Zero-Knowledge Proof [ZKP]— A revolutionary alternative to consensus mechanisms
How ZKPs are impacting Blockchain/cryptographic technologies and future applications which could change the digital space (as seen in…
How ZKPs are impacting Blockchain/cryptographic technologies and future applications which could change the digital space (as seen in Ethereum 2.0)
Cybersecurity is one of the main areas of innovation and growth in our digital age. As blockchain technology develops, the challenge of building user confidence and preserving privacy persists. Nowadays, if someone’s information has been hacked, a password or private key might not be able to identify them definitively due to contemporary advancements in hacking.
Zero-Knowledge Proofs (ZKPs), an older piece of technology, have lately regained relevance in the realm of cryptography as academics explore ways to keep data secret and transactions safe. Many blockchain developers have started integrating ZKPs to boost trust and privacy in bitcoin transactions after realising this tool’s capacity to validate users without disclosing their personal information.
What is a Zero-Knowledge Proof?
ZKPs deploy mathematical formulae to confirm the accuracy of information without exposing it. For example, one can utilise a ZKP and avoid directly sharing the data with the other party if they need to demonstrate that they own a specific piece of private information.
ZKPs evaluate loose and inconsequential pieces of data to mathematically demonstrate that the presence of the complete data set is highly plausible, in contrast to conventional cryptography techniques that inspect, encrypt, and send the entire piece of data. ZKPs stop nefarious third parties from intercepting anything of value by requiring the conveyance of little, unimportant bits of information.
The Alibaba Cave Tale, a fantastic illustration of Zero-Knowledge-Proof:
A door blocks the space between two entrances to a ring-shaped cave, with entrances on both the left and right sides. Peggy wants to show her pal Victor that she is the only one who knows the key to unlock the door. So Peggy comes up with a scheme to persuade Victor that she is aware of the code without informing him since she wants to keep it a secret:
Peggy enters one side of the ring after asking Victor to meet her at the cave’s entrance.
Peggy then requests Victor to choose which side of the ring she should go from. Peggy can leave from whatever side she likes because she knows the door’s code. Victor may thus be 50% certain that she knows the secret code if he instructs her to exit the cave from the left side, and she does.
Victor’s degree of assurance will rise if he conducts this test on Peggy enough times, and she consistently passes, leading him to believe that she knows the secret code.
The two characters in this narrative represent the prover (Peggy) and the verifier, the two parties involved in ZKP applications (Victor). In digital implementations, the prover provides the verifier with a list of commitments, such as knowing a secret code. The verifier then questions the pledges. Finally, the verifier can believe the prover’s claims if they complete the tasks.
The Alibaba cave narrative is similar to a straightforward login process. However, ZKPs can validate a user’s credentials without requiring them to submit their password to a server and run the danger of being intercepted, just as Victor does to demonstrate Peggy’s knowledge of the secret code.
Properties of ZKPs
Three requirements must be met for ZKPs:
Completeness: The verifier must establish the existence of the entire data collection that the prover asserts to be in possession.
Soundness: The challenges with which the verifier validates the prover’s claims cannot be completed without the required information.
Zero-Knowledge: Neither the prover nor the verifier may divulge any genuine private information.
Types of ZKPs
Depending on the level of communication between the prover and the verifier necessary for a ZKP, one of two alternative types of protocols can be used. Following is a description of the two types of ZKPs:
Interactive ZKPs
In interactive ZKPs, the prover must successfully fulfil challenges put forward by the verifier to win the verifier’s confidence in the accuracy and existence of the prover’s secret information. Until the prover meets the criteria of the proof, data is sent between the two parties during the verification process.
Non-Interactive ZKPs
According to the prover’s commitments, a simulated verifier will present problems for the prover to accomplish in non-interactive ZKPs. In contrast to interactive ZKPs, non-interactive ZKPs employ an automated mechanism to verify the prover’s assertions rather than a human.
Applications of Zero-Knowledge Proofs
MIT academics created the ZKP framework in the 1980s, but only a few people have used it. To decrease the amount of data accessible on the blockchain, developers have started using ZKPs, enhancing the security and privacy of Bitcoin transactions.
One group, the ZKProof movement, has even established a global developer community in an effort to further the use and standardisation of ZKP technology. We will go through a few instances of zero-knowledge proofs being used by two very well-known chains below:
ZCash and zk-SNARKs
ZKPs, a feature of the cryptocurrency ZCash, are used to authenticate transactions without disclosing the origin of the money or any other private information, such as the amount transmitted or the name of the intended receiver. Furthermore, users of ZCash can employ zk-SNARKs, or “zero-knowledge succinct non-interactive arguments of knowledge,” to demonstrate that they match the requirements for carrying out a transaction without the need for any communication between the prover and verifier. ZCash transactions are co-private and safe as a result.
Ethereum 2.0 and zk-Rollups
Zk-Rollups, created to accelerate transactions and lower costs, let users validate Ethereum transactions on layer 2 using zero-knowledge proofs and then broadcast the PoV (Proof of Validity) onto layer 1.*
*Stay tuned for our next article where we will cover the specifics of zk-Rollups post-Merge ;)
User Verification
The identities of individuals can also be confirmed using zero-knowledge proofs. For instance, if a two-factor authentication (2FA) system calls for both a social security number and a driver’s licence number, a ZKP algorithm may link certain portions of each and calculate the likelihood that the person is who they say they are. The person can use this technique to verify their identification to the system while concealing their full social security and driver’s licence numbers.
Advantages & Disadvantages of Zero-Knowledge Proofs
ZKPs, like other cryptographic techniques, have advantages and downsides, which are shown in the table below:
Conclusion
Zero-knowledge proofs provide a safe way to authenticate data required for bitcoin transactions and user IDs while protecting private data. ZKPs employ straightforward algorithms and don’t require communication between the parties participating in transactions, unlike other encryption methods.
ZKPs will likely become more widely used and crucial to blockchain technologies as developers begin to appreciate their ability to boost trust and confidentiality in the cryptography community.