An enhanced proactive social defense mechanism for Fork attack in IoT network using QHC and BFCC

Proactive defense in the Internet of Things (IoT) is a strategy to prevent threats before they damage the network. To address this, we propose a social trust-driven defense framework that integrates Quantum Hannorentz Cryptography (QHC) and Bigram Frequency-Based Caesar Cipher (BFCC) to neutralize FA threats proactively. Initially, the IoT devices and applications are registered into the network. Then, the nodes are initialized and clustered using machine intelligence-guided K-Means clustering. Next, multipath creation and trust-level analysis are performed using distributed reputation metrics. Based on the multipath and trust level, the trusted optimal path is selected. Afterward, the proactive FA defense is performed. Network loads are then balanced through machine intelligence-enhanced congestion forecasting. Finally, the integrity of the data is analyzed by a machine intelligence-powered Factach initialization with Biosinc activation-based Gated Recurrent Unit (FBGRU)-based Intrusion Detection System (IDS). The interpretation results demonstrated that the proposed QHC attained a 98.92% security level, while existing models such as QC, RSA, DES, and ElGamal achieved lower security levels of 95.26%, 92.95%, 89.71%, and 88.2%, respectively. This holistic approach establishes new benchmarks in IoT security by unifying quantum-resistant encryption, adaptive routing, and machine intelligence-driven lightweight intrusion detection to address critical gaps in Fork Attack (FA) mitigation.