数据的机密性是云存储环境下的难点问题,基于密文的访问控制技术是解决该问题的重要思路,在目前的基于密文的访问控制技术中,数据的高安全需求和频繁的策略更新使得数据拥有者(data owner,DO)端的权限更新代价过高,进而严重制约了系统的整体效率.针对此问题,提出一种适用于云存储动态策略的密文访问控制方法(cryptographic access control strategy for dynamic policy,CACDP),该方法提出了一种基于二叉Trie树的密钥管理机制,在此基础之上利用基于ELGamal的代理重加密机制和双层加密策略,将密钥和数据更新的部分开销转移到云端以减少DO权限管理负担,提高DO的处理效率.最后通过实验验证了该方案有效降低了策略更新为DO带来的性能开销.
MSU Stego Video is a public video steganographic tool, which has strong robustness and is regarded as a real video steganographic tool. In order to increase the detection rate, this paper proposes a new steganoalysis method against MSU, which uses the chessboard character of MSU embedded video, proposes a down-sample block-based collusion method to estimate the original frame and checks the chessboard mode of the different frame between tested frame and estimated frame to detect MSU steganographic evidences. To reduce the error introduced by severe movement of the video content, a method that abandons severe motion blocks from detecting is proposed. The experiment results show that the false negative rate of the proposed algorithm is lower than 5%, and the false positive rate is lower than 2%. Our algorithm has significantly better performance than existing algorithms. Especially to the video that has fast motion, the algorithm has more remarkable performance.
