PDF Document Detection for Malicious Evasion Behavior
The Portable Document Format(PDF)is one of the widely used formats in global data exchange,and people have a high level of trust in it.However,in recent years,the situation of criminals using PDF documents for malicious network attacks has become increasingly serious.With the advancement of hacker technology,they are gradually adopting methods to evade detection,making it more difficult for common learning algorithms to detect such malicious files.In response to these"smarter"malicious PDF attack samples,an analysis of the characteristics of PDF documents is conducted,and 25-dimensional features are extracted.By applying a finely-tuned Adaboost algorithm for model training,an accuracy rate of 99.63%is achieved,surpassing other research achievements in the same field.
国家科技期刊平台
NSTL
万方数据
