Automated process workflow for malware analysis

Abstract

Malware is short for malicious software, by embedding a malicious script into a software once executed can cause harmful damages to the computer system such as removing or encrypting files . Malware detection techniques are constantly evolving to keep up with the growing number of malware spices in the IT world. The timely and effectively of detection techniques can determine the critical timeline and save huge amount of infrastructure from being damage by the newly develop malwares. Over the years the use of machine learning, and automatic intelligence have shown the improvement in the rate of malware classification and detection.

This report focuses on the research and development of a fully automated process workflow in detecting the malwares from the various file formats and to provide accurate detection result for enterprise to counter against phishing emails. It is essential in today’s corporate world to prevent malwares such as ransomware from damaging critical information infrastructure systems which is commonly found in email attachments. The attackers use phishing as an attack vectors to lure victim into executing the malicious software.