Anomaly Behavior Detection for the Web Application Based on LSTM-Reference-Cited by-同舟云学术

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Anomaly Behavior Detection for the Web Application Based on LSTM

Published:2021-12-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)
language:
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Author:

Ma Hongxin¹,Wang Chunbo²,Qi Hui³

Affiliation:

1. Air Force Aviation University,Teaching and Research Guarantee Center,Changchun,China

2. Changchun Automobile Industry Institute,School of Information Technology,Changchun,China

3. Changchun University of Science and Technology,School of Computer Science and Technology,Changchun,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9688562/9688331/09688720.pdf?arnumber=9688720

Reference21 articles.

1. A Deep Learning Method to Detect Web Attacks Using a Specially Designed CNN

2. Anomaly-Based Web Attack Detection

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

4. Web traffic anomaly detection using c-lstm neural networks Expert Systems with Applications;kim,2018

5. Agarwal P Long short term memory networks for anomaly detection in time series;malhotra;Proceedings Presses universitaires de Louvain,2015

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