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.

摘要

物联网 (IoT) 允许所有实体，例如计算设备、机器、对象、人等., 在没有人为干预的情况下通过他们的 Internet 协议 (IP) 地址相互交互。因此，IP 地址正在迅速耗尽。命名数据网络（NDN）倾向于将传统的以主机为中心的网络转变为以数据为中心的网络。然而，兴趣包泛滥攻击 (IFA) 等路由攻击是一个主要的安全问题。迄今为止，对 IFA 检测机制的分类和进一步确定设计有效检测技术的关键点的关注太少。本研究旨在对最先进的 IFA 检测机制进行全面调查，并分析所使用的算法。在本文中，我们总结了不同类型的可能的攻击模型，并在 NDN 中进行了描述，具体名称为 PIT-oriented routing attack。除了，我们根据使用的拓扑结构、类比指标和攻击重点将这些机制分为九类。最后，我们强调并提供了检测机制设计中一些关键架构部分的建议，作为未来在 NDN 中保护来自 IFA 的物联网数据的挑战。