.设计了一种在图形处理器(GPU)上的彩虹表密钥分析算法.结合GPU单指令多线程的特点改进了Oechslin的彩虹表算法,将预处理中彩虹链的计算分别映射到GPU的单个线程,并利用预计算链提高了在线分析的效率.所使用的硬件平台GPU Tesla C1060相对于CPU Core2 Duo2.8 GHz,在运行速度方面,预处理提高了41.2倍(每秒110×106次DES加密),在线分析提高了3.52倍.在此系统上用1.3 GB的磁盘空间,平均2.73 s的在线分析时间以及46%的概率,成功获得了加密选择明文的40 bit DES密钥.
In this paper, we propose a new notion of secure disguisable symmetric encryption schemes, which captures the idea that the attacker can decrypt an encrypted fie to different meaningful values when different keys are put to the decryption algorithm. This notion is aimed for the following anti-forensics purpose： the attacker can cheat the forensics investigator by decrypting an encrypted file to a meaningful file other than that one he encrypted, in the case that he is caught by the forensics investigator and ordered to hand over the key for decryption. We then present a construction of secure disguisable symmetric encryption schemes.
