基于动态间隔压缩的鲁棒网络流水印算法

针对基于间隔质心的流水印缺乏纠错能力且难以抵御多流攻击的问题，提出一种基于动态间隔压缩的鲁棒网络流水印算法。该算法在基于间隔质心流水印基础上利用编解码技术增强其纠错能力，将携带同一水印信息的网络流量采用动态间隔压缩的方式调制为多种模式以抵御多流攻击。同时在检测端对水印进行分层检测，减少检测端计算资源浪费。实验结果表明，当检测阈值设为0.8时，误报率低于5%,且水印检测率可高于原始间隔质心方法10%左右，合并多条水印数据流后也无明显静默间隔。可见该算法具有良好的鲁棒性和隐蔽性，能够有效提高网络流水印的可用性。

Robust network flow watermarking algorithm based on dynamic interval compression

To address the problem that the interval centroid-based watermarking lacks of error correction capability and is difficult to resist multi-flow attacks, this paper proposed a robust network flow watermarking algorithm based on dynamic interval compression. The method used coding and decoding technology to enhance the error correction capability of the interval centroid-based watermarking, and modulated the network traffic carrying the same watermark information into multiple modes by dynamic interval compression to resist multi-flow attacks. Meanwhile, it detected the watermark in layers at the detection side to reduce the waste of computational resources. The experimental results show that when the detection threshold is set to 0.8, the false positive rate is lower than 5%, and the watermark detection rate can be higher than the original interval centroid-based method by about 10%, and there is no obvious silent interval after merging multiple watermarked flows. It can be seen that the algorithm has good robustness and concealment, and can effectively improve the usability of network flow watermarking.