# Panther’s Privacy Enhancement Stack

A zero-knowledge proof is a protocol that allows one party (the prover) to convince another party (the verifier) that they possess a piece of private information without having to actually reveal it.

Zero-knowledge proofs have only recently become practical for real-world use in finance, despite being decades old. The implications of the technology are enormous: ZKPs are able to maintain blockchains’ accuracy and make scalability possible with ease and precision. Their users can also know with complete clarity how their data is being used, only needing to share what’s absolutely necessary for a given transaction.

With ZKPs, users also no longer need to re-execute every transaction in a ledger, as they can instead check a succinct proof.

Panther also utilizes

*zk-SNARKs*, which stands for “Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge”. Thanks to zk-SNARKs, and just like with ZKPs, a prover can prove their possession of information without revealing it. However, the added benefit of zk-SNARKs is that they also allow for this to happen without both parties interacting. This helps further users’ privacy and anonymity.zkSNARKs are:

- Succinct: The size of the proof is small compared to the size of the statement being proved.
- Non-interactive: zkSNARKs do not require rounds of interaction between the prover and verifier except for a negligibly small probability.
- Argument: A weaker notion of a mathematical proof where we assume the prover has bounded computational resources.
- Knowledge: The prover cannot construct a proof without knowing a particular witness for the statement. This would be the equivalent of knowing “what to look for”, or “what to decode”.

In addition to zero-knowledge proofs, Panther uses

*differential privacy*,*homomorphic encryption*,*Secure Multi-Party Computation*, and*selective disclosure schemes*. Each of these mathematical and technical building blocks plays different roles in supporting the enablement of privacy, anonymity, and scalability. By drawing upon these technologies, Panther facilitates a shift in trust from regulatory frameworks and organizational practices to trustless mathematical proofs and their interpretation.