Abstract

Internet of Things (IoT) has massively adopted the market due to the current era demanding fully intelligent and autonomous services. The IoT industry is flourishing in terms of Internet of healthcare things, Internet of vehicles and autonomous driving, unmanned aerial vehicles, satellite and industrial Internet of things smart homes, etc. IoT can be enabled by employing connected devices such as sensors, continuously communicating, storing, and disseminating data. Data dissemination through energy-constrained low-power IoT sensors suffers from issues such as security and privacy of data. Traditional solutions using single-layer or multi-layer cryptographic algorithms do not suffice the need for security and privacy. Thus, we have proposed a blockchain-based secure onion routing protocol for a trusted and anonymous data dissemination framework for sensor communication in IoT environment. We have employed machine learning (ML) algorithms to classify adversarial and non-adversarial data fed to the onion router to reduce computational time. Our proposed framework uses a Random Forest (RF) classifier outperforming with 93.65% accuracy compared to other ML algorithms. Also, we have achieved low data storage cost, low latency, and high scalability by employing Inter Planetary File System (IPFS) and a 6G network, respectively.

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