Abstract:

The basic objection to smart contracts introduction in areas where data secrecy is essential, e.g. finance and healthcare, is the transparency nature of blockchain technology. Although zero-knowledge proofs (ZKPs) provide a promising solution to verifiable privacy, they have high computational and financial complexity levels, which make them unfeasible to use universally. This paper presents an adaptive multi-layer encryption structure to determine a solution to this limitation. These dynamically chosen and constructed cryptographic primitives (such as symmetric encryption, commitment, and zk-SNARKs) are informed by an intelligent policy engine and are selected and constructed according to the sensitivity of the transaction and the real time network conditions. This approach is no longer a traditional balance between performance and security because it uses a context-aware structure that is no longer a simple one-size-fits-all approach to privacy. We deploy a prototype to an Ethereum testnet and show that our framework supports a 38.7% and 86.9% reduction in computation overhead and gas expenditure in performing low-sensitivity transactions, respectively, over mandatory ZKP baselines, as well as strong privacy guarantees in sensitive operations. The findings affirm that adaptive, multi-layer cryptography is a sensible direction towards effective and realistic confidential smart contracts to be used in large scale application. Future research will be the incorporation of post-quantum cryptographic tools and how they can be customized to decentralized processes to achieve long-term security sustainability.

Key words: confidential smart contracts, zero-knowledge proofs (ZKPs), adaptive cryptography, blockchain privacy, multi-layer encryption