Location based detection mechanism for PUEA on CR enabled 5G-IoT network

Cognitive radio (CR) enabled 5G massive machine-type communications (mMTC) is a prominent solution to establish and maintain efficient connections among millions of devices. The primary user emulation attack (PUEA) imperils the network performance in a large-scale CR-based 5G internet of things (5G-IoT) and causes bandwidth wastage, severe interference to PU transmission, etc. Thus, a novel approach is proposed to detect the emulation attacks in the CR-enabled 5G-IoT network, and it has two main procedures. In the first approach, each SU finds the transmitter's location and shares its location information with the legitimate SUs. Each SU uses the transmitter's received signal strength and location coordinates of nearby receivers to localize the transmitter. In the second approach, each SU can receive signal energy vectors of users during sensing time and store them in the database. Whenever any new node appears, it compares with stored information and finds malicious nodes to store in the database. The adversary is detected based on the closeness of the newly received energy vector and the stored energy vectors in the database. The simulation results demonstrated significant of the proposed mechanism.