Title :
De-obfuscation and Detection of Malicious PDF Files with High Accuracy
Author :
Lu, Xun ; Zhuge, Jianwei ; Wang, Ruoyu ; Cao, Yinzhi ; Chen, Yan
Abstract :
Due to its high popularity and rich functionalities, the Portable Document Format (PDF) has become a major vector for malware propagation. To detect malicious PDF files, the first step is to extract and de-obfuscate Java Script codes from the document, for which an effective technique is yet to be created. However, existing static methods cannot de-obfuscate Java Script codes, existing dynamic methods bring high overhead, and existing hybrid methods introduce high false negatives. Therefore, in this paper, we present MPScan, a scanner that combines dynamic Java Script de-obfuscation and static malware detection. By hooking the Adobe Reader´s native Java Script engine, Java Script source code and op-code can be extracted on the fly after the source code is parsed and then executed. We also perform a multilevel analysis on the resulting Java Script strings and op-code to detect malware. Our evaluation shows that regardless of obfuscation techniques, MPScan can effectively de-obfuscate and detect 98% malicious PDF samples.
Keywords :
Cyberspace; Dictionaries; Educational institutions; Engines; Malware; Portable document format; Standards; Dynamic API Hooking; JavaScript De-obfuscation; Op-code Signature Matching;
Conference_Titel :
System Sciences (HICSS), 2013 46th Hawaii International Conference on
Conference_Location :
Wailea, HI, USA
Print_ISBN :
978-1-4673-5933-7
Electronic_ISBN :
1530-1605
DOI :
10.1109/HICSS.2013.166