Utilizing Reverse Engineering Technique for A Malware Analysis Model

Abstract

Purpose: Malicious software or malware is a real threat to the security of computer systems or networks. Researchers made various attempts to find information and knowledge about malware, including preventing or even eliminating it. One effort to detect it is using a malware dynamic analysis model based on reverse engineering techniques. However, there are many reverse engineering techniques proposed with various stages and requirements in the literature. Methods: This research uses an experimental method. The object of research is a malware analysis model using reverse engineering techniques. The experimental method used is qualitative, collecting data related to the advantages and disadvantages of the reverse engineering-based malware analysis models used as a reference in this study. The data is used as consideration to propose a new model of malware analysis utilizing reverse engineering techniques. Result: In this study an analysis model of malware was proposed by synthesizing several reverse engineering-based malware analysis models. Novelty: The proposed model was then tested in a virtual environment where it is proven to be more effective than previous models for analyzing malware.

Comparative Study of Imbalanced Data Oversampling Techniques for Peer-to-Peer Landing Loan Prediction

“…Several studies that have been conducted can address the problem of balancing the amount of data [16]. The data resampling method is an approach that works from increasing the sample distribution by copying minority class samples or eliminating some samples in the majority class [14].…”