Accession Number:

AD1033052

Title:

Improvement of Binary Analysis Components in Automated Malware Analysis Framework

Descriptive Note:

Technical Report,26 May 2015,25 Nov 2016

Corporate Author:

Keio University Fujisawa Japan

Personal Author(s):

• Takeda, Keiji

Report Date:

2017-02-21

Pagination or Media Count:

4.0

Abstract:

This research was conducted to develop components for automated system to analyze malicious software malware with minimum human interaction. The system autonomously analyze malware samples by analyzing malware binary program and by monitoring their behavior, then generate data for malware detection signature and for developing their counter measure.

Descriptors:

• malware
• computer security
• computer programs
• detection
• automation
• monitoring
• virtual machines

Subject Categories:

• Computer Systems Management and Standards

Distribution Statement:

APPROVED FOR PUBLIC RELEASE