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Research Article | Open Access |

A Game Theoretic Framework for E-Mail Detection and Forgery Analysis

Author 1: Long Chen Author 2: Yuan Lou Author 3: Min Xiao Author 4: Zhen-Xing Dong
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 1 · Published 2016

DOI: https://doi.org/10.14569/IJACSA.2016.070126

Abstract

In email forensic, the email detection and forgery conflict is an interdependent strategy selection process, and there exists complex dynamics between the detector and the forger, who have conflicting objectives and influence each other’s performance and decisions. This paper aims to study their dynamics from the perspective of game theory .We firstly analyze the email basic structure and header information, then discuss the email detection and forgery technologies. In this paper, we propose a Detection-Forgery Game (DFG) model and make a classification of players’ strategy with the Operation Complexity (OC). In the DFG model, we regard the interactions between the detector and the forger as a two-player, non-cooperative, non-zero-sum and finite strategic game, and formulate the Nash Equilibrium. The optimal detection and forgery strategies with minimizing cost and maximizing reward will be found by using the model. Finally, we perform empirical experiments to verify the effectiveness and feasibility of the model.

Keywords

How to Cite this Article

Chen, L., Lou, Y., Xiao, M., & Dong, Z. (2016). A Game Theoretic Framework for E-Mail Detection and Forgery Analysis. International Journal of Advanced Computer Science and Applications, 7(1). https://doi.org/10.14569/IJACSA.2016.070126

Chen, Long, et al.. "A Game Theoretic Framework for E-Mail Detection and Forgery Analysis." International Journal of Advanced Computer Science and Applications, vol. 7, no. 1, 2016, https://doi.org/10.14569/IJACSA.2016.070126.

@article{Chen2016,
  title     = {A Game Theoretic Framework for E-Mail Detection and Forgery Analysis},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {1},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Long Chen and Yuan Lou and Min Xiao and Zhen-Xing Dong},
  doi       = {10.14569/IJACSA.2016.070126},
  url       = {https://doi.org/10.14569/IJACSA.2016.070126}
}

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