There have been several advances in understanding the
privacy needs [25] or the privacy requirement of security
applications [26]. In this paper, we identify the privacy needs
in an outsourced data-leak detection service and provide
a systematic solution to enable privacy-preserving
DLD services.
Shingle with Rabin fingerprint [15] was used previously
for identifying similar spam messages in a collaborative
setting [27], as well as collaborative worm containment [28],
virus scan [29], and fragment detection [30].
In comparison, we tackle the unique data-leak detection
problem in an outsourced setting where the DLD provider
is not fully trusted. Such privacy requirement does not exist
in above models, e.g., the virus signatures are non-sensitive in
the virus-scan paradigm [29].We propose the fuzzy fingerprint
approach to meet the special privacy requirement and present