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55 articles for “IDS”

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Research ArticleOpen accessIn the abstractAutoencoder-Based Intrusion Detection for ARP Poisoning in SDN ControllersKago Seemela, Banyatsang Mphago, Thabo Semong, Phephisa MethulaAddress Resolution Protocol (ARP) poisoning is still a critical control plane attack in Software Defined Networks (SDNs), and spoofing of ARP mappings can trick SDNs controller and accomplish man in the middle, eavesdropping and denial of service attacks. Current SDN intrusion detection systems of ARP attacks rely on supervised learning and labelled attack data which is rather expensive and not … …Journal of Computer Science, Vol. 22, Issue 7 · 21 Jul 2026 · 869 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Distillation GAN Model for Network Intrusion DetectionChandrakala C B, Sai Sreevall, Raghudathesh G PThis study presents a distillation-based Generative Adversarial Network (GAN) model designed for intrusion detection in network systems. A Teacher-Student architecture is proposed, in which a single teacher generator is utilized to train both the teacher discriminator and the student discriminator. The model was trained to identify anomalies present in network traffic intrusions by tuning the min-max loss function in GANs. … …Journal of Computer Science, Vol. 22, Issue 2 · 5 Mar 2026 · 1,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,993 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Regularization Mechanism for Combating Class Imbalance Problem in Intrusion Detection System for Defending DDoS Attack in SDNNarender M, Yuvaraju B NIntegration of deep learning into Intrusion Detection Systems (IDS) for Software Defined Networking (SDN) is an emerging field of research. Most of the datasets used to build IDS are highly imbalanced, especially in the case of DDoS attacks, which account for a larger percentage of malicious samples than normal traffic. As a result of a class imbalance, the classification result … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,659 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion DetectionOlujimi Daniel Alao, Sheriff Alimi, Shade Oluwakemi Kuyoro et al.NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or rejecting the network packets. In this study,the aim is the implementation of NIDS with improved performance using anensemble of Support Vector Machines (SVMs) and the Gaussian Mixture Model(GMM). Four SVMs with Radial Basis Function (RBF), … …Journal of Computer Science, Vol. 18, Issue 9 · 21 Sep 2022 · 6,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Detection and Mitigation of Rushing Attacks in VANETs Using RAID: A Novel Intrusion Detection SystemVamshi Krishna Kapu, Ganesh Reddy KarriThe vehicle manufacturing hub has evolved over the last decade with the emergence of self-driving vehicles and human-driven vehicles that use the concept of Artificial Intelligence (AI). Vehicular Ad Hoc Network (VANET) is a subset of Mobile Ad Hoc Network (MANET) that allows vehicles to communicate with one another and the Road Side Unit (RSU). VANET has been a game … …Journal of Computer Science, Vol. 19, Issue 9 · 26 Aug 2023 · 5,746 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomatic Digitization of Engineering Diagrams using Intelligent AlgorithmsPremanand Ghadekar, Shaunak Joshi, Debabrata Swain et al.At present usage of computational intelligence became the ultimate need of the heavy engineering industries. Digitization can be achieved in these sectors by scanning the hard copy images. When older documents are digitized are not of very high fidelity and therefore the accuracy, reliability of the estimates of components such as equipment and materials after digitization are remarkably low since … …Journal of Computer Science, Vol. 17, Issue 9 · 28 Sep 2021 · 7,058 accessesView PDFCite
Review ArticleOpen accessIn the abstractToward an Online DoS/DDoS Classification: An Empirical Study for Network Intrusion Detection SystemsTran Hoang Hai, Nguyen Trong Khiem, Nguyen Huu PhucIn recent years, Distributed Denial of Services (DDoS) attacks have caused significant losses to industry and government due to an increasing number of devices connected to the Internet. These devices use services-over-Internet more frequently with services characterized and provided seamlessly by 5G, Cloud and Edge Computing. According to Cisco Annual Internet Report, the frequency of DoS/DDoS attacks has increased more … …Journal of Computer Science, Vol. 17, Issue 3 · 30 Mar 2021 · 6,972 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparison Study between Different Sampling Strategies for Intrusion Detection System of Active Learning ModelGhofran Mohammad Alqaralleh, Mohammad Aref Alshraideh, Ali AlrodanActive learning aims to train an accurate model with minimum cost by labeling the most informative instances without compromising the model performance. So, choosing an efficient criterion for instance selection is the most important step. Sampling stage is the main issue in active learning for many problems such as intrusion detection system. There are many methods for sampling stage to … …Journal of Computer Science, Vol. 14, Issue 8 · 26 Aug 2018 · 8,183 accessesView PDFCite
Research ArticleOpen accessIn the abstractResearch Proposal: An Intrusion Detection System Alert Reduction and Assessment Framework Based on Data MiningKarim Al-Saedi, Selvakumar Manickam, Sureswaran Ramadass et al.The Intrusion Detection System (IDS) generates huge amounts of alerts that are mostly false positives. The abundance of false positive alerts makes it difficult for the security analyst to identify successful attacks and to take remedial actions. Such alerts to have not been classified in accordance with their degree of threats. They further need to be processed to ascertain the … …Journal of Computer Science, Vol. 9, Issue 4 · 8 May 2013 · 7,709 accessesView PDFCite