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Trust based blockchain security management in edge computing | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، شماره 2، بهمن 2021، صفحه 2189-2197 اصل مقاله (2.86 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5368 | ||
| نویسندگان | ||
| D. Jayakumar* 1؛ K. Santhosh Kumar2؛ R. Sathya3 | ||
| 1Department of CSE, IFET College of Engineering, Villupuram, India | ||
| 2Department of IT, Annamalai University, Chidambaram, India | ||
| 3Department of CSE, Annamalai University, Chidambaram, India | ||
| تاریخ دریافت: 28 بهمن 1399، تاریخ بازنگری: 14 اسفند 1399، تاریخ پذیرش: 22 فروردین 1400 | ||
| چکیده | ||
| In this paper, an analysis is conducted on the data transmitted through the edge computing technique. The research creates a trust model that establishes direct, indirect, and mutual trust between the source and destination blocks when data is sent. That is, the study integrated blockchain as a model to transmit the data in a secured way through the blockchains, however, the intrusion in blockchains can be avoided based on trust based model. The simulation is conducted on various testbeds and with existing blockchain mechanisms. The findings reveal that the suggested trust-based paradigm is successful at safeguarding data sent over the edge. | ||
| کلیدواژه‌ها | ||
| MANET؛ Secured routing؛ Behavioural Trust Detection؛ Trust Degree | ||
| مراجع | ||
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[1] M.N. Ahmed, A.H. Abdullah, H. Chizari, and O. Kaiwartya, F3TM: Flooding Factor based Trust Management Framework for secure data transmission in MANETs, J. King Saud Univ. Comput. Inf. Sci. 29(3) (2017) 269–280. [2] A. Daniel, B.B. Kannan, and N.V. Kousik, Predicting Energy Demands Constructed on Ensemble of Classifiers, In: S.S. Dash, S. Das, B.K. Panigrahi (eds) Intelligent Computing and Applications, Advances in Intelligent Systems and Computing, Springer, Singapore, 2021. [3] M. Gunasekaran, and K. Premalatha, TEAP: trust-enhanced anonymous on-demand routing protocol for mobile ad hoc networks, IET Inf. Sec. 7(3) (2013) 203–211. [4] V. Laxmi, C. Lal, M.S. Gaur, and D. Mehta, JellyFish attack: Analysis, detection and countermeasure in TCPbased MANET, J. Inf. Sec. Appl. 22 (2015) 99–112. [5] N. Marchang, and R. Datta, Light-weight trust-based routing protocol for mobile ad hoc networks, IET Inf. Sec. 6(2) (2012) 77–83. [6] P.J. McNerney, and N. Zhang, A study on reservation-based adaptation for QoS in adversarial MANET environments, 8th Int. Wireless Commun. Mobile Comput. Conf. (IWCMC), IEEE (2012) 677–682. [7] Y. Natarajan, S. Kannan, and S.N. Mohanty, Survey of Various Statistical Numerical and Machine Learning Ontological Models on Infectious Disease Ontology, In: R. Satpathy, T. Choudhury, S. Satpathy, S.N. Mohanty, and X. Zhang (eds) Data Analytics in Bioinformatics, 2021. [8] S. Qazi, R. Raad, Y. Mu, and W. Susilo, Multirate DelPHI to secure multirate ad hoc networks against wormhole attacks, J. Inf. Sec. Appl. 39 (2018) 31–40. [9] R. Raja, V. Ganesan, and S.G. Dhas, Analysis on improving the response time with PIDSARSA-RAL in ClowdFlows mining platform, EAI Endors. Trans. Energy Web 5(20) (2018) 1–4. [10] S.B. Sangeetha, N.W. Blessing, and J.A. Sneha, Improving the Training Pattern in Back-Propagation Neural Networks Using Holt-Winters’ Seasonal Method and Gradient Boosting Model, In: P. Johri, J. Verma, and S. Paul (eds) Applications of Machine Learning, Algorithms for Intelligent Systems, Springer, Singapore, (2020). [11] S. Tan, X. Li, and Q. Dong, Trust based routing mechanism for securing OSLR-based MANET, Ad Hoc Networks 30(C) (2015) 84-98. [12] D.S.K. Tiruvakadu, and V. Pallapa, Confirmation of wormhole attack in MANETs using honeypot, Comput. Secur. 76 (2018) 32–49. [13] B. Wang, X. Chen, and W. Chang, A light-weight trust-based QoS routing algorithm for ad hoc networks, Perv. Mobile Comput. 13(2014) (2014) 164–180. [14] H. Xia, Z. Jia, X. Li, L. Ju, and E.H.M. Sha, Trust prediction and trust-based source routing in mobile ad hoc networks, Ad Hoc Networks 11(7) (2013) 2096–2114. [15] N. Yuvaraj, K. Srihari, G. Dhiman, K. Somasundaram, A. Sharma, S. Rajeskannan, M. Soni, G.S. Gaba, M.A. AlZain, and M. Masud, Nature-Inspired-Based approach for automated cyberbullying classification on multimedia social networking, Math. Prob. Engin. 2021 (2021) 1–12. | ||
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