IfNot: An approach towards mitigating interest flooding attacks in Named Data Networking of Things

Abstract

Named Data Networking (NDN) has emerged as a model to accommodate content distribution, security, and mobility. Recently, NDN has been applied to the Internet of Things (IoT), referred to as Named Data Networking of Things (NDNoT). In the rapidly evolving landscape of the NDNoT securing data transmission is paramount. The main purpose and contribution of the research presented in this paper is to safeguard the security vulnerabilities of data transmission in NDNoT. This paper specifically addresses the critical issue of interest flooding attacks in NDNoT. These attacks can disrupt network operations posing far-reaching threats to data integrity and availability. To mitigate these attacks and threats the paper introduces the IfNoT mechanism and evaluates its performance through comprehensive simulations in a realistic and recognized simulator, called Cooja. IfNot identifies the potential interest flooding attacker nodes in the NDNoT environment. It reduces the impact of the attack and the undesirable interest traffic caused by such an attack, which optimizes the network resource utilization at a maximum level. The study also explores the influence of key parameters provided by the IfNoT mechanism. Moreover, the study also identifies optimum settings for these parameters to enhance network utilization. When evaluated using various metrics, including success rate, average latency, and total interest traffic, under different conditions and parameter settings, IfNoT was able to counter the interest flooding attacks effectively. IfNoT mechanism is able to increase success ratio up to 28%, decrease average latency up to 31%, and decrease total interest traffic up to 58%.