Despite the highly secure content sharing and the optimized forwarding mechanism, the content delivery in a Named Data Network (NDN) still suffers from numerous vulnerabilities that can be exploited to reduce the efficiency of such architecture. Malicious attacks in NDN have become more sophisticated and the foremost challenge is to identify unknown and obfuscated malware, as the malware authors use different evasion techniques for information concealing to prevent detection by an Intrusion Detection System (IDS). For the most part, NDN faces immense negative impacts from attacks such as Cache Pollution Attacks (CPA), Cache Privacy Attacks, Cache Poisoning Attacks, and Interest Flooding Attacks (IFA), that target different security components, including availability, integrity, and confidentiality. This poses a critical challenge to the design of IDS in NDN. This paper provides the latest taxonomy, together with a review of the significant research works on IDSs up to the present time, and a classification of the proposed systems according to the taxonomy. It provides a structured and comprehensive overview of the existing IDSs so that a researcher can create an even better mechanism for the previously mentioned attacks. This paper discusses the limits of the techniques applied to design IDSs with recent findings that can be further exploited in order to optimize those detection and mitigation mechanisms.

Named Data Networking (NDN), one of the most suitable candidates for the future Internet architecture, allows all network nodes to have a local cache that is used to serve incoming content requests. Content caching is an essential component in NDN: content is cached in routers and used for future requests in order to reduce bandwidth consumption and improve data delivery speed. Moreover, NDN introduces new self-certifying contents features that obviously improve data security and make NDN a secured-by-design architecture able to support an efficient and secure content distribution at a global scale. However, basic NDN security mechanisms, such as signatures and encryption, are not sufficient to ensure security in these networks. Indeed, the availability of the Data in several caches in the network allows malicious nodes to perform attacks that are relatively easy to implement and very effective. Such attacks include Cache Pollution Attacks (CPA), Cache Privacy Attacks, Content Poisoning Attacks and Interest Flooding Attacks. In this paper, we identify the different attack models that can disrupt the NDN operation. We conducted several simulations on NDNSim to assess the impact of the Cache Pollution Attack on the performance of a Named Data Network. More precisely, we implemented different attack scenarios and analyzed their impact in terms of cache hit ratio, data retrieval delay and hit damage ratio.