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85 results for “Intrusion detection”
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Research ArticleOpen accessPhrase in the titleINTRUSION DETECTION IN MOBILE AD HOC NETWORK USING SECURE ROUTING FOR ATTACKER IDENTIFICATION PROTOCOLS. Gopalakrishnan, P. GaneshkumarIn past few decades, the migration of communication takes place from wired networks to wireless networks because of its mobility and scalability and Mobile Ad hoc Network (MANET) is a unique and significant application in recent years which does not necessitates any pre-existing network infrastructure. Each node can act as both transmitters as well as receivers that are communicating with … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 29 May 2014 · 6,715 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnsemble Learning for Proactive Detection of Network-Intrusion-Based Insurance FraudBenjamin Asubam Weyori, Selorm Kofi Tagbo et al.We propose an ensemble learning pipeline that proactively integrates Stacking Feature Embedding (SFE) with Principal Component Analysis (PCA) and tree-based ensembles to proactively detect insurance fraud originating from network intrusions. The main contributions are: (1) the novel integration of SFE-PCA as a meta-feature construction step for tabular network flow data; (2) a sensitivity analysis that justifies PCA reduction ratios used … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 935 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
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 keywordsEFFECTIVE BLACK HOLE ATTACKS IN MANETSRaja Azlina Raja Mahmood, Zurina Mohd Hanapi, Sazlinah Hasan, AsadIqbal KhanBlack hole or packet drop attack is a denial of service attack on routing protocols in which malicious nodes fabricate routing information, attract packets routed through them and then deliberately drop these packets. Most of the black hole attack simulations are performed by constantly fabricating routing information and thus consistently attracting packets to them, which can be easily detected by … …Journal of Computer Science, Vol. 9, Issue 12 · 25 Nov 2013 · 6,932 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 keywordsBehaviour Based Worm Detection and Signature AutomationMohammed Anbar, Selvakumar Manickam, Al-Samarraie Hosam et al.Problem statement: A worm is a malicious piece of code that self-propagates, often via network connections, to exploit security flaws in computers connected through the network. In general, worms do not need any human intervention to propagate and are considered a real threat to network assets and the properties of organizations. An Intrusion Detection Systems (IDSs) are employed to detect … …Journal of Computer Science, Vol. 7, Issue 11 · 6 Sep 2011 · 6,895 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparative Power Analysis of Precomputation Based Content Addressable MemoryM. Arun, A. KrishnanProblem statement: In this study we discus about Signature Detection Technique (SDT) used in Network Intrusion Detection System (NIDS). Design of SDT using Content Addressable Memory (CAM) is discussed. Approach: Two novel architectures, XOR and ones count based Pre computation CAM architectures are proposed and implemented in third party back end tool with 0.18 mm technology, power consumptions are compared. … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 6,598 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Approach Based on Federated Learning for the Identification of Man in the Middle Attacks in IOT Networks Using BlockchainSarumathi S, Juliet Johny, Minal Khandare et al.Federated Learning (FL) enables cooperative model training across dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. In the Internet of Things (IoT), federated learning enables cooperative model training among dispersed edge devices while protecting data privacy and providing localized insights without the need for centralized data aggregation. Nevertheless, Federated Learning’s … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,613 accessesView PDFCite