FastEmbed: Predicting vulnerability exploitation possibility based on ensemble machine learning algorithm

In recent years, the number of vulnerabilities discovered and publicly disclosed has shown a sharp upward trend. However, the value of exploitation of vulnerabilities varies for attackers, considering that only a small fraction of vulnerabilities are exploited. Therefore, the realization of quick ex...

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Bibliographic Details
Published in:	PloS one 2020-02, Vol.15 (2), p.e0228439
Main Authors:	Fang, Yong, Liu, Yongcheng, Huang, Cheng, Liu, Liang
Format:	Article
Language:	English
Subjects:	Accuracy Algorithms Analysis Artificial intelligence Biology and Life Sciences Computer and Information Sciences Computer security Computer Security - standards Computer Security - statistics & numerical data Computer software industry Computer viruses Confidentiality - standards Cybercrime Cybersecurity Data Collection - standards Data encryption Data mining Embedding Exploitation Feature extraction Forecasting Information Systems - standards Intelligence gathering Internet crime Learning algorithms Machine Learning Methods Morphology National security Physical Sciences Prediction models Proof of Concept Study Research and Analysis Methods Risk-Taking Semantics Social networks Social Sciences Threat evaluation
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