Automatic Malware Analysis An Emulator Based Approach /

• Main Authors: Yin, Heng. (Author), Song, Dawn. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: New York, NY : Springer New York : Imprint: Springer, 2013.
• Series: SpringerBriefs in Computer Science,
• Subjects: Computer science.; Data protection.; Data structures (Computer science).; Data encryption (Computer science).; Information systems.; Computer Science.; Systems and Data Security.; Data Encryption.; Data Structures, Cryptology and Information Theory.; Information Systems and Communication Service.; Information Systems Applications (incl. Internet).
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4614-5523-3

 Malicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems.� Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.