高阶隐写直觉模糊集距离安全性测度

在隐写安全性研究滞后于隐写算法发展的前提下,隐写安全性研究成为亟待解决的问题。根据隐写通信过程的模糊不确定性,对隐写数据采用n阶Markov链建模,提出了隐写系统直觉模糊集距离安全性测度,并证明了该安全性测度的有界性、交换性和一致性。仿真实验表明,该安全性测度具有对不同隐写算法的度量区分能力。与确定模式下安全性相比较,在相同数据统计模型下,直觉模糊集距离安全性测度获得了更全面的隐蔽性评价。

HIGH-ORDER STEGANOGRAPHY SECURITY EVALUATION BASED ON INTUITIONISTIC FUZZY SET DISTANCE

Given that the research on steganography security evaluation lags back the development of steganography algorithm, it is an urgent problem for the study of steganography security evaluation. In this paper, according to the indeterminacy of seteganographic communication, the stego data are modeled as n-order Markov model, and a novel security evaluation in terms of intuitionistic fuzzy set distance is introduced for stganographic system. Furthermore, the security evaluation is proved to have the properties of boundedness, symmetric and uniform. The experimental results show that the proposed security evaluation can distinguish the security of the different steganographies. In addition, compared with the deterministic security evaluations under the same distribution model, the proposed security evaluations obtain a better estimate of the divergence between the cover images and stego images.