An optimal LT code for network flow watermarking
Sheng ua Gao, Lei Zhang · Third International Conference on Computer Science and Communication Technology (ICCSCT 2022) · 2022
Network flow watermarking has been employed to analyze whether two flows are correlated, which is often applied in non-cooperative networks. The detection performance of network flow watermarking is poor due to delay jitter, packets loss etc. In this paper, we improve the detection performance of network flow watermarking by using Luby Transform (LT) codes, which can take full advantage of network flow by automatically adapting to the length of network flow. To further improve the performance of LT codes for network flow watermarking, an optimal degree distribution is generated through a heuristic algorithm. Theoretical analysis and simulations show that our proposed method outperforms others in terms of the detection performance.