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Hunan, China

Zhang B.Y.,Hunan Police Academy
Applied Mechanics and Materials | Year: 2014

This paper describes the basic models of network security state evaluation system and concentrates on researching the situation assessment method with stochastic model. In the paper, which makes use of the Hidden Semi-Markov Model (HsMM), tries to simulate the operation of network system. The alert statistics, deriving from network defense system, is used as data sources to realize the evaluation of network security situation. HsMM modifies the HMM model concerning the hypothesis of some state-duration time in relation to exponential distribution, which coincides the description of the network system's operation in the real world. The experimental results imply that HsMM is an ideal security evaluation method. © (2014) Trans Tech Publications, Switzerland. Source

Zhao W.,Hunan Police Academy | Wang N.,National University of Defense Technology
Applied Mechanics and Materials | Year: 2013

In this paper, a novel framework as a combination of Probability Collectives (PC) and Collaborative Optimization (CO) is proposed and detailed illustrated. The framework has a two-level structure which is similar to that of CO, but with the system level replaced by distributed PC based agents. This formulation maintains the advantage of CO while enhances the optimization and coordination ability at the system level. For better implementation, some adaption and improvement has been made to the origin PC method. The resultant PCCO framework shows satisfied performance in handling complex optimization problems with both efficiency and accuracy. © (2013)Trans Tech Publications, Switzerland. Source

Yan X.,Hunan Police Academy
Journal of Convergence Information Technology | Year: 2011

The increasing network attacks reveal one of the fundamental security problems, this paper proposes against denial of services based on packet limiting algorithm. It has presented algorithms that help to detect and stop attacks and to trace the path to the attacker for obvious reasons. The algorithm tracks packet rates to and from subnets, then determine the route path. Experimental result shows that the proposed algorithm is effective. Source

Yan X.,Hunan Police Academy
Proceedings - 2011 International Conference on Future Computer Sciences and Application, ICFCSA 2011 | Year: 2011

In view that the efficiency of computer forensics technology is insufficient and some other problems at present, a computer dynamic forensics method has been proposed based on BP neural network. This method has combined the advantages of artificial neural network in pattern recognition which can timely and accurately identify the network attack behaviors. On this basis, a prototype system with dynamic forensics has been designed. And the experiment has showed that this system has high detection rate for the network bad behaviors and the detection performance is superior to other pattern recognition methods. © 2011 IEEE. Source

Liu W.-Y.,Hunan Police Academy | Liu W.-Y.,National University of Defense Technology
Journal of Computational and Theoretical Nanoscience | Year: 2016

According to the disposal demand for packets and all kinds of constraints in the current condition, this paper discusses a modeling method of extended double-layer capacitated arc routing problems (Capacitated Arc Routing Problem, CARP) optimization model based on express logistics. The model is described in detail, and the solution of the model is discussed. The paper analyses and discusses the solution to complexity of the model, and proposes a better solution to the doublelayer CARP optimization model. According to the scheme, the paper chooses a sort of improved ant colony algorithm to solve the model. And the results show that the scheme is beneficial to controlling the cost of logistics links, to minimizing purchase cost, transportation cost and delivery time. The scheme plays a very imperative role in enhancing the competitiveness of enterprises. © 2016 American Scientific Publishers All rights reserved. Source

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