Title
Exposing invisible timing-based traffic watermarks with BACKLIT
Abstract
Traffic watermarking is an important element in many network security and privacy applications, such as tracing botnet C&C communications and deanonymizing peer-to-peer VoIP calls. The state-of-the-art traffic watermarking schemes are usually based on packet timing information and they are notoriously difficult to detect. In this paper, we show for the first time that even the most sophisticated timing-based watermarking schemes (e.g., RAINBOW and SWIRL) are not invisible by proposing a new detection system called BACKLIT. BACKLIT is designed according to the observation that any practical timing-based traffic watermark will cause noticeable alterations in the intrinsic timing features typical of TCP flows. We propose five metrics that are sufficient for detecting four state-of-the-art traffic watermarks for bulk transfer and interactive traffic. BACKLIT can be easily deployed in stepping stones and anonymity networks (e.g., Tor), because it does not rely on strong assumptions and can be realized in an active or passive mode. We have conducted extensive experiments to evaluate BACKLIT's detection performance using the PlanetLab platform. The results show that BACKLIT can detect watermarked network flows with high accuracy and few false positives.
Year
DOI
Venue
2011
10.1145/2076732.2076760
ACSAC
Keywords
Field
DocType
c communication,traffic watermarking,interactive traffic,botnet c,state-of-the-art traffic,practical timing-based traffic watermark,state-of-the-art traffic watermark,sophisticated timing-based watermarking scheme,invisible timing-based traffic watermark,anonymity network,detection performance,network flow,backlit,sequential sampling,invisible,biometrics,network security,false positive
PlanetLab,Digital watermarking,Computer security,Computer science,Botnet,Network packet,Network security,Real-time computing,Watermark,Tracing,Voice over IP
Conference
Citations 
PageRank 
References 
20
0.82
30
Authors
6
Name
Order
Citations
PageRank
Xiapu Luo11302110.23
Peng Zhou2200.82
Junjie Zhang384941.61
Roberto Perdisci4213797.99
Wenke Lee59351628.83
Rocky K. C. Chang665951.06