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Research on Web Vulnerability Mining System Based on Machine Learning
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AI
DOI：10.1007/978-981-95-3480-7_17.png)
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Abstract
En 中文
Vulnerability mining has evolved alongside the Internet, initially focusing on exploiting executable vulnerabilities like buffer overflows and heap overflows. As the Web became central to various sectors, it became a prime target for network attacks. Current vulnerability mining focuses on Fuzzing, source code auditing, and rule matching. Automated vulnerability mining, especially with web crawlers and big data, has advanced quickly, but classifying the accumulated data remains a challenge. This paper proposes a machine learning-based Web vulnerability mining system that integrates automated crawling, data collection, feature extraction, classification, and cloud computing technologies.
Keywords:
Web Security
Vulnerability Excavation
Machine Learning System
Intelligent Classification
Classifier
Journal
B
IF:
0
Papers:
28
Citations:
0
