基于污染数据分析实现LSB秘密消息的检测

信息隐藏技术已经成为网络信息安全的一个重要研究方向，如何有效地监控和检测网络中传递的秘密消息对于保障国家安全具有重要的现实意义．针对互联网上大量的隐写软件利用彩色厦灰度图像的最低有效比特位（LSB）隐藏秘密消息，基于污染数据分析，提出了一种新的隐写分析方法，并给出了此算法的数学模型．该方法不仅可以快速有效地检测出图像中秘密消息的存在性，同时还可以精确地估计出连续及随机间隔嵌入算法下所嵌入秘密消息的长度．

Detection of Secret Message in Spatial LSB Steganography Based on Contaminated Data Analysis

Information hiding technique is of great importance for network information security and how to search and detect secret messages transferred in network is crucial and practical to safeguard the national security. On Internet, a large number of steganographic programs use the least significant bit (LSB) embedding to hide message in digital images. Based on contaminated data analysis, a new steganalytic technique capable of a reliable detection of spatial LSB steganography is proposed and its mathematical model is built . This method can not only detect the existence of hidden messages embedded in images fast and reliably, but also estimate accurately the amount of hidden messages embedded by using a sequentially or randomly scattered algorithm.