基于排序学习的流式文档数据无损隐藏仿真  

Lossless Hiding Simulation of Streaming Document Data Based on Ranking Learning

作　　者：徐佳丽 罗丽 XU Jia-li;LUO Li(Polytechnic Institute,Jiangxi Science and Technology Normal University Nanchang Jiangxi 330038,China)

机构地区：[1]江西科技师范大学理工学院,江西南昌330038

出　　处：《计算机仿真》2022年第3期174-178,共5页Computer Simulation

基　　金：江西省高等学校教学改革研究课题(JXJG-19-42-1)。

摘　　要：由于现阶段已有方法未能对流式文档数据进行排序,导致传输时延增加,流式文档数据正确接收率和生命周期减少,提出一种基于排序学习的流式文档数据无损隐藏方法。将强化学习思想应用于流式文档数据排序中,通过将排序学习行为建模为马尔可夫决策过程,在每一次迭代的过程中根据全部排序位置信息,为各个排序位置选取最优的文档。经过排序后,通过基于曼彻斯特码的信息隐藏算法MSHA,改变流式文档数据中某些位置的跳变,完成信息嵌入,进而实现流式文档数据无损隐藏。仿真结果表明,所提方法不仅能够有效降低传输时延,同时还能够增加流式文档数据正确接收率和生命周期。The traditional streaming document data sorting method has defects,such as increased transmission delay,reduced life cycle and acceptance rate,being caused by the lack of streaming document data sorting.This paper presents a lossless hiding method of streaming document data based on sorting learning.The reinforcement of learning idea was applied to streaming document data sorting.The sorting learning behavior was modeled to form a Markov decision process.In the process of each iteration,the optimal document was selected for each sorting location according to all sorting location information.After sorting,the information hiding algorithm based on the Manchester code changed some positions of the streaming document data to complete the information embedding.Finally,the lossless hiding of the streaming document data was completed.The simulation results show that this method can reduce the transmission delay and increase the correct reception rate and life cycle of streaming document data.

关 键 词：排序学习 流式文档数据 无损隐藏 马尔可夫决策 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]