Adaptive and Context-Aware Defenses Against Interest Flooding Attacks in CCN-based IoT

The Internet of Things (IoT), particularly in constrained environments like Wireless Sensor Networks (WSNs), demands scalable and secure networking. Content-Centric Networking (CCN) addresses key IoT challenges through content-based communication, enabling caching, request aggregation, and resilience. However, CCN is vulnerable to Interest Flooding Attacks (IFA), which overload the Pending Interest Table (PIT) with excessive Interest packets. IfNot, a lightweight mitigation approach, adjusts forwarding based on PIT timeouts but suffers from high false positives and limited resilience to adaptive attackers. To improve this, we propose IfNot-R, which penalizes malicious behavior using historical data, and IfNot-FPGuard, which reduces false positives via longterm Interest satisfaction tracking. These enhancements strengthen IFA defense in dynamic IoT contexts.