| Summary: | This work shows the comprehensive model of obfuscation techniques in decentralized peer-to-peer (P2P) network transactions by consolidating a distributed learning approach and blockchain as the backbone technologies. We provide several protocols by utilizing the CryptoNote protocols to be deployed into the Ethereum blockchain environment that can overcome the demerits of most current blockchain systems in terms of traceability and linkability of data flows. The concerns of traceability and linkability of transactions arise since data record breaches have occurred intermittently, where valuable information is often mishandled and misused, inducing a security threat to personal privacy. Furthermore, We thoroughly analyzed the pros and cons of the constructed protocols along with a systematic security evaluation to satisfy the design objectives and requirements. The constructed protocols are unbiased since the observers cannot extract and associate transactional information with any entity. Our assessment and assumptions neglect the hard fork where a radical change in the blockchain network is required for thorough real-world implementation. Finally, the numerical results and symbolic modelling indicate that the proposed protocols fill the gap of the existing model found in the literature. These findings highlight a fresh concept of privacy awareness in decentralized network environments, the properties that most constructions are lacking.
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