In DDoS attack (Distributed Denial of Service), an attacker gains control of many network users by a virus. Then the controlled users send many requests to a victim, leading to lack of its resources. DDoS attacks are hard to defend because of distributed nature, large scale and various attack techniques.One of possible ways of defense is to place sensors in the network that can detect and stop an unwanted request. However, such sensors are expensive so there is a natural question about a minimum number of sensors and their optimal placement to get the required level of safety.We present two mixed integer models for optimal sensor placement against DDoS attacks. Both models lead to a tradeoff between the number of deployed sensors and the volume of uncontrolled flow. Since above placement problems are NP-hard, two efficient heuristics are designed, implemented and compared experimentally with exact linear programming solvers.

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This paper addresses the comparison of algorithms for a version of the Network Utility Maximization (NUM) problem. The joint formulation of routing and transmission rate control within the multiuser and single-path setting is assumed within the NUM. Since the problem is NP-hard, the efficient heuristics are designed, implemented and compared experimentally with other existing heuristics and exact linear programming solver. The linear approximation is applied for a nonlinear utility function. The results of the experiments demonstrate a trade-off between computing time and precision of goal value.