Increasing The Robustness Of Deep Neural Networks For Text Classification By Examining Adversarial Examples


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Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing


Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing

Author: Igor V. Tetko

language: en

Publisher: Springer Nature

Release Date: 2019-09-09


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The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.

Malware Detection


Malware Detection

Author: Mihai Christodorescu

language: en

Publisher: Springer Science & Business Media

Release Date: 2007-03-06


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This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.