In a DDoS attack (Distributed Denial of Service), an attacker gains control of many network users through a virus. Then the controlled users send many requests to a victim, leading to its resources being depleted. DDoS attacks are hard to defend because of their distributed nature, large scale and various attack techniques. One possible mode of defense is to place sensors in a network that can detect and stop an unwanted request. However, such sensors are expensive so there is a natural question as to the minimum number of sensors and the optimal placement required to get the necessary level of safety. Presented below are two mixed integer models for optimal sensor placement against DDoS attacks. Both models lead to a trade-off between the number of deployed sensors and the volume of uncontrolled flow. Since the above placement problems are NP-hard, two efficient heuristics are designed, implemented and compared experimentally with exact mixed integer linear programming solvers.
翻译:在DDoS攻击(分散拒绝服务)中,攻击者通过病毒控制了许多网络用户。然后受控制的用户向受害者发出许多请求,导致其资源耗尽。DDoS攻击由于其分布性、规模大和各种攻击技术而难以防御。一种可能的防御方式是将传感器置于一个能够探测和阻止不想要的要求的网络中。然而,这种传感器费用昂贵,因此自然要问的是,传感器的最低数量和获得必要安全水平所需的最佳位置。下面是两种混合的组合式传感器模型,用于对DDoS攻击的最佳定位。两种模型都导致部署传感器的数量与不受控制的流量之间的权衡。由于上述安置问题是NP硬的,因此设计、实施和实验性地比较了两种高效的超自然现象,与精确的混合整线性编程编程解算器。