ABSTRACT
This chapter describes novel hybrid feature retrieval (HFR) model that can detect malicious executables efficiently. It discusses aspects of malware executables. Feature vectors are generated from each training instance, using the selected feature set. There have been significant efforts in recent years to detect malicious executables. There are two mainstream techniques to automate the detection process: behavioral and content-based. HFR consists of different phases and components. The HFR model consists of two phases: a training phase and a test phase. Cloud computing offers a cheap alternative to more CPU power and much larger disk space, which could be utilized for much faster feature extraction and selection process.
