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31 articles for “Intrusion Detection Systems (IDS)”
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Research ArticleOpen accessIn the abstractAdvanced Hierarchical Deep Learning Approach for Intrusion Detection: Hyperparameter Tuning and Performance Evaluation on the CICIDS DatasetAjeet Singh, Azath M, Shahazad Niwazi Qurashi et al.Intrusion Detection Systems (IDS) are essential in the communication security and integrity of contemporary network architectures. This study introduces a novel advanced hierarchical deep learning model for network intrusion detection using the CICIDS dataset-2019. To improve the detection accuracy, the proposed model architecture builds several deep learning layers embedded with hyperparameters' optimization. Additional preprocessing steps, including over-sampling and min-max scaling, … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,158 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Intrusion Detection System Using RF, SVM, and DT: A Comparison-Based KDD Data SetWalaa Hassan Elashmawi, Alaa Sheta, Ahmad Al-QeremThe rapid growth of technology has brought about many advantages, but has also made networks more susceptible to security threats. Intrusion Detection Systems (IDS) play a vital role in protecting computer networks against malicious activities. Given the dynamic and constantly evolving nature of cyber threats, these systems must continuously adapt to maintain their effectiveness. Machine Learning (ML) methods have gained … …Journal of Computer Science, Vol. 21, Issue 8 · 28 Aug 2025 · 5,821 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 · 5,756 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 · 5,668 accessesView PDFCite
Review ArticleOpen accessIn the abstractGeneration Test-Cases of Attacks in Mobile Ad Hoc NetworkSara Chadli, Mohammed Saber, Abdelhak ZiyyatThe number and increasing complexity of attacks against MANETs have grown significantly in recent years. While many security proposals have been developed. However, these proposals suffer from the problems of tests and evaluations. Among these solutions, the Intrusion Detection Systems (IDS) that can act as defense mechanisms. However, this last poses serious problems for its evaluators that need classify the … …Journal of Computer Science, Vol. 12, Issue 10 · 14 Dec 2016 · 6,527 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Survey of Anomaly Detection Using Data Mining Methods for Hypertext Transfer Protocol Web ServicesMohsen Kakavand, Norwati Mustapha, Aida Mustapha et al.In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Jan 2015 · 9,256 accessesView PDFCite
Research ArticleOpen accessIn the abstractMULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTIONG. Palanivel, K. DuraiswamyWe propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 27 Jun 2014 · 6,781 accessesView PDFCite
Research ArticleOpen accessIn the abstractREVIEW CLUSTERING MECHANISMS OF DISTRIBUTED DENIAL OF SERVICE ATTACKSWesam Bhaya, Mehdi Ebady ManaaDistributed Denial of Service attacks (DDoS) overwhelm network resources with useless or harmful packets and prevent normal users from accessing these network resources. These attacks jeopardize the confidentiality, privacy and integrity of information on the internet. Since it is very difficult to set any predefined rules to correctly identify genuine network traffic, an anomaly-based Intrusion Detection System (IDS) for network … …Journal of Computer Science, Vol. 10, Issue 10 · 26 Jun 2014 · 7,643 accessesView PDFCite
Research ArticleOpen accessIn the abstractHYBRID FEATURE SELECTION ALGORITHM FOR INTRUSION DETECTION SYSTEMSeyed Reza Hasani, Zulaiha Ali Othman, Seyed Mostafa Mousavi KahakiNetwork security is a serious global concern. Usefulness Intrusion Detection Systems (IDS) are increasing incredibly in Information Security research using Soft computing techniques. In the previous researches having irrelevant and redundant features are recognized causes of increasing the processing speed of evaluating the known intrusive patterns. In addition, an efficient feature selection method eliminates dimension of data and reduce redundancy … …Journal of Computer Science, Vol. 10, Issue 6 · 31 Jan 2014 · 7,357 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 · 7,712 accessesView PDFCite