In dense RFID systems, where numerous readers and tags operate simultaneously in close proximity, securing reader-to-reader communication is essential to prevent attacks such as eavesdropping and spoofing. Existing protocols focus primarily on reader-to-tag communication and use static security mechanisms that may be inadequate in dynamic conditions. We propose DCA-KEAE, a Dynamic Context-Aware Key Exchange and Adaptive Encryption framework for RFID systems. DCAKEAE adapts security protocols in real-time based on factors such as reader proximity, system load, and threat levels: it employs lightweight symmetric keys for low-risk scenarios and escalates to stronger protocols like ECDH and AES-256 in highrisk environments. Evaluations with up to 10,000 readers show that DCA-KEAE reduces latency, optimizes encryption, and improves system throughput, offering a scalable and efficient solution for RFID networks, with applications extending to the Internet of Things (IoT), industrial automation, and smart grids.

Dense RFID environments pose significant challenges, such as reader collisions, tag interference, and scalability issues, which degrade system performance and reliability. This paper introduces RFIDNet, a novel protocol designed to address these challenges by dynamically coordinating reader activities and optimizing network resource utilization. The proposed RFIDNet is an innovative framework of advanced mechanisms that include a Carrier Sense Multiple Access with Reader Arbitration (CSMARA) scheme for efficient reader coordination, Dynamic Frequency Hopping (DFH) for interference mitigation, and merging Frequency and Time Division Multiple Access (F/TDMA) with Reduce Coverage Control (RCC) to handle unresolved contention. Experimental validations using a Universal Software Radio Peripheral (USRP) testbed and MATLAB simulations demonstrate that RFIDNet improves the overall system performance compared to the baseline. This confirms RFIDNet's robustness and scalability, making it a viable solution for realworld, dense RFID deployments.

ABSTRACT Dense radio frequency identification (RFID) networks suffer from severe reader collisions, redundant reads, and inefficient resource utilization, particularly in large‐scale deployments. Existing approaches, including centralized and hybrid scheduling schemes, fail to scale effectively due to their reliance on global coordination and static allocation mechanisms. This paper presents NEMO (neighbourhood‐aware efficient management and optimization), a fully decentralized neighbourhood‐aware RFID network framework that dynamically optimizes scheduling, power control, and frequency allocation without requiring global coordination. NEMO leverages a novel adaptive scheduling mechanism to mitigate collisions while ensuring fair and efficient tag interrogation. Extensive universal software radio peripheral‐based hardware experiments and large‐scale simulations with up to 5000 readers and 1,000,000 tags demonstrate that NEMO outperforms state‐of‐the‐art protocols by achieving 25% higher throughput, 30% fewer collisions, 40% reduction in redundant reads, and improved energy efficiency by 18%. Additionally, NEMO exhibits scalability and robustness under extreme network congestion by maintaining high performance even as the numbers of readers and tags increase. The proposed framework is highly applicable to real‐world RFID deployments in warehouses, logistics, smart retail, Internet of Things, and industrial automation, where dense RFID environments demand efficient, adaptive, and decentralized resource management.