Security Analysis of Enterprise Network
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2009 proceedings
Security Analysis of Enterprise Network Based on
Stochastic Game Nets Model
Yuanzhuo Wang, Chuang Lin, Senior Member, IEEE, Yang Wang, Kun Meng
Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
Email: {yzwang, clin, ywang, mengkun08}@csnet1.cs.tsinghua.edu.cn
Abstract—In this paper, we propose a novel modeling method,
Stochastic Game Nets (SGN), and use it to model and analyze the security issues in enterprise networks. Firstly, the definition and modeling algorithm of Stochastic Game Nets are given. And then we apply the Stochastic Game Nets method to describe the attack and defense course in the enterprise networks successfully, and find a Nash equilibrium. Finally we analyze the confidentiality and integrity of the enterprise network quantificationally based on the model. The method can also be applied to other areas with respect to a game.
Keywords- Stochastic Game Net, Enterprise Network, Security
Analysis, Integrality, Confidentiality.
I.
INTRODUCTION
Enterprise networks interconnect islands of departmental, local and remote computing and communication resources.
They provide many benefits to organizations using them, such as the enhancement of efficiency, allowing employees greater flexibility in their work habits etc. As the role of enterprise networks, they are keeping expanding in theirs support of both internal and external connectivity in the form of emerging internet, intranet and extranet applications. Unfortunately, owing to all kinds of reasons, the networks always are under the hazard of illegal intrusion. This has given rise to the dichotomy faced by those partaking in the information economy paradigm. Security has become an ever increasingly critical element for enterprise network design and
implementation.
Security Analysis of Enterprise Network Based on
Stochastic Game Nets Model
Yuanzhuo Wang, Chuang Lin, Senior Member, IEEE, Yang Wang, Kun Meng
Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
Email: {yzwang, clin, ywang, mengkun08}@csnet1.cs.tsinghua.edu.cn
Abstract—In this paper, we propose a novel modeling method,
Stochastic Game Nets (SGN), and use it to model and analyze the security issues in enterprise networks. Firstly, the definition and modeling algorithm of Stochastic Game Nets are given. And then we apply the Stochastic Game Nets method to describe the attack and defense course in the enterprise networks successfully, and find a Nash equilibrium. Finally we analyze the confidentiality and integrity of the enterprise network quantificationally based on the model. The method can also be applied to other areas with respect to a game.
Keywords- Stochastic Game Net, Enterprise Network, Security
Analysis, Integrality, Confidentiality.
I.
INTRODUCTION
Enterprise networks interconnect islands of departmental, local and remote computing and communication resources.
They provide many benefits to organizations using them, such as the enhancement of efficiency, allowing employees greater flexibility in their work habits etc. As the role of enterprise networks, they are keeping expanding in theirs support of both internal and external connectivity in the form of emerging internet, intranet and extranet applications. Unfortunately, owing to all kinds of reasons, the networks always are under the hazard of illegal intrusion. This has given rise to the dichotomy faced by those partaking in the information economy paradigm. Security has become an ever increasingly critical element for enterprise network design and
implementation.
References: and Secure Computing,1(1), 2004. Computer Security Foundations Workshop, 2002. Computer Security Foundations Workshop, 2005. [8] R. Browne. C4i defensive infrastructure for survivability against multimode attacks. In Proceedings of 21st Century Military CommunicationArchitectures and Technologies for Information Superiority, 2000. Springer-Verlag, New York, 1996.