Cryptography based Authentication Approach to enhance the resource security for Wireless Networks against DdoS

Abstract

The IoT is growing in many fields, including healthcare, smart homes, transportation, and industrial automation. However, because to its openness and heterogeneity, it faces numerous security threats. Distributed denial of service (DDoS) and routing assaults are the most dangerous forms of these threats because they compromise the scalability, dependability, and availability of IoT infrastructures. Methods for detection are covered extensively in this review paper, with a focus on clustering-based approaches, models for fault tolerance, and energyefficient routing algorithms. Structured tables provide a comparative examination of current methodologies and results, allowing one to assess their merits and cons. Special emphasis is placed on the distinction between centralized, distributed, and emerging hybrid detection frameworks. Recent advances, such as federated learning and graph-based artificial intelligence, demonstrate how distributed and hybrid models can enhance privacy, scalability, and real-time responsiveness while mitigating the drawbacks of centralized architectures. By synthesizing insights from existing literature and the latest frameworks, this review identifies open challenges in adaptability, synchronization, and resource optimization, and it points toward hybrid detection as a promising direction for securing large-scale IoT deployments.