Biblio
Based on Markov chain analysis method, the situation prediction of smart grid security and stability can be judged in this paper. First component state transition probability matrix and component state prediction were defined. A fast derivation method of Markov state transition probability matrix using in system state prediction was proposed. The Matlab program using this method was compiled to analyze and obtain the future state probability distribution of grid system. As a comparison the system state distribution was simulated based on sequential Monte Carlo method, which was in good agreement with the state transition matrix, and the validity of the method was verified. Furthermore, the situation prediction of the six-node example was analyzed, which provided an effective prediction and analysis tool for the security situation.
The Cramer-Shoup cryptosystem has attracted much attention from the research community, mainly due to its efficiency in encryption/decryption, as well as the provable reductions of security against adaptively chosen ciphertext attacks in the standard model. At TCC 2005, Vasco et al. proposed a method for building Cramer-Shoup like cryptosystem over non-abelian groups and raised an open problem for finding a secure instantiation. Based on this work, we present another general framework for constructing Cramer-Shoup like cryptosystems. We firstly propose the concept of index exchangeable family (IEF) and an abstract construction of Cramer-Shoup like encryption scheme over IEF. The concrete instantiations of IEF are then derived from some reasonable hardness assumptions over abelian groups as well as non-abelian groups, respectively. These instantiations ultimately lead to simple yet efficient constructions of Cramer-Shoup like cryptosystems, including new non-abelian analogies that can be potential solutions to Vasco et al.'s open problem. Moreover, we propose a secure outsourcing method for the encryption of the non-abelian analog based on the factorization problem over non-commutative groups. The experiments clearly indicate that the computational cost of our outsourcing scheme can be significantly reduced thanks to the load sharing with cloud datacenter servers.