Mitigating Security Attacks in Spectrum Allocation in Cognitive Radio Networks

Current channel assignment techniques rely on the nodes’s decent nature and lack of malicious intent. The accuracy of the information disseminated by the nodes is not confirmed because it is based on an assumption of trust. Furthermore, in distributed channel assignment methods, each node chooses their spectrum allocation independently and notifies its neighbours of the choice, which is also unreliable. Due to its autonomous decision-making and lack of validation, a node is susceptible to three different kinds of channel assignment attacks: Channel Ecto-Parasite Attack (CEPA), Network Endo-Parasite Attack (NEPA), and LOw cost Ripple effect Attack (LORA). In this paper, we present a detection technique for distributed Cognitive Radio Network named “Smart Neighbour Mechanism” that detects attacks that occur in spectrum assignment, such as CEPA, NEPA and LORA. The suggested security technique is based on the idea of using neighbour monitoring to detect malignant users within the system, protecting it from security risks that take advantage of channel assignment problems. Additionally, we conduct simulation-based studies to illustrate the efficacy of our proposed technique.