# Interest Flooding Attacks in Named Data Networking and Mitigations: Recent Advances and Challenges
## 2 NDN Architecture and Vulnerability to Interest Flooding
### Interest Flooding Attack Vulnerability Analysis  
The architectural features that enable NDN's content-centric benefits also create specific attack vectors that distinguish Interest Flooding Attacks from traditional denial-of-service methods. Understanding these vulnerabilities requires examination of how NDN's design principles interact with malicious traffic patterns and resource consumption behaviors.  
1. **PIT Resource Exhaustion Mechanisms:** The finite capacity of PIT represents the main vulnerability target in IFA. Each interest packet consumes a PIT entry until either a corresponding data packet arrives or the entry is canceled due to unfilled requests. Attackers can exploit the PIT consuming mechanism by generating large volumes of interest packets for non-existent or deliberately unsatisfiable content, causing PIT entries to accumulate until router memory resources are exhausted [11; 16]. The packet exhaustion prevents legitimate interest packets from receiving PIT entries, effectively denying service to legitimate users without requiring the high bandwidth consumption typically associated with traditional flooding attacks.
2. **Pull-Based Communication Exploitation:** NDN's pull-based model ensures that data flows through the network only upon explicit request through interest packets. Although this design improves control over data dissemination and mitigates specific unsolicited data delivery attacks, it creates opportunities for abuse through interest  
Figure 1: NDN forwarding architecture.  
manipulation [17]. Attackers can generate high volumes of interest packets for non-existent or rarely accessed content, knowing these requests cannot be satisfied with existing data packets. The resulting accumulation of unsatisfiable interests leads to resource exhaustion and degraded service for legitimate network users [18].
3. **Stateful Forwarding Vulnerabilities:** The distinction between NDN's stateful forwarding and traditional IP routing creates unique attack opportunities. Conventional IP networks maintain minimal per-packet state, making them less susceptible to state exhaustion attacks. NDN routers must maintain detailed information about each forwarded interest packet, including content names and interface mappings, until the corresponding data packet completes the transaction [19; 20]. The persistent state maintenance requirement enables attackers to consume router resources through coordinated interest flooding without requiring successful data retrieval or high bandwidth utilization.  
Several mitigation approaches have emerged to address these vulnerabilities. Cryptographic route tokens provide mechanisms to validate interest packets and ensure that only legitimate requests consume PIT resources [18]. Advanced detection methods combining Exponential Weighted Moving Average (EWMA) algorithms with logistic regression techniques focus on identifying malicious prefixes while reducing network disruption [21] or reducing memory consumption and preserving legitimate traffic [22]. Real-time detection systems employing Artificial Neural Networks (ANNs) and traceback-based mitigation strategies have demonstrated enhanced network resilience against sophisticated flooding attacks [23].  
The effectiveness of these countermeasures depends on their ability to distinguish between legitimate traffic bursts and malicious flooding patterns while maintaining the performance benefits that make NDN attractive for content distribution applications. This pattern discrimination challenge becomes particularly acute in resource-constrained environments, where computational overhead for detection and mitigation must remain minimal to preserve system functionality.