NAttack! Adversarial Attacks to bypass a GAN based classifier trained to\n detect Network intrusion Article Swipe
Aritran Piplai
,
Sai Sree Laya Chukkapalli
,
Anupam Joshi
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2002.08527
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2002.08527
With the recent developments in artificial intelligence and machine learning,\nanomalies in network traffic can be detected using machine learning approaches.\nBefore the rise of machine learning, network anomalies which could imply an\nattack, were detected using well-crafted rules. An attacker who has knowledge\nin the field of cyber-defence could make educated guesses to sometimes\naccurately predict which particular features of network traffic data the\ncyber-defence mechanism is looking at. With this information, the attacker can\ncircumvent a rule-based cyber-defense system. However, after the advancements\nof machine learning for network anomaly, it is not easy for a human to\nunderstand how to bypass a cyber-defence system. Recently, adversarial attacks\nhave become increasingly common to defeat machine learning algorithms. In this\npaper, we show that even if we build a classifier and train it with adversarial\nexamples for network data, we can use adversarial attacks and successfully\nbreak the system. We propose a Generative Adversarial Network(GAN)based\nalgorithm to generate data to train an efficient neural network based\nclassifier, and we subsequently break the system using adversarial attacks.\n
Related Topics
Concepts
Metadata
- Type
- preprint
- Landing Page
- http://arxiv.org/abs/2002.08527
- https://arxiv.org/pdf/2002.08527
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4287866314
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4287866314Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2002.08527Digital Object Identifier
- Title
-
NAttack! Adversarial Attacks to bypass a GAN based classifier trained to\n detect Network intrusionWork title
- Type
-
preprintOpenAlex work type
- Publication year
-
2020Year of publication
- Publication date
-
2020-02-19Full publication date if available
- Authors
-
Aritran Piplai, Sai Sree Laya Chukkapalli, Anupam JoshiList of authors in order
- Landing page
-
https://arxiv.org/abs/2002.08527Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2002.08527Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2002.08527Direct OA link when available
- Concepts
-
Adversarial system, Adversarial machine learning, Computer science, Artificial intelligence, Machine learning, Classifier (UML), Generative adversarial network, Artificial neural network, Generative grammar, Intrusion detection system, Deep learning, Computer securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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