TY - GEN
T1 - Detecting covert channels within VoIP
AU - Zhao, Hong
AU - Ansari, Nirwan
N1 - Funding Information:
Acknowledgement Research funding is partially provided by the National Science Foundation through Grant No. CMMI-1351537 by Hazard Mitigation and Structural Engineering program and by a grant from the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA).
PY - 2012
Y1 - 2012
N2 - VoIP (Voice Over IP) was ranked third among the top 11 technologies of the decade in 2011. It is one of the most popular networking services. As it is readily adopted, the VoIP traffic is increasing steadily. The large amount of data transported by VoIP makes it ideal for creating covert channels. Attacks based on covert channels becomes a new challenge for network security. In this paper, possible covert channels via VoIP are analyzed, and an effective countermeasure to detect hidden messages in both SEQ (Sequence Number) and SSRC (Source Identifier) fields in the RTP protocol during conversation phase is proposed. This proposed method creates a new processing space, in which, normal traffic is analyzed and characterized by a proposed statistical model. This model is used in detecting hidden information in SSRCs and SEQs. Simulation results show that 100% detection rate can be realized. As the proposed model requires only a small amount of training data and no illegal traffic is used in the training, the computational complexity is small and can be used for on-line covert channel detection.
AB - VoIP (Voice Over IP) was ranked third among the top 11 technologies of the decade in 2011. It is one of the most popular networking services. As it is readily adopted, the VoIP traffic is increasing steadily. The large amount of data transported by VoIP makes it ideal for creating covert channels. Attacks based on covert channels becomes a new challenge for network security. In this paper, possible covert channels via VoIP are analyzed, and an effective countermeasure to detect hidden messages in both SEQ (Sequence Number) and SSRC (Source Identifier) fields in the RTP protocol during conversation phase is proposed. This proposed method creates a new processing space, in which, normal traffic is analyzed and characterized by a proposed statistical model. This model is used in detecting hidden information in SSRCs and SEQs. Simulation results show that 100% detection rate can be realized. As the proposed model requires only a small amount of training data and no illegal traffic is used in the training, the computational complexity is small and can be used for on-line covert channel detection.
UR - http://www.scopus.com/inward/record.url?scp=84864184012&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864184012&partnerID=8YFLogxK
U2 - 10.1109/SARNOF.2012.6222709
DO - 10.1109/SARNOF.2012.6222709
M3 - Conference contribution
AN - SCOPUS:84864184012
SN - 9781467314640
T3 - 35th IEEE Sarnoff Symposium, SARNOFF 2012 - Conference Proceedings
BT - 35th IEEE Sarnoff Symposium, SARNOFF 2012 - Conference Proceedings
T2 - 35th IEEE Sarnoff Symposium, SARNOFF 2012
Y2 - 21 May 2012 through 22 May 2012
ER -