A differential game method against attacks in heterogeneous honeynet

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The use of honeynet has become relatively common for security researchers and network operators to improve the network security. Thus, study of decision-making against attacks in a heterogeneous honeynet is significantly important for improving the design of honeynet and effectively preventing attacks. This paper establishes a dynamic node-evolutive model under attacks by considering the inherent characteristics and the functional interaction between ordinary nodes and honeypots, based on which the decision-making problem is modeled as a differential game. The existence of the saddle-point involved in the game is validated and the optimal dynamic strategies for the honeynet system and attackers are obtained through the proposed algorithm. The obtained optimal strategies are verified using several random strategies. The effects of the network topology and attack duration on the strategies for both sides and on the overall attack effect are evaluated. The key findings are: a) strategic decision-making should be closely related to the node degree. Specifically, the higher-degree node adapts attack or capture strategy in preference to the lower-degree one, in contrast to the patching strategy. b) a honeynet with higher power-law exponent is beneficial to eliminate attack effects, whereas a higher attack duration can aggravate these effects. The obtained results provide a theoretical foundation to improve the design of honeynet and restrain honeynet attacks.