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Dive into the research topics where Jindong Wang is active.

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Featured researches published by Jindong Wang.


international conference on computer science and network technology | 2011

A grid resource matching algorithm

Qiang Guo; Jindong Wang; Hengwei Zhang; Na Wang

Resource matching is one of the core functions of the grid resource management. Currently, the resource matching algorithm is mainly divided into two categories: the performance indicated matching algorithm and the cost indicated matching algorithm. This paper use correlation matrix designed a performance and cost constrained resource matching algorithm, which based on weighted Euclidean distance. The matlab simulation results show that the algorithm can effectively find the matched resource out in the network environment.


pacific-asia conference on circuits, communications and systems | 2011

HRMF-G: A Grid-Based Hierarchical Resource Management Framework

Kun Wang; Qiang Guo; Hengwei Zhang; Jindong Wang

Grid resource management is a core component of the grid. This paper analyzes the characteristics of the grid, and designed a Hierarchical Resource Management Framework for data resource in grid(HRMF-G). For the characteristics of the grid and the existing shortage of hierarchical resource management, we improved, respectively, the resource management domain model by Wang Hong et al, the multi-level resource schedule model by Zeren Zhima et al and the general resource manager by Klaus Krauter et al. And then applies them to the HRMF-G.


international symposium on intelligent information technology and security informatics | 2010

An Intelligent Security Defensive Software Scheme and Realization

Kun Wang; Jindong Wang; Liuqing Shen; Zhen-hua Han

The existing security defensive systems, which have limitations in many ways, can not adapt to the need of future network defense. In allusion to the problem, an intelligent security defensive software is designed. It has intelligent functions such as environment awareness, self-adaptation, dynamic reconstruction, and so on. Besides, the general realization methods are proposed herein.


international seminar on business and information management | 2008

The Research and Design of the Intelligent Security Defendable Software's Cooperative Framework

Jindong Wang; Wei-Wei Cao; Kun Wang; Hengwei Zhang

Coordinated defense is one of network security technology development directions, and how to make security systems work cooperatively is a critical problem. So uniform coordinated working mechanisms and policies are necessary. In Intelligent Security Defendable Software (ISDS), Execution Components can work cooperatively and implement coordinated tasks, and they need uniform commands. Hence coordinated-control has become very critical to ISDS. In order to make components in ISDS work cooperatively, combining with the characteristics of ISDS, a cooperative framework is presented in this paper, and the design of the Command Component (CC)is discussed in particular. The framework combines component technology, cooperative working and artificial intelligent, which has security, cooperatively and extensibility.


ieee advanced information technology electronic and automation control conference | 2017

Network defense strategy selection based on best-response dynamic evolutionary game model

Jianming Huang; Jindong Wang; Hengwei Zhang; Na Wang

Since traditional game theory applying to network attack and defense has the restriction of complete rational, we establish non-cooperative evolutionary game model of network attack and defense on the premise of bounded rationality, and solved by the replicator dynamic equations. For the strategy learning evolution process of defender, we use the Best-response dynamic learning mechanism to establish the dynamic evolutionary game model between defenders, which can analyze the dynamic evolution process and defense evolution equilibrium point of defending strategy selection. Then, we summarize the evolution laws of network defense strategy selection under bounded rationality. The validity of the model and method is validated by system simulation.


IEEE Access | 2017

Markov Evolutionary Games for Network Defense Strategy Selection

Jianming Huang; Hengwei Zhang; Jindong Wang

Since the characteristics of opposite objectives, non-cooperation relationship, and dependent strategies of network attack and defense are highly consistent with game theory, researching the decision-making methods of network defense and applying the game models to analyze the network attack–defense behaviors has been of concern in recent years. However, most of the research achievements regarding to the game models are based on the hypothesis that both the two sides’ players are completely rational, which is hard to meet. Therefore, we combined the evolutionary game theory and Markov decision-making process to construct a multi-stage Markov evolutionary game model for network attack–defense analysis, in view of the bounded rationality constraint. The model, based on the non-cooperative evolutionary game theory, could accomplish dynamic analysis and deduction for the multi-stage and multi-state network attack–defense process. In addition, an objective function with discounted total payoffs was designed by analyzing payoff characteristics of the multi-stage evolutionary game, which is more consistent with the reality of network attack and defense. Besides, the solving method for multi-stage game equilibrium was proposed on the basis of calculating the single-stage evolutionary game equilibrium. In addition, an algorithm for optimal defense strategy of the multi-stage evolutionary games was given. Finally, the experiments showed the high effectiveness and validity of the model and method that has a guiding significance for the network attack and defense.


Third International Conference on Cyberspace Technology (CCT 2015) | 2015

Research for modeling network security based on attack-defense grapy of state reduction

Jindong Wang; Hengwei Zhang; Na Wang; Tao Li

In order to assess network security threats better, we model the attackers and defenders behavior based on attack-defense graph from the perspective of both attacker and defender, which lays the foundation of the further research for the scientific and precise information security threat assessment. Due to the existing problems of generating traditional attack-defense graph (e.g. explosion of state space, and the large-scale and complex generation of attack-defense graph), we in this paper propose a method for generating attack-defense graph based on state reduction, then we model the behavior of attacker and defender in network security. Finally, the method and the model proposed in this paper are proved to be scientific and effective within a typical network scenario.


international conference on computer science and network technology | 2011

Design of a resource selection approach in grid

Jindong Wang; Qiang Guo; Hengwei Zhang; Jian Zhang

Resource selection is the premise and foundation to ensure the quality of resource scheduling in grid. Accurate resource reliability risk, credibility, and real-time load filter can effectively ensure the success rate of users job. This paper use the historical information of resources, combined with real-time load of resources, designed a new resource selection approach in grid. Simulation experiments show that this approach can effectively select the available resource set, improve the quality of resource scheduling and reduce the failure rate of grid job.


international conference on computer engineering and technology | 2010

An intelligent security defensive software

Kun Wang; Jindong Wang; Liuqing Shen; Na Wang

The existing security defensive systems, which have limitations in many ways, can not adapt to the need of future network defense. In allusion to the problem, an intelligent security defensive software is designed. It has intelligent functions such as environment awareness, self-adaptation, dynamic reconstruction, and so on.


international conference on intelligent computation technology and automation | 2009

The Design of Intelligent Security Defensive Software Based on Autonomic Computing

Liuqing Shen; Jindong Wang; Kun Wang; Hengwei Zhang

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