Abstract
Trustworthiness of edge routers and clients plays a significant role in a cloud environment for ensuring reliable packet delivery. Trust of clients depends on the level of cooperation attributed by them for ensuring seamless service and on the support rendered by them for the sake of their neighbouring clients towards the core objective of reliable data dissemination. The level of collaboration between clients is highly influenced by distributed denial of service (DDoS) attacks as they directly influence the performance of cloud computing environment by preventing them from involving in normal data transactions that could result in reduced throughput and packet delivery rate. A mean availability parameter-based DDoS detection mechanism (MAPDDM) is contributed for handling the impacts induced by DDoS towards the dynamic clients of the subnet. The performance of MAPDDM is analysed by varying the size of subnets and number of attackers under the dynamic influence of varying traffic request using CloudSim. The simulation results infer that MAPDDM is phenomenal in sustaining the trust value of clients to a maximum of 82% even when the amount of traffic is varied.
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References
Kim SS, Reddy ALN (2008) Statistical techniques for detecting traffic anomalies through packet header data. IEEE/ACM Trans Netw 16:562–575
Lopez R, Onate E (2006) A variational formulation for the multilayer perceptron. In: Proceeding of artificial neural networks—ICANN 2006, Lecture Notes in Computer Science, Athens, pp 159–168
Modi CN, Patel DR, Patel A, Rajarajan M (2012) Integrating signature Apriori based network intrusion detection system (NIDS) in cloud computing. Procedia Technol 6:905–912
Lo C-H, Ansari N (2013) CONSUMER: A novel hybrid intrusion detection system for distribution networks in smart grid. IEEE Trans Emerg Topics Comput 1:33–44
Li M, Li M (2010) An adaptive approach for defending against DDoS attacks. Math Probl Eng 66:1137–1151
Janczewski LJ (2001) Handling distributed denial-of-service attacks. Inf Secur Tech Rep 6:37–44
Chen Y, Hwang K (2006) Collaborative detection and filtering of shrew DDoS attacks using spectral analysis. J Parallel Distrib Comput 66:1137–1151
Du P, Nakao A (2010) OverCourt: DDoS mitigation through credit-based traffic segregation and path migration. Comput Commun 33:2164–2175
Varalakshmi P, Selvi ST (2013) Thwarting DDoS attacks in grid using information divergence. Future Gener Comput Syst 29:429–441
Nesmachnow S, Iturriaga S, Dorronsoro B (2015) Efficient heuristics for profit optimization of virtual cloud brokers. IEEE Comput Intell Mag 10:33–43
Raj Kumar PA, Selvakumar S (2011) Distributed denial of service attack detection using an ensemble of neural classifier. Comput Commun 34:1328–1341
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Amuthan, A., Harikrishna, P. (2019). Mean Availability Parameter-Based DDoS Detection Mechanism for Cloud Computing Environments. In: Zungeru, A., Subashini, S., Vetrivelan, P. (eds) Wireless Communication Networks and Internet of Things. Lecture Notes in Electrical Engineering, vol 493. Springer, Singapore. https://doi.org/10.1007/978-981-10-8663-2_12
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DOI: https://doi.org/10.1007/978-981-10-8663-2_12
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