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SIP Steganalysis Using Chaos Theory

The Session Initiation Protocol (SIP) is an IETF-defined signaling protocol widely used for controlling communication sessions such as voice and video calls over Internet Protocol (IP). With wide applications of SIP, hiding secret data in some SIP header fields becomes a potential threat to many applications using SIP. In this paper, chaos theory is applied to analyze normal SIP traffic and a feature model is proposed to detect hidden data in some SIP header fields. Experimental results show that the proposed method has average 91.9% detection rate and the computational complexity is low which makes this method appropriate for online mode.