B2C Trading Platform Security Strategy Based on the Optimal Stopping Theory

In order to find out an optimal stopping rule for the B2C trading platform security risk, we propose a quantitative random process decision-making model. Two factors were regarded as independent variables which were investment for search security risk and profit of the B2C enterprise. In the same time, the optimal search times of enterprises’ B2C trading platform was a dependent variable, and the loss resulted by the B2C trading platform security risk as a random process. The existence of the optimal solution of this problem was proved, and the solution of the computer program was given, by which we can solve the problem conveniently. Therefore, the search times has strongly maneuverability. It also provides the theoretical and practical guidance for the safety decision-making of the B2C trading platform.

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