A modified LOF-based approach for outlier characterization in IoT.

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From: Annales des Telecommunications(Vol. 76, Issue 3-4)
Publisher: Springer
Document Type: Report; Brief article
Length: 193 words

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Keywords: Outlier characterization; Internet of Things; Local Outlier Factor; Cyber security Abstract The Internet of Things (IoT) is a growing paradigm that is revolutionary for information and communication technology (ICT) because it gathers numerous application domains by integrating several enabling technologies. Outlier detection is a field of tremendous importance, including in IoT. In previous works on outlier detection, the proposed methods mainly tackled the efficacy and the efficiency challenges. However, a growing interest in the interpretation of the detected anomalies has been noticed by the research community, and only a few works have contributed in this direction. Furthermore, characterizing anomalous events in IoT-related problems has not been conducted. Hence, in this paper, we introduce our modified Local Outlier Factor (LOF)--based outlier characterization approach and apply it to enhance the IoT security and reliability. Experiments on both synthetic and real-world datasets show the good performance of our solution. Author Affiliation: (1) School of Computer Science and Engineering, Nanjing University of Science and Technology, 210094, Nanjing, China (2) CEDRIC Lab, Conservatoire National des Arts et Metiers, Paris, France (a) lyndaboukela@njust.edu.cn Article History: Registration Date: 06/16/2020 Received Date: 02/09/2020 Accepted Date: 06/16/2020 Online Date: 07/03/2020 Byline:

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Gale Document Number: GALE|A659037828