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➥ Privacy 2.0: The Infrastructure Web 3.0 Has Been Waiting For Crypto promised privacy but delivered exposure. Every wallet, trade, and action stayed public. Privacy 2.0 fixes this through encrypted computation, giving users control over what stays visible. Here’s everything you need to know about Web3 privacy in 30s 🧵 — — — ► Why Privacy Matters Now From 2015 to 2022, global breaches more than doubled, exposing over 10 billion records. People are realizing how easily their data can be tracked and monetized. In Web3, every wallet, trade, and transaction is public. Transparency builds trust but eliminates privacy. Privacy-first apps are already growing fast. Telegram and Signal gained millions of users between 2019–2021. Brave reached 66M monthly users in 2023, proving users want control. That same demand is moving to crypto. Builders are creating private DeFi, AI, and gaming protocols. Users want data ownership. This shift defines Privacy 2.0 — privacy built into the base layer of Web3. — ► The Problem with Web3 Privacy ➤ Blockchains are transparent by default. Over 40% of on-chain activity is traceable through analytics tools. ➤ This openness builds trust but removes confidentiality. Traders and institutions can’t operate securely without exposing strategies. ➤ Developers can’t build private primitives like dark order books or shielded lending when every transaction is public. ➤ Around 60% of institutions avoid on-chain activity due to compliance risks and data visibility. ➤ Without privacy infrastructure, Web3 adoption remains limited. Transparency without protection isn’t trust — it’s exposure. — ► Privacy 2.0 Crypto achieved transparency but not confidentiality. Privacy 2.0 introduces encrypted computation, keeping data private while results remain verifiable. ➤ Phase 1.0 Focused on transactional anonymity. Projects: @monero, @Zcash used ring signatures and zk-SNARKs to hide senders, receivers, and amounts. ➤ Phase 1.5 Extended privacy to smart contracts but limited composability. Projects: @SecretNetwork, @OasisProtocol used TEEs for secure execution; @RAILGUN_Project applied zk-SNARKs for private DeFi. ➤ Phase 2.0 Known as Decentralized Confidential Computing (DeCC). Enables shared private state, multiple users and dApps compute on encrypted data without revealing inputs. Projects: @ArciumHQ, @UmbraPrivacy, @nillionnetwork, Fhenix use MPC and FHE to power private DeFi, AI, and gaming. — ► Five Core Privacy Technologies Privacy 2.0 runs on five main cryptographic systems enabling encrypted computation with verifiable results. ❶ Zero-Knowledge Proofs (ZK) Prove validity without exposing data. Projects: @AleoHQ, @MinaProtocol, @RAILGUN_Project, @Zcash, @Aleph__Zero use ZK for private transactions and computation proofs. ❷ Multi-Party Computation (MPC) Distributes encrypted workloads across nodes that compute jointly without sharing inputs. Projects: @ArciumHQ, @nillionnetwork (using multiple privacy techniques), @partisiampc apply MPC for encrypted DeFi, AI, and cross-chain logic. ❸ Trusted Execution Environments (TEEs) Secure hardware enclaves that isolate and process encrypted data. Projects: @SecretNetwork, @OasisProtocol, @PhalaNetwork, @tenprotocol, @MarlinProtocol, and @iEx_ec use TEEs for confidential smart contracts. ❹ Fully Homomorphic Encryption (FHE) Enables computation directly on encrypted inputs. Projects: @FhenixIO, @zama_fhe, @inconetwork use FHE for private trading, lending, and analytics. ❺ Garbled Circuits (GC) Encrypt computation logic instead of raw data, letting multiple parties compute together without exposing inputs. Projects: @COTInetwork, @FairGateLabs, and other research teams use GC for scalable, low-latency encrypted payments and compute protocols. — ► Use Cases Privacy 2.0 opens a new design space for developers, combining confidentiality with verifiability. ➤ Private DeFi Dark order books, private swaps, and shielded lending for traders and institutions. ➤ AI and Data Analytics AI models can train on encrypted data using privacy-preserving compute. ➤ Gaming Hidden-state mechanics like on-chain poker or fog-of-war remain fair and verifiable. ➤ Healthcare and Identity Sensitive data can be analyzed without exposure, improving compliance and security. — ► Wrap-Up The blockchain trilemma solved decentralization and scalability but left privacy behind. Every transaction is public, exposing users and institutions. Without privacy, transparency turns into risk. Web3 cannot be secure until users control their data. Privacy 2.0 completes the trilemma with encrypted computation: keeping data private, results verifiable, and networks truly secure.