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23 August 2022 A traffic detection method of ROP attack based on image representation
Mengjie Zhang, Jian Wang, Kaijie Huang, Gang Yang
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Proceedings Volume 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022); 1233009 (2022) https://doi.org/10.1117/12.2646272
Event: International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 2022, Huzhou, China
Abstract
The use of malicious loading like ROP to carry out remote vulnerability attacks has become a severe concern to computer systems. It is critical to reliably detect ROP assaults in traffic and to successfully detect and block remote attacks before they have an impact on the attack target. Existing traffic-based detection approaches, on the other hand, rely on searching for particular bytes in the traffic, which has a low detection efficiency and a significant cost. This study proposes a lightweight ROP attacktraffic detection approach based on image representation, which can identify the ROP chain's image representation from network traffic and therefore complete the detection. We extract gadget fragments from network traffic using ROP gadgets of genuine attacks and randomly mix them with regular traffic to create a training dataset. The inputs are then fed into a Convolutional Neural Network (CNN). Our tests demonstrate that our accuracy reaches 99.7%.
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Mengjie Zhang, Jian Wang, Kaijie Huang, and Gang Yang "A traffic detection method of ROP attack based on image representation", Proc. SPIE 12330, International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), 1233009 (23 August 2022); https://doi.org/10.1117/12.2646272
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KEYWORDS
Data modeling
Convolution
Target detection
Network security
Quantization
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