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Distributed filtering algorithm based on local outlier factor under data integrity attacks
Journal of the Franklin Institute, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yue Luo +4 more
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A Genetic-Based Incremental Local Outlier Factor Algorithm for Efficient Data Stream Processing
Proceedings of the 2020 4th International Conference on Compute and Data Analysis, 2020Interest in outlier detection methods is increasing because detecting outliers is an important operation for many applications such as detecting fraud transactions in credit card, network intrusion detection and data analysis in different domains. We are now in the big data era, and an important type of big data is data stream.
Omar Alghushairy +3 more
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Active Semi-supervised Affinity Propagation Clustering Algorithm Based on Local Outlier Factor
2018 37th Chinese Control Conference (CCC), 2018Clustering algorithm can reveal the inherent properties and laws of data through the learning of unlabeled data. However, interference data exists in some fields of different data forms, and the clustering will reduce the credibility of clustering results without processing data.
Lei Qi, Li Ting
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Accelerating the local outlier factor algorithm on a GPU for intrusion detection systems
Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units, 2010The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in which the degree to which an object is outlying is dependent on the density of its local neighborhood, and each object can be assigned an LOF which represents the likelihood of
Malak Alshawabkeh +2 more
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2021
In the era of big data, outlier detection has become an important task for many applications, such as the network intrusion detection system. Data streams are a unique type of big data, which recently has gained a lot of attention from researchers. Nevertheless, there are challenges in applying traditional outlier detection algorithms for data streams.
Omar Alghushairy +3 more
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In the era of big data, outlier detection has become an important task for many applications, such as the network intrusion detection system. Data streams are a unique type of big data, which recently has gained a lot of attention from researchers. Nevertheless, there are challenges in applying traditional outlier detection algorithms for data streams.
Omar Alghushairy +3 more
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A Comparative Study of Local Outlier Factor Algorithms for Outliers Detection in Data Streams
2018Outlier detection analyzes data, finds out anomalies, and helps to discover unforeseen activities in safety crucial systems. Outlier detection helps in early prediction of various fraudulent activities like credit card theft, fake insurance claim, tax stealing, real-time monitoring, medical systems, online transactions, and many more.
Supriya Mishra, Meenu Chawla
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Application of Cluster-Based Local Outlier Factor Algorithm in Anti-Money Laundering
2009 International Conference on Management and Service Science, 2009Financial institutions’ capability in recognizing suspicious money laundering transactional behavioral patterns (SMLTBPs) is critical to anti-money laundering. Combining distance-based unsupervised clustering and local outlier detection, this paper designs a new cluster-based local outlier factor (CBLOF) algorithm to identify SMLTBPs and use authentic ...
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The International Journal of Advanced Manufacturing Technology, 2019
In this research, we proposed a real-time chatter detection and suppression module for intelligent spindle to increase machining efficiency and processing yield. For early detections of chatters, the relative wavelet packet energy entropy with high sensitivity in the high-frequency band and the local outlier factor (LOF) algorithm were utilized as ...
Yung-Chen Yao +3 more
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In this research, we proposed a real-time chatter detection and suppression module for intelligent spindle to increase machining efficiency and processing yield. For early detections of chatters, the relative wavelet packet energy entropy with high sensitivity in the high-frequency band and the local outlier factor (LOF) algorithm were utilized as ...
Yung-Chen Yao +3 more
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