Search Results - (( data detection method algorithm ) OR ( data normalization based algorithm ))
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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Anomaly behavior detection using flexible packet filtering and support vector machine algorithms
Published 2016“…Both methods used DARPA 98- 99 dataset and Lincoln Labs data. …”
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A clustering-based method for outlier detection under concept drift
Published 2024“…However, challenges may arise from assuming the majority of data comprises normal instances, particularly during sudden spikes in attack data, potentially diminishing algorithm effectiveness. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Unsupervised Anomaly Detection with Unlabeled Data Using Clustering
Published 2005“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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Fault diagnostic algorithm for precut fractionation column
Published 2004“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim
Published 2018“…This research addressed severe contamination or occlusion presence in a face recognition based on image data. A modified version of the existing least trimmed square, LTS method with genetic algorithm (LTS with GAs) was proposed to cater the problem of noise or occlusion and improve the performance of face recognition. …”
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems
Published 2012“…The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Blotch removal using multi-level scanning, shape analysis, and meta heuristic techniques
Published 2015“…Regarding the detection, a post processing method based on a combination of pixel-based and objects-based methods was proposed. …”
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification
Published 2013“…Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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