A Survey of Interest Flooding Attack in Named-Data Networking: Taxonomy, Performance and Future Research Challenges. Issue 5 (3rd September 2022)

• Record Type: Journal Article
• Authors: Lee, Ren-Ting; Leau, Yu-Beng; Park, Yong Jin; Anbar, Mohammed
• Is Part Of: IETE technical review. Volume 39:Issue 5(2022)
• Page Start: 1027
• Page End: 1045
• Publication Date: 2022-09-03
• Subjects: Analogy metric -- Attack model -- CIFA -- Collusive interest flooding attack -- IFA -- Interest flooding attack -- Named-data networking -- NDN -- Taxonomy; Telecommunication -- Periodicals; Electronics -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/02564602.2021.1957029
• Languages: English
• ISSNs: 0256-4602

Abstract

ABSTRACT: Internet of Things (IoT) allows all entities such as computing devices, machines, objects, people, etc ., to interact with each other through their Internet Protocol (IP) addresses without human intervention. Consequently, IP addresses are being exhausted rapidly. Named-Data Networking (NDN) tends to transit the conventional host-centric network into the data-centric network. However, routing attacks such as Interest Flooding Attack (IFA) is a primary security concern. To date, far too little attention has been paid to classify the IFA detection mechanisms and further identify the key points to design an efficient detection technique. This study aimed to conduct a comprehensive survey of state-of-the-art IFA detection mechanisms and analysed the algorithms used. In this paper, we summarize the different types of possible attack models with a specific name with a description in NDN, specifically the PIT-oriented routing attack. Besides, we classified these mechanisms into nine categories with its topology used, analogy metrics and attack focus. Finally, we have highlighted and provide recommendations in some critical pieces of architecture in detection mechanism design as future challenges to secure the IoT data from IFA in NDN.