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Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif 《计算机系统科学与工程》2023,47(1):553-574
Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 1038 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 a massive 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 Pollination Algorithm (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 BFPA-FA 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-FA is effective in the ICMPv6 DDoS attacks via IDS. 相似文献
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Alyasseri Zaid Abdi Alkareem Khader Ahamad Tajudin Al-Betar Mohammed Azmi Yang Xin-She Mohammed Mazin Abed Abdulkareem Karrar Hameed Kadry Seifedine Razzak Imran 《Neural computing & applications》2023,35(11):7943-7962
Neural Computing and Applications - The electroencephalogram (EEG) signal denoising problem has been considered a challenging task because of several artifact noises, such as eye blinking, eye... 相似文献
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Nayef Bahera H. Abdullah Siti Norul Huda Sheikh Sulaiman Rossilawati Alyasseri Zaid Abdi Alkareem 《Multimedia Tools and Applications》2022,81(2):2065-2094
Multimedia Tools and Applications - Object classification, such as handwritten Arabic character recognition, is a computer vision application. Deep learning techniques such as convolutional neural... 相似文献
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Alyasseri Zaid Abdi Alkareem Alomari Osama Ahmad Al-Betar Mohammed Azmi Makhadmeh Sharif Naser Doush Iyad Abu Awadallah Mohammed A. Abasi Ammar Kamal Elnagar Ashraf 《Neural computing & applications》2022,34(19):16387-16422
Neural Computing and Applications - Bat-inspired algorithm (BA) is a robust swarm intelligence algorithm that finds success in many problem domains. The ecosystem of bat animals inspires the main... 相似文献
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Al-Betar Mohammed Azmi Alyasseri Zaid Abdi Alkareem Awadallah Mohammed A. Abu Doush Iyad 《Neural computing & applications》2021,33(10):5011-5042
Neural Computing and Applications - In this paper, a new nature-inspired human-based optimization algorithm is proposed which is called coronavirus herd immunity optimizer (CHIO). The inspiration... 相似文献
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Abasi Ammar Kamal Khader Ahamad Tajudin Al-Betar Mohammed Azmi Naim Syibrah Makhadmeh Sharif Naser Alyasseri Zaid Abdi Alkareem 《Multimedia Tools and Applications》2021,80(1):37-82
Multimedia Tools and Applications - The automatic topic extraction (TE) from scientific publications provides a very compact summary of the clusters’ contents. This often helps in locating... 相似文献
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