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44 results for “Anomaly Detection”
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Research ArticleOpen accessPhrase in the titleA Novel Hybrid Method for Network Anomaly Detection Based on Traffic Prediction and Change Point DetectionMouhammd AlkasassbehIn recent years, computer networks have become more and more advanced in terms of size, applications, complexity and level of heterogeneity. Moreover, availability and performance are important issues for end users. New types of cyber-attacks that can affect and damage network performance and availability are constantly emerging and some threats, such as Distributed Denial of Service (DDoS) attacks, can be … …Journal of Computer Science, Vol. 14, Issue 2 · 3 Jan 2018 · 8,404 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAnomaly Detection in Electroencephalogram Signals Using Unconstrained Minimum Average Correlation Energy FilterAini Hussain, Rosniwati Ghafar, Salina Abdul Samad, Nooritawati Md TahirProblem statement: Electroencepharogram (EEG) is an extremely complex signal with very low signal to noise ratio and these attributed to difficulty in analyzing the signal. Hence for detecting abnormal segment, a distinctive method is required to train the technologist to distinguish the anomalous in EEG data. The objective of this study was to create a framework to analyze EEG signals … …Journal of Computer Science, Vol. 5, Issue 7 · 31 Jul 2009 · 7,326 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleIssues and Challenges in Anomaly Intrusion Detection for HTTP Web ServicesMohsen Kakavand, Norwati Mustapha, Aida Mustapha et al.In recent years, the development of Web-based applications has made possible novel online activities, such as banking and electronic shopping. This implies significant use of the Hypertext Transfer Protocol (HTTP) as the standard communication protocol enabler for Web services. Due to this role, HTTP has become an essential middle target of bound attacks for intruders. This paper is set to … …Journal of Computer Science, Vol. 11, Issue 11 · 12 Jan 2016 · 7,566 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHandling Web and Database Requests Using Fuzzy Rules for Anomaly Intrusion DetectionSelvamani Kadirvelu, Kannan ArputharajProblem statement: It is necessary to propose suitable detection and prevention mechanisms to provide security for the information contents used by the web application. Many prevention mechanisms which are currently available are not able to classify anomalous, random and normal request. This leads to the problem of false positives which is classifying a normal request as anomalous and denying access … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,305 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEmbedded Software Platform Used for Detection and Mitigation of a MAC Anomaly in IEEE 802.11n NetworksArgemiro Bevilacqua, Vitor Chaves de Oliveira, Gunnar Bedicks Jr. et al.IEEE 802.11 standard is largely used anywhere as a cheap way to access internet, but the majority of devices used does not provide a standard way to manage them. Mobile stations competing for access point may causes a general wireless network failure, known as the ''MAC Anomaly''. It is presented here an access point with modified firmware, that monitors wireless … …American Journal of Applied Sciences, Vol. 12, Issue 12 · 21 Nov 2015 · 6,509 accessesView PDFCite
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 keywordsDetecting Anomalies in IoT Using Intuitionistic Fuzzy Clustering AlgorithmsVijo Arul Selvi M., Fehmin Nadira Laskar, Fokrul Alom Mazarbhuiya et al.Intuitionistic Fuzzy Sets (IFS) are convenient ways to represent the vagueness and uncertainty inherent in any dataset. There are many uses of these. One such use is the Fuzzy C-Means (FCM) algorithm, which clusters the data objects into a pre-assigned (c) number of fuzzy clusters, which has been adopted in many fields, namely, pattern classification, anomaly detection, fraud identification, etc. … …Journal of Computer Science, Vol. 22, Issue 2 · 2 Mar 2026 · 1,600 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDifferSqueezeNet: A Leaner Defect Detection ModelJose Joao Manrique Franco, Marcelo RudekIn the industrial environment, the inherent limitations of manual inspection have caused the ascent of automated computer vision systems that aim to match or surpass human performance. In this context, the artificial intelligence field has been interested in defect detection with the creation of many machine learning techniques, focusing on Unsupervised and Semi-supervised learning methods. Since most of these methods … …Journal of Computer Science, Vol. 21, Issue 3 · 4 Feb 2025 · 5,727 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMULTI 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 · 6,776 accessesView PDFCite