ZTips

ZTips

Truth Rewarded, Privacy Guarded

The problem ZTips solves

Problems

  1. Lack of Reliable Anonymous Tipping verification mechanisms leading to malicious reporting
  2. Lack of mature Technology Infrastructures increases the chance of information leakage and traceability of the tipster
  3. Risk to Life, Family, or Finances discourages participation
  4. Ineffective Incentive Mechanisms reduce Tipsters’ Motivation

Solutions

  1. Verification and Anonymity of Investigators and Tipsters is obtained through ZK implementation along with ZK Verification Badges with Optional KYC
  2. Incremental incentive release by Investigators leads to competition among tipsters to deliver credible information
  3. Freemium tip reporting & Credibility rating of tipsters lead to the enforcement of a feedback loop which eliminates malicious reporting
  4. Implementation of ZK for both anonymity and verification at multiple steps during the information exchange ensures a robust solution
  5. Offchain computation of entire proof generation ensures scalability of the platform handling high volumes of information exchange in the future
  6. Escrow implementation between investigator and tipster ensures protection from fraud risks

Dynamic Credibility System:

  1. Acceptance Score: Tipsters are scored based on the ratio of accepted tips to total tips
  2. Credibility Ratings: Tipsters are awarded based on their acceptance scores:
    A) Super Reliable: Tipsters with an accuracy score of over 80% are deemed highly credible.
    B) Trustworthy: Tipsters with scores between 60% and 80% are considered reliable.
    C) Considerable: Scores between 40% and 60% indicate moderate credibility.
    D) Risky: Tipsters with scores between 10% and 40% are flagged as potentially unreliable.
    E) Fraudster: Tipsters with scores below 10% are considered untrustworthy.

Industry Use Cases

  1. Crime & Justice Delivery
  2. Politics
  3. Relationships
  4. Software Bug Bounties/Ethical Hacking
  5. Financial Institutions
  6. Big Corporations
  7. Surveys
  8. Media Houses
  9. Defence

Challenges we ran into

  1. Managing numerous package dependency depreciation issues: We examined previous smart contracts with similar dependency problems, which helped us resolve the issues.
  2. Typescript data structure errors in MINA forced us to switch to Risk Zero overnight: Reporting this error to the Mina team later helped them fix it.

Tracks Applied (5)

Prizes for Top 3, Hackers' Choice & Chewing Glass

We are solving an important real-world problem in a novel way. If this gets wider adoption, the crisis of meaningful inf...Read More

Best application that uses zkVerify to verify ZK proofs

We have generated various ZK proofs which will be verified faster using ZKverify to attain the scalability of the platfo...Read More

zkVerify

🤩 Best zkVM Application

As clearly mentioned in your judging criteria, we are solving an important real-world problem in a novel way. If this ge...Read More

RISC Zero

🤝 ZK Coprocessor

We have used steel view call proofs library and the proof is generated Offchain.

RISC Zero

👪 Integrations Bounty

We have used Risk zero libraries to integrate in our project

RISC Zero

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