Research on the Penetration Testing Model in the Vertical Field Using Generative AI Technology

Traditional penetration testing relies deeply on high technical requirements for testers, thus limiting the breadth of popularization. Automated pen-testing with artificial intelligence reduces the barrier. This article introduces the application of generative artificial intelligence in the field of pen-testing, introduces machine learning modeling techniques for vulnerability intelligence, constructs a large language model for experimental analysis, and looks forward to future research.

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Published
2024-11-29
DOI
https://doi.org/10.1109/ei264398.2024.10990542
Primary Topic
Advanced Decision-Making Techniques
Type
article
Field-Weighted Citation Impact
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article

Research on the Penetration Testing Model in the Vertical Field Using Generative AI Technology

Cong Hou, Yue Sun, Yuyue Su
Advanced Decision-Making Techniques
article

Research on the Penetration Testing Model in the Vertical Field Using Generative AI Technology

Cong Hou, Yue Sun, Yuyue Su
article en

Abstract

Traditional penetration testing relies deeply on high technical requirements for testers, thus limiting the breadth of popularization. Automated pen-testing with artificial intelligence reduces the barrier. This article introduces the application of generative artificial intelligence in the field of pen-testing, introduces machine learning modeling techniques for vulnerability intelligence, constructs a large language model for experimental analysis, and looks forward to future research.

State Grid Corporation of China (China) (CN)
Openalex Percentile: Top 51%
Advanced Decision-Making Techniques
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