20182018 3rd International Conference on Computer Science and Engineering (UBMK)Requires access

Analysis and Comparison of Opcode-based Malware Detection Approaches

Mert Nar, Arzu Gorgulu Kakisim, Necmettin Çarkacı, Melek Nurten Yavuz, İbrahim Soğukpınar

Open publisher page 6 citations

Abstract

Malicious software (Malwares) become major threats for digital assets in the digital environment. Traditional malware detection systems use the signatures of the malware executables to detect them. However, the complexity and diversity of malwares increases day by day with metamorphic ones that quickly change its structure and signature. Therefore, most of the researches have focused on the detection of these kinds of malwares. In this work, five different malware detection approaches have been implemented and tested on real and synthetic malware and benign samples. We have collected a new malware data set including 6857 benign and 8701 malicious samples. Experiments have shown that the real malware executables decrease the performance of the methods.

About this research paper

What this paper is about

Malicious software (Malwares) become major threats for digital assets in the digital environment. Traditional malware detection systems use the signatures of the malware executables to detect them. However, the complexity and diversity of malwares increases day by day with metamorphic ones that quickly change its structure and signature. Therefore, most of the researches have focused on the detection of these kinds of malwares. In this work, five different malware detection approaches have been implemented and tested on real and synthetic malware and benign samples. We have collected a new malware data set including 6857 benign and 8701 malicious samples. Experiments have shown that the real malware executables decrease the performance of the methods.

Why it matters

OpenAlex reports 6 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Malicious software (Malwares) become major threats for digital assets in the digital environment. Traditional malware detection systems use the signatures of the malware executables to detect them. However, the complexity and diversity of malwares increases day by day with metamorphic ones that quickly change its structure and signature. Therefore, most of the researches have focused on the detection of these kinds of malwares. In this work, five different malware detection approaches have been implemented and tested on real and synthetic malware and benign samples. We have collected a new malware data set including 6857 benign and 8701 malicious samples. Experiments have shown that the real malware executables decrease the performance of the methods.

Key concepts: Malware, Opcode, Computer science, Cryptovirology, Executable, Software, Set (abstract data type), Computer security

Related papers

Back to paper searchBrowse research topicsOriginal source
Analysis and Comparison of Opcode-based Malware Detection Approaches — Research Paper | ScholarLens