Defense against flooding attacks using probabilistic thresholds in the internet of things ecosystem
This addresses security vulnerabilities in IoT ecosystems, which is critical for protecting billions of connected devices, though it appears incremental as it builds on existing routing protocols and detection techniques.
The paper tackles flooding attacks in IoT networks by proposing LSFA-IoT, a method that detects attacks through physical layer intrusion and APT-RREQ messages, resulting in improved false positive rate, false negative rate, detection rate, and packet delivery rate compared to existing methods like REATO and IRAD.
The Internet of Things (IoT) ecosystem allows communication between billions of devices worldwide that are collecting data autonomously. The vast amount of data generated by these devices must be controlled totally securely. The centralized solutions are not capable of responding to these concerns due to security challenges problems. Thus, the Average Packet Transmission RREQ (APT-RREQ) as an effective solution, has been employed to overcome these concerns to allow for entirely secure communication between devices. In this paper, an approach called LSFA-IoT is proposed that protects the AODV routing protocol as well as the IoT network against flooding. The proposed method is divided into two main phases; The first phase includes a physical layer intrusion and attack detection system used to detect attacks, and the second phase involves detecting incorrect events through APT-RREQ messages. The simulation results indicated the superiority of the proposed method in terms of False Positive Rate (FPR), False Negative Rate (FPR), Detection Rate (DR), and Packet Delivery Rate (PDR) compared to REATO and IRAD. Also, the simulation results show how the proposed approach can significantly increase the security of each thing and network security.