Is Emulating "Binary Grep in Eyes" Possible with Machine Learning?
Mamoru Mimura, Yuhei Otsubo, Hidema Tanaka, Atsuhiro Goto · 2017
Talented people who work in the fields of cybersecurity are greatly lacking. In particular, there are insufficient experts or white hackers. They have incredible skills such as "binary grep in eyes", which nobody cannot explain logically why or how does it work. "Binary grep in eyes" is a skill to emulate executing GREP command in binary files with human eyes. In general, it is difficult to automate their skills. \par This paper proposes some methods to emulate "binary grep in eyes" to detect unseen malicious document files with Convolutional Neural Network (CNN). CNN is commonly linked with innovations in the fields of image recognition and achieves superior results over several prior existing models. Then this paper created the dataset from actual malicious document files in the wild, and calculated the Precision, the Recall and the F-measure to evaluate our method. As the result, there is a possibility that our method can emulate "binary grep in eyes" and detect the shellcode in unseen malicious document files..