Symbol Probability

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The Experts below are selected from a list of 11766 Experts worldwide ranked by ideXlab platform

A. I. Starikovskii - One of the best experts on this subject based on the ideXlab platform.

Dipak Ghosal - One of the best experts on this subject based on the ideXlab platform.

  • designing analog fountain timing channels undetectability robustness and model adaptation
    IEEE Transactions on Information Forensics and Security, 2016
    Co-Authors: Weiwei Liu, Guangjie Liu, Jiangtao Zhai, Yuewei Dai, Dipak Ghosal
    Abstract:

    In existing model-based timing channels, the requirement for the target model to be shared between the sender and the receiver limits the sender’s ability to adapt to changes in the inter-packet delay (IPD) distribution of the application traffic. In this paper, using analog fountain codes (AFCs) with a general model-fitting coding framework, we design timing channel schemes that allow the sender to change the target model without synchronizing with the receiver. We first propose analog fountain timing channels based on Symbol transition when the application packet streams have IPD distribution that is shape similar to the distribution of AFC code Symbol values. For more general packet streams, we then propose analog fountain timing channels based on Symbol split in which the linearly mapped Symbols are split using a Symbol Probability split matrix to mimic the IPD distribution of the application traffic. We use real VoIP and SSH traffic to compare the proposed schemes with model-based timing channels using LT codes and AFC. Experimental results show that both the proposed schemes are model-secure. The robustness of the two schemes is higher than the model-based timing channels using LT codes whereas not as good as those using AFC when the sender and receiver sides are synchronized with respect to the target model. Moreover, when the sender and the receiver are not synchronized with respect to the model, the robustness of the proposed schemes is significantly higher than model-based timing channels.

G. V. Kulikov - One of the best experts on this subject based on the ideXlab platform.

Weiwei Liu - One of the best experts on this subject based on the ideXlab platform.

  • designing analog fountain timing channels undetectability robustness and model adaptation
    IEEE Transactions on Information Forensics and Security, 2016
    Co-Authors: Weiwei Liu, Guangjie Liu, Jiangtao Zhai, Yuewei Dai, Dipak Ghosal
    Abstract:

    In existing model-based timing channels, the requirement for the target model to be shared between the sender and the receiver limits the sender’s ability to adapt to changes in the inter-packet delay (IPD) distribution of the application traffic. In this paper, using analog fountain codes (AFCs) with a general model-fitting coding framework, we design timing channel schemes that allow the sender to change the target model without synchronizing with the receiver. We first propose analog fountain timing channels based on Symbol transition when the application packet streams have IPD distribution that is shape similar to the distribution of AFC code Symbol values. For more general packet streams, we then propose analog fountain timing channels based on Symbol split in which the linearly mapped Symbols are split using a Symbol Probability split matrix to mimic the IPD distribution of the application traffic. We use real VoIP and SSH traffic to compare the proposed schemes with model-based timing channels using LT codes and AFC. Experimental results show that both the proposed schemes are model-secure. The robustness of the two schemes is higher than the model-based timing channels using LT codes whereas not as good as those using AFC when the sender and receiver sides are synchronized with respect to the target model. Moreover, when the sender and the receiver are not synchronized with respect to the model, the robustness of the proposed schemes is significantly higher than model-based timing channels.

Yu. I. Savvateev - One of the best experts on this subject based on the ideXlab platform.