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25 results for “Detection of Anomalies”
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Research ArticleOpen accessIn the abstractLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,302 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnomaly 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 abstractA Clustering based Approach for Contextual Anomaly Detection in Internet of ThingsDina ElMenshawy, Waleed Helmy, Neamat El-TaziInternet of Things (IoT) is a network which connects different communication devices with the internet to attain quick, robust and real-time information transfer and communication, achieving intelligent management. IoT is still in its infancy so it faces numerous challenges varying from data management to security concerns. Sensors generate enormous quantities of data that need to be handled efficiently to have … …Journal of Computer Science, Vol. 15, Issue 8 · 24 Aug 2019 · 7,582 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal Time Anomaly Detection in Massive Data Streams with ELK StackJakup Fondaj, Zirije HasaniReal time anomaly detection is very popular topic nowadays this because the number of data generated every day is larger and larger. Facing with the phenomena of Big Data is not an easy task. The main aim of this research is to fine appropriate architecture for real-time big data analytic and its main task is to detect anomalies in this … …Journal of Computer Science, Vol. 15, Issue 6 · 17 Jun 2019 · 7,794 accessesView PDFCite
Research ArticleOpen accessIn the abstractContinuous Wavelet Transform Based Spectral Decomposition of 3d Seismic Data for Reservoir Characterization in Oyi Field, se Niger DeltaChukwuemeka Ngozi Ehirim, Andifon Sylvester AkpanContinuous Wavelet Transform (CWT) is one of the most used wavelet transform based spectral decomposition methods in the direct detection of hydrocarbons and as an indicator of stratigraphic variability due to its optimal time-frequency resolution and variable time window requirements. CWT based spectral decomposition was applied on a 3D Post Stack Time Migrated (PSTM) seismic data acquired over a producing … …American Journal of Applied Sciences, Vol. 14, Issue 8 · 28 Apr 2017 · 7,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractScorpius: sFlow Network Anomaly SimulatorMarcos V.O. de Assis, Mario Lemes Proença Jr.Due to the increasing amount of data traveling computer networks every day, efficient management of this information is required to ensure the quality of the services provided by them. Development of new network management tools and mechanisms is a widely approached area due to its importance, not only to the current technology, but also to next generation network standards and … …Journal of Computer Science, Vol. 11, Issue 4 · 23 Jul 2015 · 7,528 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 · 6,776 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,968 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid of Fuzzy Clustering Neural Network Over NSL Dataset for Intrusion Detection SystemDahlia Asyiqin Ahmad Zainaddin, Zurina Mohd HanapiIntrusion Detection System (IDS) is one of the component that take part in the system defence, to identify abnormal activities happening in the computer system. Nowadays, IDS facing composite demands to defeat modern attack activities from damaging the computer systems. Anomaly-Based IDS examines ongoing traffic, activity, transactions and behavior in order to identify intrusions by detecting anomalies. These technique identifies … …Journal of Computer Science, Vol. 9, Issue 3 · 4 May 2013 · 6,574 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Local Network Intrusion Detection System Based on Support Vector MachineMuamer N. Mohammad, Norrozila Sulaiman, Emad T. KhalafProblem statement: Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable Intrusion Detection Systems (IDS). Many methods and techniques were used for modeling the IDS, but some of them contribute little or not to resolve it. Approach: Intrusion detection system for local area network by using Support Vector Machines (SVM) was … …Journal of Computer Science, Vol. 7, Issue 10 · 6 Aug 2011 · 7,313 accessesView PDFCite