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72 results for “Intrusion Detection System”
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Research ArticleOpen accessIn the keywordsAutoencoder-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 keywordsAn Intrusion Detection Framework for MEC-Enabled IoT NetworksRofaida Tawfik, Abdelfattah Hegazy, Hesham Dahshan, Ahmed Gaber AbuabdallahMobile Edge Computing (MEC) has emerged as a promising paradigm for supporting latency-sensitive Internet of Things (IoT) applications by bringing computational resources closer to data sources. However, the distributed nature of MEC environments increases exposure to network-based security threats, particularly network intrusions that can impact both system reliability and task offloading efficiency. This paper proposes a security-aware framework that integrates … …Journal of Computer Science, Vol. 22, Issue 4 · 1 Apr 2026 · 1,921 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdvanced 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 · 2,148 accessesView PDFCite
Research ArticleOpen accessIn the keywordsGenerating IoT Specific Anomaly Datasets Using Cooja Simulator (Contiki-OS) and Performance Evaluation of Deep Learning Model Coupled with Aquila OptimizerVandana Choudhary, Sarvesh Tanwar, Tanupriya ChoudhuryIn recent times, the massive expansion of the Internet of Things (IoT) has transformed various facets of everyday life and industries. The compelling cause behind the widespread adoption of IoT is the increasing availability of affordable, compact, and energy-efficient computing devices. While these devices offer significant benefits, they also raise substantial security and privacy challenges. Consequently, safeguarding IoT networks and … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 6,850 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRandom Forests for Online Intrusion Detection in Computer NetworksHeitor Scalco Neto, Wilian Soares Lacerda, Rafael Verão FrançozoThis study proposes a methodology to build an Online Network Intrusion Detection System by using the Computational Intelligence technique called Random Forests and an API to preprocess the network packets. The experiments were carried out from two network traffic databases: The ISCX (i); and a test database (ii) created with the proposed API in our own network environment. The results … …Journal of Computer Science, Vol. 17, Issue 10 · 19 Oct 2021 · 6,955 accessesView PDFCite
Review ArticleOpen accessIn the keywordsGeneration 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 · 6,522 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA 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 · 9,252 accessesView PDFCite
Research ArticleOpen accessIn the keywordsWIRELESS MESH NETWORK CROSS-LAYER INTRUSION DETECTIONF. S. Al-Anzi, S. KhanIntrusion is something which is unsolicited activity and which might be used to interrupt the functions of wireless network. If we talk about wireless networks, having centralized monitoring policy; therefore it is very much easy to detect and eliminate intrusions efficiently. But when we look forward to wireless scenario, especially in the multi hop wireless network, intrusion activities are more … …Journal of Computer Science, Vol. 10, Issue 12 · 23 Dec 2014 · 8,278 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe use of Random Forest Classification and K-means Clustering Algorithm for Detecting Time Stamped Signatures in the Active NetworksKamalanaban Ethala, R. Shesadri, N. G. RenganathanIn day to day information security infrastructure, intrusion detection is indispensible. Signature based intrusion detection system mechanisms are often available in detecting many types of attacks. But this mechanism alone is not sufficient in many cases. Another intrusion detection method viz K-means is employed for clustering and classifying the unlabelled data. IDS is a special embedded device or relied software … …Journal of Computer Science, Vol. 9, Issue 7 · 18 Jun 2013 · 7,496 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImproving the Attack Detection Rate in Network Intrusion Detection using Adaboost AlgorithmP. Natesan, P. Balasubramanie, G. GowrisonProblem statement: Nowadays, the Internet plays an important role in communication between people. To ensure a secure communication between two parties, we need a security system to detect the attacks very effectively. Network intrusion detection serves as a major system to work with other security system to protect the computer networks. Approach: In this article, an Adaboost algorithm for network … …Journal of Computer Science, Vol. 8, Issue 7 · 16 May 2012 · 7,461 accessesView PDFCite