Malware analysis is a task of utmost importance in cyber-security. Two approaches exist for malware analysis: static and dynamic. Modern malware uses an abundance of techniques to evade both dynamic and static analysis tools. Current dynamic analysis solutions either make modifications to the running malware or use a higher privilege component that does the actual analysis. The former can be easily detected by sophisticated malware while the latter often induces a significant performance overhead. We propose a method that performs malware analysis within the context of the OS itself. Furthermore, the analysis component is camouflaged by a hypervisor, which makes it completely transparent to the running OS and its applications. The evaluation of the system’s efficiency suggests that the induced performance overhead is negligible.
With the advent of the mobile industry, we face new security challenges. ARM architecture is deployed in most mobile phones, homeland security, IoT, autonomous cars and other industries, providing a hypervisor API (via virtualization extension technology). To research the applicability of this virtualization technology for security in this platform is an interesting endeavor. The hypervisor API is an addition available for some ARMv7-a and is available with any ARMv8-a processor. Some ARM platforms also offer TrustZone, which is a separate exception level designed for trusted computing. However, TrustZone may not be available to engineers as some vendors lock it. We present a method of applying a thin hypervisor technology as a generic security solution for the most common operating system on the ARM architecture. Furthermore, we discuss implementation alternatives and differences, especially in comparison with the Intel architecture and hypervisor with Trust-Zone approaches. We provide performance benchmarks for using hypervisors for reverse engineering protection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.