Abstract
DDoS attacks deplete network bandwidth and render the services unavailable to normal users. In spite of various qualitative and rule based defense mechanisms, the threat persists continuously because such mechanisms do not capture the incentive oriented attacker’s intentions. Game theory promises to provide incentive based decision support system to defend against such attacks. The current work proposes a defense mechanism designed as two player zero sum finite horizon repeated game where decisions to allow or drop an incoming traffic at edge router are taken based on a flow-rate threshold. The flow-rate threshold is dynamically adjusted and updated based on maximum payoff obtained by the defender at a particular stage of the game. Payoff is computed by quantifying network conditions and parameters. The normal and attack traffic are modelled using normal and poisson distribution functions respectively. Using these functions, drop and pass probabilities of flows are computed. Further, costs and benefits in respect of the attacker and defender are computed based on the bandwidth utilized by the flows. Subsequently, payoff functions are designed for attacker and defender. Payoff functions are optimized to construct baseline optimal strategies. Nash Equilibrium is obtained using numerical computations which suggests an optimal flow-rate threshold to be set by the defender to secure the network against DDoS attacks round the clock.
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Kumar, B., Bhuyan, B. (2021). Game Theoretical Defense Mechanism Against Bandwidth Based DDoS Attacks. In: Maji, A.K., Saha, G., Das, S., Basu, S., Tavares, J.M.R.S. (eds) Proceedings of the International Conference on Computing and Communication Systems. Lecture Notes in Networks and Systems, vol 170. Springer, Singapore. https://doi.org/10.1007/978-981-33-4084-8_58
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