Securing SDN Data Plane:Investigating the effects of IP SpoofingAttacks on SDN Switches and its Mitigation : Simulation of IP spoofing using Mininet

Sammanfattning: Background:Software-Defined Networking (SDN) represents a network architecture that offers a separate control and data layer, facilitating its rapid deployment and utilization for diverse purposes. However, despite its ease of implementation, SDN is susceptible to numerous security attacks, primarily stemming from its centralized nature. Among these threats, Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks pose the most substantial risks. In the event of a successful attack on the SDNcontroller, the entire network may suffer significant disruption. Hence, safe guarding the controller becomes crucial to ensure the integrity and availability of the SDN network. Objectives:This thesis focuses on examining the IP spoofing attack and its impact on the Data Plane, particularly concerning the metrics of an SDN switch. The investigation centers around attacks that manipulate flow-rules to amplify the number of rules and deplete the resources of a switch within the Data Plane of an SDN network. To conduct the study, a software-defined network architecture was constructed using Mininet, with a Ryu controller employed for managing network operations. Various experiments were carried out to observe the response of the SDN system when subjected to an IP spoofing attack, aiming to identify potential mitigation strategies against such threats. Method and Results: To simulate the resource exhaustion scenario on the SDN network’s Data Plane,we deliberately triggered an escalation in the number of flow-rules installed in the switch. This was achieved by sending packets with spoofed IP addresses, there by exploiting the switch’s limited resources. Specifically, we focused on monitoring the impact on CPU utilization, storage memory, latency, and throughput within the switch. Detailed findings were presented in the form of tables, accompanied by graphical representations to visually illustrate the effects of increasing flow rules on the switches. Furthermore, we explored potential mitigation measures by developing an application that actively monitors the flow rules on the Ryu controller, aiming to detect and counteract such resource-exhausting effects.