Online anomaly detection with concept drift adaptation using recurrent neural networks

Proceedings of the ACM India Joint International Conference on Data Science and Management of Data - CoDS-COMAD '18 ◽

10.1145/3152494.3152501 ◽

2018 ◽

Author(s):

Sakti Saurav ◽

Pankaj Malhotra ◽

Vishnu TV ◽

Narendhar Gugulothu ◽

Lovekesh Vig ◽

...

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks ◽

Concept Drift ◽

Online Anomaly Detection

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Recurrent Neural Networks on Duty of Anomaly Detection in Databases

Advances in Neural Networks – ISNN 2007 - Lecture Notes in Computer Science ◽

10.1007/978-3-540-72395-0_12 ◽

2007 ◽

pp. 85-94 ◽

Author(s):

Jaroslaw Skaruz ◽

Franciszek Seredynski

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks

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Collective Anomaly Detection Based on Long Short-Term Memory Recurrent Neural Networks

Future Data and Security Engineering - Lecture Notes in Computer Science ◽

10.1007/978-3-319-48057-2_9 ◽

2016 ◽

pp. 141-152 ◽

Author(s):

Loïc Bontemps ◽

Van Loi Cao ◽

James McDermott ◽

Nhien-An Le-Khac

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks ◽

Short Term Memory ◽

Term Memory ◽

Long Short Term Memory ◽

Collective Anomaly

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Concept Drift Adaption for Online Anomaly Detection in Structural Health Monitoring

Proceedings of the 28th ACM International Conference on Information and Knowledge Management - CIKM '19 ◽

10.1145/3357384.3357816 ◽

2019 ◽

Author(s):

Hongda Tian ◽

Nguyen Lu Dang Khoa ◽

Ali Anaissi ◽

Yang Wang ◽

Fang Chen

Keyword(s):

Structural Health Monitoring ◽

Anomaly Detection ◽

Health Monitoring ◽

Concept Drift ◽

Structural Health ◽

Online Anomaly Detection

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Anomaly Detection in Cyber Physical Systems Using Recurrent Neural Networks

2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE) ◽

10.1109/hase.2017.36 ◽

2017 ◽

Author(s):

Jonathan Goh ◽

Sridhar Adepu ◽

Marcus Tan ◽

Zi Shan Lee

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks ◽

Cyber Physical Systems ◽

Physical Systems

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Robust Anomaly Detection for Multivariate Data of Spacecraft through Recurrent Neural Networks and Extreme Value Theory

IEEE Access ◽

10.1109/access.2021.3136505 ◽

2021 ◽

pp. 1-1

Author(s):

Gang Xiang ◽

Ruishi Lin

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Extreme Value Theory ◽

Recurrent Neural Networks ◽

Multivariate Data ◽

Value Theory ◽

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Applying of Recurrent Neural Networks for Industrial Processes Anomaly Detection

2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT) ◽

10.1109/usbereit51232.2021.9455060 ◽

2021 ◽

Author(s):

Sergei K. Alabugin ◽

Alexander N. Sokolov

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks ◽

Industrial Processes

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Poster abstract: Streamlined anomaly detection in web requests using recurrent neural networks

2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) ◽

10.1109/infcomw.2017.8116538 ◽

2017 ◽

Author(s):

Arne Bochem ◽

Hang Zhang ◽

Dieter Hogrefe

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks ◽

Poster Abstract

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Attention-based Encoder-Decoder Recurrent Neural Networks for HTTP Payload Anomaly Detection

10.1109/ispa-bdcloud-socialcom-sustaincom52081.2021.00196 ◽

2021 ◽

Author(s):

Shang Wu ◽

Yijie Wang

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks

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Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining ◽

10.1145/3447548.3467125 ◽

2021 ◽

Author(s):

Zhiwei Wang ◽

Zhengzhang Chen ◽

Jingchao Ni ◽

Hui Liu ◽

Haifeng Chen ◽

...

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks ◽

Discrete Event ◽

Event Sequence ◽

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Anomaly detection in aircraft data using Recurrent Neural Networks (RNN)

2016 Integrated Communications Navigation and Surveillance (ICNS) ◽

10.1109/icnsurv.2016.7486356 ◽

2016 ◽

Author(s):

Anvardh Nanduri ◽

Lance Sherry

Keyword(s):

Neural Networks ◽

Anomaly Detection ◽

Recurrent Neural Networks ◽

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