Download Automatic Malware Analysis: An Emulator Based Approach by Heng Yin PDF

By Heng Yin

Malicious software program (i.e., malware) has develop into a critical hazard to interconnected desktops for many years and has brought on billions of greenbacks damages every year. a wide quantity of recent malware samples are chanced on day-by-day. Even worse, malware is speedily evolving turning into extra subtle and evasive to strike opposed to present malware research and security structures.

Automatic Malware research presents a virtualized malware research framework that addresses universal demanding situations in malware research. with reference to this new research framework, a sequence of research ideas for computerized malware research is constructed. those thoughts trap intrinsic features of malware, and are compatible for facing new malware samples and assault mechanisms.

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Extra resources for Automatic Malware Analysis: An Emulator Based Approach

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In addition, rootkits may implant hooks to intercept and tamper with critical system information to conceal their presence in the system. Malware with a stealth backdoor may also place hooks on the network stack to establish a stealthy communication channel with remote attackers. Several tools [2, 10, 13] detect hooking behaviors by checking known memory regions for suspicious entries. However, they need prior knowledge of how existing malware implants hooks. Therefore, they become futile when malware uses new hooking mechanisms.

Depending on the installation delay, the whole procedure lasts 15 to 25 minutes. 2 summarizes the results of this experiment. We can see that Panorama was able to correctly identify all malware samples, but falsely declared three benign samples to be malicious. Two of these false positives were personal firewall programs. The third false positive was a browser accelerator. By checking the taint graphs related to these three samples, we observed that the information access and processing behaviors of these benign samples closely resemble that of malware.

Html 22. : Secure program execution via dynamic information flow tracking. In: Proceedings of the 11th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’04) (2004) 42 4 Privacy-breaching Behavior Analysis 23. : Cross-Site Scripting Prevention with Dynamic Data Tainting and Static Analysis. In: Proceeding of the Network and Distributed System Security Symposium (NDSS’07) (2007) 24. : Gatekeeper: Monitoring Auto-Start Extensibility Points (ASEPs) for spyware management.

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