Stacks + Nostr
  • Introduction: Stacks + Nostr
  • SIP and NIP Summaries
    • SIP Summaries
      • SIP-000: The Stacks Improvement Proposal Process
      • SIP-001: Burn Election
      • SIP-002: The Clarity Smart Contract Language
      • SIP-003: Stacks P2P Network
      • SIP-004: Cryptographic Commitment to Materialized Views
      • SIP-005: Blocks, Transactions, and Accounts 👀
      • SIP-006: Clarity Cost Execution Assessment
      • SIP-007: Stacking Consensus
      • SIP-008: Clarity Parsing and Analysis Cost Assessment
      • SIP-009: Standard Trait Definition for Non-Fungible Tokens
      • SIP-010: Standard Trait Definition for Fungible Tokens
      • SIP-012: Burn Height Selection for a Network Upgrade to Introduce New Cost-Limits
      • SIP-013: Standard Trait Definition for Semi-Fungible Tokens
      • SIP-015: Stacks Upgrade of Proof-of-Transfer and Clarity
      • SIP-016: Metadata for Tokens
      • SIP-018: Signed Structured Data
      • SIP-020: Bitwise Operations in Clarity
    • NIP Summaries
      • NIP-1
      • NIP-2
      • NIP-3
      • NIP-4 👀
      • NIP-5 👀
      • NIP-6 👀
      • NIP-7
      • NIP-8
      • NIP-9
      • NIP-10
      • NIP-11
  • Feature Unlocks
    • Decentralized Identity Verification
    • Censorship-Resistant Social Networking
    • Secure Asset Management
    • Private Voting and Governance
    • Decentralized Notifications
    • Trustless Collaboration
  • Related Tech 👀
    • BNS
    • sBTC
  • Experimental Design and Methodology
  • Results and Discussion
  • Conclusion
  • Additional Research
    • ZKP
    • Indistinguishability Obfuscation from Well-Founded Assumptions
  • SIP-xx Draft
  • Disclaimer:
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  1. Additional Research

ZKP

What is Zero Knowledge Proof? https://www.youtube.com/watch?v=5qzNe1hk0oY

Zero Knowledge Proof (ZKP) is a cryptographic concept that allows one party, known as the prover, to demonstrate to another party, called the verifier, that they possess a specific piece of information without actually revealing the information itself. This technique ensures the protection of sensitive data while still enabling the establishment of trust between the two parties.

One common analogy used to explain ZKP is the "Finding Waldo" example. In this scenario, Alice (the prover) wants to prove to Bob (the verifier) that she knows the location of Waldo in a picture without revealing Waldo's exact position. To do this, Alice can use a large board with a cut-out in the shape of Waldo and place it over the picture. By positioning the picture so that Waldo is visible through the cut-out, Alice can show Bob that she knows Waldo's location without giving away the specific position.

This example demonstrates two key properties of Zero Knowledge Proofs. First, it shows the completeness of the proof, meaning that if Alice truly knows the location of Waldo, she can successfully convince Bob. Secondly, it illustrates the zero-knowledge property, as Bob learns that Alice knows Waldo's location without learning the location itself.

In real-world cryptographic applications, ZKPs are used to protect sensitive information in various domains, such as secure authentication, privacy-preserving data sharing, and anonymous transactions. One of the most prominent use cases is in blockchain technology, where ZKPs can help verify the validity of transactions without revealing the details of the transactions themselves. This enables enhanced security and privacy for users while maintaining the integrity and trust within the system.

The underlying mathematics and cryptographic techniques of Zero Knowledge Proofs can be quite complex, often involving advanced concepts such as elliptic curve cryptography, homomorphic encryption, and interactive proof systems. Despite the technical complexity, ZKPs offer a powerful tool for maintaining privacy and trust in an increasingly interconnected digital world.

Source: https://www.youtube.com/watch?v=6uGimDYZPMw&list=PL8Vt-7cSFnw29cLUVqAIuMlg1QJ-szV0K&index=1&pp=iAQB

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