Title: LeakProber: A framework for profiling sensitive data leakage paths

Abstract: 

In this paper, we present the design, implementation, and evaluation
of LeakProber, a framework that leverages the whole system dynamic
instrumentation and the inter-procedural analysis to enable data
propagation path profiling in the production system. We integrate both
the static analysis and runtime tracking to establish a holistic and
practical approach to generating the sensitive data propagation graph
(sDPG) with minimum runtime overhead. We evaluate our system on
several data stealing attacks scenario for generating sDPG. The sDPG
generated by our system captures multiple aspects of data accessing
patterns and provides clear insights into the data leakage path. We
also measure the performance of our system and find that it degrades
the production system about 6% in the trace-on mode. When our
prototype works in the trace-off mode, the runtime overhead is even
lower, on an average of 1.5% across each benchmark we run. We believe
that it is feasible to directly apply our prototype into production
system environment.