2019.
15. Adi, Erwin, et al. “Machine learning and data analytics for the IoT.” Neural Computing and Applications (2020): 1-29.
16. Yigitcanlar, Tan, et al. “Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature.” Energies 13.6 (2020): 1473.
17. Yaqoob, Ibrar, et al. “Internet of things forensics: Recent advances, taxonomy, requirements, and open challenges.” Future Generation Computer Systems 92 (2019): 265-275.
18. A. Sheth, Transforming big data into smart data: Deriving value via harnessing volume, variety, and velocity using semantic techniques and technologies, in: Data Engineering (ICDE), 2014 IEEE 30th International Conference on, IEEE, 2014, pp. 2–2.
19. Shinde, D.; Siddiqui, N. IOT Based Environment change Monitoring Controlling in Greenhouse using WSN. In Proceedings of the 2018 International Conference on Information, Communication, Engineering and Technology (ICICET 2018), Pune, India, 29–31 August 2018; pp. 1–5.
20. Pathak, A.; Uddin, M.A.; Jainal Abedin, M.; Andersson, K.; Mustafa, R.; Hossain, M.S. IoT based smart system to support agricultural parameters: A Case Study. Procedia Comput. Sci. 2019,155,648–653.
21. Hosseini, M.; McNairn, H.; Mitchell, S.; Davidson, A.; Robertson, L.D. Comparison of Machine Learning Algorithms and Water Cloud Model for Leaf Area Index Estimation Over Corn Fields. In Proceedings of the IGARSS 2019 - 2019 IEEE Int. Geosci. Remote Sens. Symp, Yokohama, Japan, 28 July–2 August 2019; pp. 6267–6270.
22. Fazai, R.; Mansouri, M.; Abodayeh, K.; Puig, V.; Selmi, M.; Nounou, H.; Nounou, M. Multiscale Gaussian Process Regression-Based GLRT for Water Quality Monitoring. Conf. Control Fault Toler. Syst. Sys. Tol. 2019, 44–49. [CrossRef].
23. Dimitriadis, S.; Goumopoulos, C. Applying machine learning to extract new knowledge in precision agriculture applications. In Proceedings of the 12th Pan-Hellenic Conference on Informatics Doryssa Seaside Resort (PCI 2008), Samos Island, Greece, 28–30 August 2008; pp. 100–104.
24. Y. Wang, W. Lin, T. Zhang, and Y. Ma, “Research on application and security protection of internet of things in smart grid,” pp. 1–5, Dec 2012.
25. A.-M. Rahmani, N. Thanigaivelan, T. N. Gia, J. Granados, B. Negash, P. Liljeberg, and H. Tenhunen, “Smart e-health gateway: Bringing intelligence to internet-of-things based ubiquitous healthcare systems,” in Consumer Communications and Networking Conference (CCNC), 2015 12th Annual IEEE, Jan 2015, pp. 826–834.
26. Jain, B.; Brar, G.; Malhotra, J.; Rani, S.; Ahmed, S.H. A cross layer protocol for traffic management in Social Internet of Vehicles. Future Gen. Comput. Syst. 2018, 82, 707–714. [CrossRef]
27. Ghosh, A.; Chatterjee, T.; Samanta, S.; Aich, J.; Roy, S. Distracted Driving: A Novel Approach towards Accident Prevention. Adv. Comput. Sci. Technol. 2017, 10, 2693–2705.
28. Sharifinejad, Maedeh, Ali Dorri, and Javad Rezazadeh. “BIS-A Blockchainbased Solution for the Insurance Industry in Smart Cities.” arXiv preprint arXiv:2001.05273 (2020).
29. C. Cecchinel, M. Jimenez, S. Mosser, M. Riveill, An architecture to support the collection of big data in the internet of things, in: 2014 IEEE World Congress on Services, IEEE, 2014, pp. 442–449.
30. A. Sheth, Internet of things to smart iot through semantic, cognitive, and perceptual computing, IEEE Intelligent Systems 31 (2) (2016) 108–112.
31. S. Bin, L. Yuan, W. Xiaoyi, Research on data mining models for the internet of things, in: 2010 International Conference on Image Analysis and Signal Processing, IEEE, 2010, pp. 127–132.
32. F. Chen, P. Deng, J. Wan, D. Zhang, A. V. Vasilakos, X. Rong, Data mining for the internet of things: literature review and challenges, International Journal of Distributed Sensor Networks 2015 (2015) 12.
33. C.-W. Tsai, C.-F. Lai, M.-C. Chiang, L. T. Yang, Data mining for internet of things: a survey, IEEE Communications Surveys & Tutorials 16 (1) (2014) 77–97
34. Fadi, AL-Turjman, and Deebak Bakkiam David. “Seamless Authentication: For IoT-Big Data Technologies in Smart Industrial Application Systems.” IEEE Transactions on Industrial Informatics (2020).
35. Pääkkönen, Pekka, and Daniel Pakkala. “Extending reference architecture of big data systems towards machine learning in edge computing environments.” Journal of Big Data 7 (2020): 1-29.
36. Neelakandan, S & Paulraj, D 2020, ‘A gradient boosted decision tree-based sentiment classification of twitter data’, International Journal of Wavelets, Multiresolution and Information Processing, vol. 18, no. 4, pp. 205027 1-21. DOI: https://doi.org/10.1142/S0219691320500277
37. Neelakandan, S & Paulraj, D 2020, ‘An Automated Exploring And Learning Model For Data Prediction Using Balanced CA-Svm’, Journal of Ambient Intelligence and Humanized Computing, Vol.12, no.5, April 2020 , DOI: https://doi.org/10.1007/s12652-020-01937-9
38. Neelakandan, S, Annamalai, R., Rayen,