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Junwen Lu, Jinhui Wang, Xiaojun Wei, Keshou Wu and Guanfeng Liu
There is relatively little research on deep learning for anomaly detection within the field of deep learning. Existing deep anomaly detection methods focus on the learning of feature reconstruction, but such methods mainly learn new feature representatio...
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Milad Memarzadeh, Ata Akbari Asanjan and Bryan Matthews
Identifying safety anomalies and vulnerabilities in the aviation domain is a very expensive and time-consuming task. Currently, it is accomplished via manual forensic reviews by subject matter experts (SMEs). However, with the increase in the amount of d...
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Konstantina Fotiadou, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Dimitrios Skias, Sofia Tsekeridou and Theodore Zahariadis
Network intrusion detection is a key pillar towards the sustainability and normal operation of information systems. Complex threat patterns and malicious actors are able to cause severe damages to cyber-systems. In this work, we propose novel Deep Learni...
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Ruobin Qi, Craig Rasband, Jun Zheng and Raul Longoria
Smart grids integrate advanced information and communication technologies (ICTs) into traditional power grids for more efficient and resilient power delivery and management, but also introduce new security vulnerabilities that can be exploited by adversa...
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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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Olga Tushkanova, Diana Levshun, Alexander Branitskiy, Elena Fedorchenko, Evgenia Novikova and Igor Kotenko
Cyberattacks on cyber-physical systems (CPS) can lead to severe consequences, and therefore it is extremely important to detect them at early stages. However, there are several challenges to be solved in this area; they include an ability of the security...
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Xiaoyu Tang, Sijia Xu and Hui Ye
In network edge computing scenarios, close monitoring of network data and anomaly detection is critical for Internet services. Although a variety of anomaly detectors have been proposed by many scholars, few of these take into account the anomalies of th...
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James Simon Flynn, Cinzia Giannetti and Hessel Van Dijk
In many manufacturing systems, anomaly detection is critical to identifying process errors and ensuring product quality. This paper proposes three semi-supervised solutions to detect anomalies in Direct Current (DC) Nut Runner engine assembly processes. ...
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Luis Basora, Paloma Bry, Xavier Olive and Floris Freeman
Predictive maintenance has received considerable attention in the aviation industry where costs, system availability and reliability are major concerns. In spite of recent advances, effective health monitoring and prognostics for the scheduling of condit...
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