Walling up Backdoors in Intrusion Detection Systems-Reference-Cited by-同舟云学术

Walling up Backdoors in Intrusion Detection Systems

Published:2019-12-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd ACM CoNEXT Workshop on Big DAta, Machine Learning and Artificial Intelligence for Data Communication Networks
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Author:

Bachl Maximilian¹,Hartl Alexander¹,Fabini Joachim¹,Zseby Tanja¹

Affiliation:

1. Technische Universität Wien

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3359992.3366638

Reference19 articles.

1. D. W. Apley and J. Zhu. 2016. Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models. arXiv:1612.08468 [stat] (Dec. 2016). arXiv: 1612.08468. D. W. Apley and J. Zhu. 2016. Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models. arXiv:1612.08468 [stat] (Dec. 2016). arXiv: 1612.08468.

2. B. Biggio I. Corona G. Fumera G. Giacinto and F. Roli . 2011 . Bagging classifiers for fighting poisoning attacks in adversarial environments. In 10th Int'l Workshop on Multiple Classifier Systems volume 6713 of LNCS . Springer Naples Italy 350--359. B. Biggio I. Corona G. Fumera G. Giacinto and F. Roli. 2011. Bagging classifiers for fighting poisoning attacks in adversarial environments. In 10th Int'l Workshop on Multiple Classifier Systems volume 6713 of LNCS. Springer Naples Italy 350--359.

3. A comparative analysis of methods for pruning decision trees

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