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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm
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作者 Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam +6 位作者 Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif 《Computer Systems Science & Engineering》 SCIE EI 2023年第10期553-574,共22页
Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the network.IPv6 has introduced new features like Neighbour Discovery Protocol(NDP)and A... Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the network.IPv6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration Scheme.IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications.Therefore,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of features.This paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential features.Moreover,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios.The results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)features.The proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS. 展开更多
关键词 IPv6 ICMPV6 DDoS feature selection flower pollination algorithm anomaly detection
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Visual tracking using discriminative representation with l2 regularization
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作者 Haijun WANG Hongjuan GE 《Frontiers of Computer Science》 SCIE EI CSCD 2019年第1期199-211,共13页
In this paper,we propose a novel visual tracking method using a discriminative representation under a Bayesian framework.First,we exploit the histogram of gradient (HOG)to generate the texture features of the target t... In this paper,we propose a novel visual tracking method using a discriminative representation under a Bayesian framework.First,we exploit the histogram of gradient (HOG)to generate the texture features of the target templates and candidates.Second,we introduce a novel discriminative representation and l2-regularized least squares method to solve the proposed representation model.The proposed model has a closed-form solution and very high computational efficiency.Third,a novel likelihood function and an update scheme considering the occlusion factor are adopted to improve the tracking performance of our proposed method. Both qualitative and quantitative evaluations on 15 challenging video sequences demonstrate that our method can achieve more robust tracking results in terms of the overlap rate and center location error. 展开更多
关键词 visual tracking discriminative REPRESENTATION BAYESIAN framework closed-form solution
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