面向公式对象的恶意文档智能检测技术OA

Formula editor,an important component of Office software,has become a disaster area for vulnerability exploit.In response to the above issues,a formula object oriented intelligent detection method for malicious documents is proposed.By extracting formula objects from office documents and converting them into images,the problem of detecting malicious formula objects is transformed into an image classification problem.Deep learning technology is used to achieve self extraction of detection features.The detection model is trained on a training set consisting of 4 078 benign samples and 1 173 malicious samples,and tested on 1 323 benign samples and 312 malicious samples,achieving a mali-cious sample detection rate of 99.36%,with zero false positives for benign samples and an average sample detection time of about 0.5 ms.To test the anti-evasion ability of the model,a corresponding ad-versarial sample test set is constructed using the methods of"adding normal"and"removing abnor-mal"on the basis of malicious test samples mentioned above.The experiments show that the proposed detection method has strong robustness.