Visible to the public Lprov: Practical Library-Aware Provenance Tracing

TitleLprov: Practical Library-Aware Provenance Tracing
Publication TypeConference Paper
Year of Publication2018
AuthorsWang, Fei, Kwon, Yonghwi, Ma, Shiqing, Zhang, Xiangyu, Xu, Dongyan
Conference NameProceedings of the 34th Annual Computer Security Applications Conference
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-6569-7
Keywordscomposability, Human Behavior, human factors, Metrics, pubcrawl, resilience, Resiliency, Secure File Sharing

With the continuing evolution of sophisticated APT attacks, provenance tracking is becoming an important technique for efficient attack investigation in enterprise networks. Most of existing provenance techniques are operating on system event auditing that discloses dependence relationships by scrutinizing syscall traces. Unfortunately, such auditing-based provenance is not able to track the causality of another important dimension in provenance, the shared libraries. Different from other data-only system entities like files and sockets, dynamic libraries are linked at runtime and may get executed, which poses new challenges in provenance tracking. For example, library provenance cannot be tracked by syscalls and mapping; whether a library function is called and how it is called within an execution context is invisible at syscall level; linking a library does not promise their execution at runtime. Addressing these challenges is critical to tracking sophisticated attacks leveraging libraries. In this paper, to facilitate fine-grained investigation inside the execution of library binaries, we develop Lprov, a novel provenance tracking system which combines library tracing and syscall tracing. Upon a syscall, Lprov identifies the library calls together with the stack which induces it so that the library execution provenance can be accurately revealed. Our evaluation shows that Lprov can precisely identify attack provenance involving libraries, including malicious library attack and library vulnerability exploitation, while syscall-based provenance tools fail to identify. It only incurs 7.0% (in geometric mean) runtime overhead and consumes 3 times less storage space of a state-of-the-art provenance tool.

Citation Keywang_lprov:_2018