Panorama: capturing system-wide information flow for malware detection and analysis

Malicious programs spy on users’ behavior and compromise their privacy. Even software from reputable vendors, such as Google Desktop and Sony DRM media player, may perform undesirable actions. Unfortunately, existing techniques for detecting malware and analyzing unknown code samples are insufficient and have significant shortcomings. We observe that malicious information access and processing behavior is the fundamental trait of numerous malware categories breaching users’ privacy (including keyloggers, password thieves, network sniffers, stealth backdoors, spyware and rootkits), which separates these malicious applications from benign software. We propose a system, Panorama, to detect and analyze malware by capturing this fundamental trait. In our extensive experiments, Panorama successfully detected all the malware samples and had very few false positives. Furthermore, by using Google Desktop as a case study, we show that our system can accurately capture its information acce...

• Type: Conference
• Year: 2007
• Where: CCS
• Authors: Heng Yin, Dawn Xiaodong Song, Manuel Egele, Christopher Kruegel, Engin Kirda
• Keywords: CCS 2007, Fundamental Trait, Google Desktop, Malware, Security Privacy