Summary The main goal of code obfuscation is to make software more difficult to reverse engineer. These techniques modify data structures and control flow while retaining the functionality of the original program. Although obfuscation is a useful method for protecting programs, it can also be used to protect malware. This raises concerns that malware could use code obfuscation to avoid detection by antivirus software. It is very difficult to analyze the functionality of obfuscated malware before it has been deobfuscated. Furthermore, commercial obfuscation tools allow malware authors to apply multiple obfuscation options simultaneously, and current deobfuscation techniques cannot handle this situation. In this study, we analyzed a well‐known commercial obfuscation tool called Themida. We applied its many obfuscation options to a program and implemented a tool to recover the original code and data. We extracted features from obfuscated programs and analyzed their control flow. Our tool is based on these features and the control flow patterns and can identify whether Themida has been applied to the program and which obfuscation options have been used. Finally, we suggested a method for recovering the import address table of programs by using dynamic binary instrumentation. The proposed rules and algorithms can almost completely recover the APIs of programs even though they are hidden by obfuscation options provided by Themida.

A scaler is one of the most important modules in various video applications, such as ultra-high definition TV and scalable video systems. A variety of scaling techniques have been used to increase the video quality when the resolution of the source image has to be up- and down-scaled. Some conventional schemes exploit the property of local block data. Others consider the edge information of the data to be scaled. In this paper, we formulate a scaling problem to minimize the information loss resulting from the resizing process. The loss is considered in both the spatial and the frequency domains, and then it is minimized to optimize the kernel of the scaler. The simulation results show that the proposed algorithm reduces the information loss more than conventional schemes. When compared with the conventional algorithms, the proposed method outperforms those with similar complexity.