ZK fixes the broken privacy layer of the internet

Several online services enforce weak password standards, do not hash user passwords, or just utilize a poor hashing method. So if a web service has a data breach, the passwords are more likely to be compromised. Enters Zero-Knowledge Proofs.

ZK fixes the broken privacy layer of the internet 1ZK fixes the broken privacy layer of the internet 1

For a 5th grader:
Zero-knowledge is a way of proving something without sharing information about it. For example, imagine you have a box that you say contains a secret. I can prove to you that there is something in the box without actually opening it or telling you what is inside. This is a very advanced and complex idea, but in simple terms, zero-knowledge is all about being able to show that something is true without giving away any details about it.


For grownups:
Zero-knowledge proofs are a type of cryptographic protocol that allows one party (the prover) to prove to another party (the verifier) that they know a certain piece of information, without revealing any information about the actual content of that knowledge. This is done with the help of mathematical algorithms and cryptographic methods that let the prover show the verifier that their claim is true without giving away any sensitive information.

This can be useful in a variety of settings, such as in financial transactions where the parties want to prove that they have the necessary funds without revealing the exact amount of money they possess, or in online voting systems where the parties want to prove that they have voted without revealing their actual vote.


Use-cases include:
• Digital signatures: ZKPs can be used to create digital signatures that are verifiable without revealing the actual content of the signed message. This can be useful in financial transactions, where the parties want to prove that they have signed a contract without revealing the details of the contract itself.

• Anonymous voting: ZKPs can be used in e-voting systems to allow voters to prove that they have cast their vote without revealing their actual vote. This can help to maintain the privacy and integrity of the voting process.

• Secure multi-party computation: ZKPs can be used to allow multiple parties to compute a function on their inputs without revealing their inputs to each other. This can be useful in situations where the parties want to jointly compute a function on sensitive data, without revealing the data to each other.

• Identity verification: ZKPs can be used to verify the identity of a user without revealing any sensitive information about the user, such as their password or biometric data. This can be useful in situations where the parties want to prove that they are who they claim to be without revealing any sensitive information.

• Privacy-preserving data analysis: ZKPs can be used to allow multiple parties to jointly analyze a dataset without revealing the individual records in the dataset to each other. This can be useful in situations where the parties want to perform analytics on sensitive data without revealing the #data to each other.