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18 results for “Anomaly Detection Algorithm”
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Research ArticleOpen accessPhrase in the titleAnomaly Detection Algorithms for Streaming Data: Performance ComparisonZirije HasaniToday’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming … …Journal of Computer Science, Vol. 16, Issue 7 · 18 Jul 2020 · 7,288 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA BIO-SURVEILLANCE SYSTEM USING EFFICIENT ALGORITHM FOR INFORMATION SHARING APPLICATIONSShobhanjaly P. Nair, K. Silambarasan, N. Bindhu, R. SrinivasanBio-Surveillance represents a health information system for public that stores and integrates health related information and data across a variety of data. Bio-surveillance strategies are projected for detection of disease outbreaks from existing diagnostic data, but their performance is typically not understandable. The focus of the paper is to develop a bio-surveillance system which can serve the aim of biosurveillance … …Journal of Computer Science, Vol. 10, Issue 7 · 17 Jun 2014 · 7,038 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHandling 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 accessIn the keywordsHYBRID 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 · 7,350 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDETECTING ABNORMAL BEHAVIOR IN SOCIAL NETWORK WEBSITES BY USING A PROCESS MINING TECHNIQUEMahdi Sahlabadi, Ravie Chandren Muniyandi, Zarina ShukurDetecting abnormal user activity in social network websites could prevent from cyber-crime occurrence. The previous research focused on data mining while this research is based on user behavior process. In this study, the first step is defining a normal user behavioral pattern and the second step is detecting abnormal behavior. These two steps are applied on a case study that … …Journal of Computer Science, Vol. 10, Issue 3 · 22 Nov 2013 · 7,916 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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
Research ArticleOpen accessIn the abstractDetecting 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 abstractEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,466 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,234 accessesView PDFCite