# Interest Flooding Attacks in Named Data Networking and Mitigations: Recent Advances and Challenges
## 1 Introduction  
The existing Internet architecture was initially designed as a host-centric communication model, focusing on end-to-end connectivity between specific devices through InternetProtocol (IP) addresses. Although Internet architecture has served well for decades, the explosive growth of content distribution, mobile connectivity, and the emerging Internet of Things (IoT) has created fundamental mismatches between how users consume content and how the underlying network operates [1]. Today's Internet usage is predominantly centered on content retrieval rather than host-to-host communication, with applications such as video streaming, social networks, and content sharing dominating traffic patterns [2]. To address these challenges, Information-Centric Networking (ICN) has emerged as a promising paradigm for future Internet architecture, shifting focus from \"where\" content is located to \"what\" content is requested [3]. ICN moves away from traditional host-to-host communication, instead prioritizing Named Content Retrieval (NCR). NCR allows for in-network caching, faster content delivery, and better support for mobile users [4]. Named Data Networking (NDN) represents one of the most active and mature ICN implementations, designed as a clean-slate approach to revolutionize network architecture by making content names the cornerstone of communication [5; 6]. Rather than by IP address, in NDN, users request content by name using interest packets, and the network delivers data packets that carry that content back along the reverse path, regardless of which node provides it [6]. NDN change improves caching, mobility, and security at the data level but brings new risks. Since the network keeps track of pending requests, attackers can exploit how interest and data packets are processed and forwarded [7]. Interest Flooding Attacks (IFAs) represent a significant threat to distributed denial-of-service (DDoS) attacks in NDN, where adversaries generate a large volume of malicious interest packets to disrupt normal network functions [8]. Since NDN routers maintain a Pending Interest Table (PIT) to track data requests, excessive unsolicited interests can rapidly exhaust memory resources, leading to packet loss and service degradation [7]. In severe cases, legitimate requests are completely blocked, preventing access to valid content. IFA differs from conventional DoS attacks by targeting the request handling process rather than overwhelming a server with data packets. Attackers inject a substantial number of interest packets for non-existent or unsatisfiable content, causing a continuous expansion of PIT entries that depletes processing capacity [9]. This degradation occurs without requiring high bandwidth, making the attack particularly effective in resource-constrained environments such as the Internet of Things [10]. Various countermeasures have been proposed, including rate limiting, PIT management, and anomaly detection [11]. As NDN architectures gain increasing attention, securing them against IFAs has become a critical area, with many ongoing efforts focused on developing scalable and adaptive defense mechanisms. Compared to earlier reviews [8; 11], which emphasize classification and high-level summaries, this survey offers a more deployment-focused perspective. By examining recent detection strategies through the lens of computational cost, scalability, and adaptability across different application domains, the paper provides a practical reference for researchers aiming to implement or expand IFA defenses in real networks. Its emphasis on domain-specific implementation trade-offs, particularly in IoT and edge computing, distinguishes this work. This survey provides a comprehensive and up-to-date analysis of IFA in NDN, with a particular focus on research advances over the past five years. Our contributions are as follows.