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Cyber-resilient machine learning framework for accurate individual load forecasting and anomaly detection in smart grids. [PDF]

Sci Rep
Tayseer M, Talaat M, Zamel AA, Sedhom BE, Elgamal M, Senjyu T, Song D, Ibrahim IM, Elkholy MH.   +8 more
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Secure aggregation for heterogeneous enterprise data based on federated meta-learning. [PDF]

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Yang C, Ma Y.
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Detecting potential fraudulent healthcare insurance claims using anomaly detection : a comparative study on isolation forest and local outlier factor algorithms

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Distributed filtering algorithm based on local outlier factor under data integrity attacks

Journal of the Franklin Institute, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yue Luo, Yun Liu, Wen Yang, Jiayu Zhou, Taolin Lv   +4 more
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GMBLOF: A Machine Learning Algorithm of Novelty Detection Based on Local Outlier Factor

2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI), 2022
Local Outlier Factor (LOF) algorithm is a typical machine learning algorithm and has good accuracy in novelty detection for detecting global and local outlier.
Xing Yang, Kexin Peng, Le An, Pan Huang, Peng Feng   +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, 2020
Interest 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, Raed Alsini, Xiaogang Ma, Terence Soule   +3 more
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Identifying Abnormal Energy Consumption Patterns in Industrial Settings: Application of Local Outlier Factor Algorithm for a Processing Factory in Vietnam

2023 Asia Meeting on Environment and Electrical Engineering (EEE-AM), 2023
In practice, the energy consumption of industrial equipment rises mostly due to wear and tear, which might include leaks or faulty plant conditions.
Hoang-Anh Dang, Van-Dung Dao, Chi-Dung Dang, Nhat Hai Nguyen, Anh Hoang   +4 more
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Improving the Efficiency of Genetic-Based Incremental Local Outlier Factor Algorithm for Network Intrusion Detection

Transactions on Computational Science and Computational Intelligence, 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, Raed Alsini, Xiaogang Ma, Terence Soule   +3 more
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Application of Cluster-Based Local Outlier Factor Algorithm in Anti-Money Laundering

2009 International Conference on Management and Service Science, 2009
Financial 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 ...
Zengan Gao
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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, 2010
The 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, Byunghyun Jang, David Kaeli   +2 more
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