Zero Knowledge vs Decoy based Systems
"Cryptocurrency exposes all your spending activities to the public since it's just like a Twitter to your Bank account and this is a great issue that must be solved by adopting on chain privacy." - Ian Miers at Devcon4.
Certain crypto projects have gained recognition for their privacy-centric approaches. Zcash is renowned for employing Zero Knowledge Proofs (ZK) to protect transaction amounts and addresses. Monero stands out for its utilization of a Decoy-based sender obfuscation in combination with other encryption schemes to attain user privacy on the blockchain.
Understanding ZK Proofs and Decoy Based Systems
Zero Knowledge Proofs are cryptographic systems that allow one party (the prover) to demonstrate to another party (the verifier) the validity of a statement without revealing any underlying information about the statement itself. In the context of Zcash, ZK proofs are employed to verify the validity of a transaction without disclosing transaction details such as the SENDER, RECEIVER or transaction AMOUNT.
This ensures that user privacy is preserved as the transaction remains confidential while still being validated. This technology is designed to ensure the confidentiality of financial transactions on the Zcash network.
In the Decoy-based systems such as RingCT, multiple transactions are combined making it challenging or difficult to trace the actual source and destination of funds. The algorithm introduces decoy inputs and outputs in transactions also employing encryption of the addresses used as inputs & using Range proofs to validate the amount transferred is spendable.
This approach obfuscates the transaction trail. The use of decoy inputs makes it challenging for anyone analyzing the blockchain to identify the real sender, receiver, or transaction amount.
Important Note: This method of on-chain privacy preserving transaction still explicitly reveals (encrypted) inputs to all user transactions. Metadata such as the between different users on the network can still be gathered. If an adversary actively participates in generating transactions on the network, it effectively deanonymises the decoy inputs of other users.
