Web3 AI: Protecting Data with ZKP, TEE & FHE

In today’s data-driven world, personal information is increasingly at risk as our extensive digital footprints make sensitive data more vulnerable to breaches and unauthorised access. Advanced Web3 AI technologies have emerged to enable more secure Web3 systems:

1. Zero-Knowledge Proofs (ZKP): Transparency Without Compromise

ZKP is a cryptographic method that allows one party to prove the validity of a statement to another party without revealing underlying information to achieve both privacy and transparency. For example:

zkKYC by zkMe: Enables platforms to verify identities for KYC compliance without exposing sensitive personal data, preserving both user privacy and regulatory adherence.

ZKP excels as a tool for ensuring that only necessary information is shared while proving validity—making it ideal for verifiable Web3 AI processes, sensitive transactions and identity management.

2. Trusted Execution Environment (TEE): Secure, Isolated Processing

TEE is a hardware-based solution that creates a secure and isolated computing environment, protecting sensitive data and processes from external threats. This is particularly useful for autonomous AI agents in terms of:

Secure Operations: They separate sensitive computations from the standard environment, shielding them from external tampering or hacking attempts.

Autonomous AI Management: Projects like Phala Network and Fleek Machines leverage TEEs for purposes like token issuance, MEV protection and creating easy-to-deploy secure computing environments for developers.

TEEs provide a trusted layer for executing smart contracts, managing sensitive workflows and safeguarding proprietary AI model weights from reverse engineering or theft.

3. Fully Homomorphic Encryption (FHE): Computing on Encrypted Data

FHE allows computations to be performed on encrypted data without needing to decrypt it, thus preserving confidentiality throughout the process, such as:

Governance Voting: Mind Network uses FHE to ensure user votes remain private and secure, fostering trust in decision-making processes.

Restaking with Privacy: Assets can remain encrypted during staking or financial operations, eliminating exposure and mitigating risk.

The combination of FHE with TEEs further strengthens the security model, with TEEs protecting the computational environment and FHE ensuring that sensitive data remains encrypted during usage.

These AI technologies are a huge step toward a more secure and privacy-focused Web3 ecosystem, enabling users to keep control over their data while ensuring accountability and verifiability. As Web3 AI technologies continue to evolve, combining these advanced cryptographic and hardware solutions will be essential to fostering innovation while safeguarding user sovereignty. This resilient and privacy-enhanced Web3 infrastructure will lay the foundation for a digital future built on trust and privacy.

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*Disclaimer: The information provided on this blog does not constitute investment advice, financial advice, trading advice, or any other form of professional advice. aelf makes no guarantees or warranties about the accuracy, completeness, or timeliness of the information on this blog. You should not make any investment decisions based solely on the information provided on this blog. You should always consult with a qualified financial or legal advisor before making any investment decisions.

What's aelf Ventures?

aelf Ventures is the investment arm of aelf, a high-performance Layer 1 AI blockchain platform that offers builders and users advanced AI functionalities and cutting-edge infrastructure. With a dedicated fund of $50 million, aelf Ventures is focused on empowering Layer 1 blockchain projects and various aspects of the Web3 ecosystem, such as DeFi, GameFi, NFT, and those looking to make the transition from Web2 to Web3.

Till date, aelf Ventures has invested in projects such Crystal Fun and Confiction Labs (pka. Mythic Protocol), and is actively incubating promising ventures within the ecosystem such as Portkey, eBridge, Forest NFT Marketplace, AwakenSwap, eWell, and BeanGoTown.

Find out more about aelf and stay connected with our community:

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Tool/Platform	What's it about
ChainGPT	An AI-powered assistant for the blockchain and crypto industry, specializing in content creation, language translation, smart contract coding, and more.
aelf	A high-performance, customisable multi-chain blockchain framework with AI-powered smart contracts and a developer-friendly environment.
Quick Intel	An AI-powered crypto security platform that helps investors avoid scams, rug pulls, and honeypots by analysing smart contracts, social sentiment, and on-chain data.
Cogwise AI News Aggregator	An AI-powered news aggregator that analyses real-time news and global trends to predict market movements in the crypto market.
OpenAI Codex	An AI system that transforms natural language into code, automating code creation for smart contracts, blockchain applications, and other development tasks.
QnA3	An AI-powered Web3 knowledge hub that provides real-time information and insights on cryptocurrencies, blockchain projects, and the broader Web3 ecosystem, with unique Solana Actions integrations.
Fetch.ai	A platform that combines AI and blockchain to create autonomous economic agents (AEAs) for various applications, including supply chain optimisation and smart city management.
Octavia	A decentralised digital identity (DID) platform for creating and managing self-sovereign digital identities, empowering users to control their data and online presence.
TensorFlow	A versatile open-source machine learning framework used for building AI models that can analyse blockchain data, enhance security, and predict market trends.
Alethea	A platform that creates 'Intelligent NFTs' (iNFTs) with unique personalities and the ability to engage in conversations, powered by AI and blockchain technology.

Chain	URL	Explorer
AELF	https://aelf-test-node.aelf.io/	https://explorer-test.aelf.io/
tDVW	https://tdvw-test-node.aelf.io/	https://explorer-test-side02.aelf.io/

Feature	Description
Inheritance	ERC-404 inherits from the interfaces IERC-404, IERC721 Receiver, and IERC165, implementing functions specified in these interfaces, behaving as both ERC20 and ERC721.
Data Structures	Mappings track balances, allowances, approvals, and ownership of tokens. Double-ended queue stores ERC721 token IDs. Data for managing ownership and indices of ERC721 tokens.
Constructor	Initialises token name, symbol, decimals, and other necessary variables for ERC20 and ERC721 tokens.
Token Minting and Burning	_mintERC20 function for minting ERC20 tokens. _retrieveOrMintERC721 function for minting ERC721 tokens and retrieving from a bank. _withdrawAndStoreERC721 function for depositing ERC721 tokens into the bank.
Transfers	Functions for transferring ERC20 and ERC271 tokens between addresses. Distinguishes between token types based on ID. _transferERC20WithERC721 function handles transfers involving both types.
ERC20 and ERC721 Interactions	Approve function handles approvals for both token types. Functions like transferFrom, safeTransferFrom, and permit handle transfers and approvals.
EIP-2612 Support	Supports EIP-2612 permit functionality for ERC20 tokens.
Interface Compatibility	Implements necessary functions for ERC-404 and ERC165 interfaces, indicating compatibility with ERC20 and ERC721 standards.

Role	Max Number
BP	2N+1, N starts from 8 in 2022
Candidate node	5*(2N+1)
Voter	No limit

Benefits	Description
Makes smart contracts 'smarter'	AI-driven smart contracts can autonomously modify terms based on predefined conditions and real-time data input, ensuring that the contracts are not just automated but also intelligent and self-improving over time.
Levelled up data analysis	Data is the new oil, and AI is the machinery that refines it. It is possible for AI to reduce large-volume blockchain data analysis time by up to 90%.
Boosts security	Through machine learning models, AI can prevent frauds and detect security threats in real time. It can identify potential breaches, predict future threats, and adapt to evolving security measures.
Lowers carbon footprint	AI algorithms help optimise energy consumption in blockchain operations, given the flak drawn by activities like Bitcoin mining.

Data Privacy & Verifiability: Leveraging ZK, TEE and FHE for a Secure Web3 Future

1. Zero-Knowledge Proofs (ZKP): Transparency Without Compromise

2. Trusted Execution Environment (TEE): Secure, Isolated Processing

3. Fully Homomorphic Encryption (FHE): Computing on Encrypted Data

What's aelf Ventures?

What Are the Best LLMs for AI Agent Development?

Data Privacy & Verifiability: Leveraging ZK, TEE and FHE for a Secure Web3 Future

Fund house	Known for	Description
Grayscale Investments	Market leader, extensive experience	Known for pioneering cryptocurrency ETFs
Ark Invest	Innovative approach, tech-forward	Led by renowned investor Cathie Wood
Fidelity Investments	Established trust, large client base	Strong presence in both traditional finance and crypto
VanEck	Diversification, Risk management	Pioneers in commodity-linked ETFs
Invesco	Strong research, broad market reach	Expertise in global ETF offerings
Bitwise Asset Management	Crypto-focused, deep sector knowledge	Early entrant into crypto index funds
WisdomTree	Strategic asset management, innovative solutions	Notable for integrating crypto assets into traditional portfolios
ProShares	ETF expertise, market adaptability	Launched the first Bitcoin-linked ETF in the U.S

Pros	Cons
Enhanced Efficiency and Automation	Security and Reliability Concerns
Advanced Analytics and Predictive Modelling	Ethical and Regulatory Dilemmas
New Financial Products and Services	Centralisation Paradox: Power is concentrated in the hands of a few

	Layer 1	Layer 2	Layer 3
Function	Core blockchain operations (consensus, security)	Scaling and efficiency improvements	Application layer (dApps, smart contracts)
Examples	Bitcoin, Ethereum	Lightning Network, Plasma	Decentralised exchanges, NFT marketplaces
Scalability	Limited by design	Enhanced through off-chain processing	Dependent on underlying layers
Security	High, due to decentralisation	Relies on Layer 1 for finality and security	Inherits security from Layer 1 and 2
Primary Role	Foundation of the blockchain network	Alleviates congestion, speeds up transactions	User interaction and functionality

AI Crypto Project	Category
Fetch.ai (FET)	Decentralised AI
SingularityNET (AGIX)	Decentralised AI Marketplace
Ocean Protocol (OCEAN)	Data Sharing and Monetisation
The Graph (GRT)	Blockchain Data Indexing
Numerai (NMR)	Crowdsourced Machine Learning
Cortex (CTXC)	AI Execution on Blockchain
Golem (GLM)	Decentralised Cloud Computing
NEAR Protocol (NEAR)	Scalable Blockchain Platform
Akash Network (AKT)	Decentralised Cloud Computing
Render Token (RNDR)	Distributed GPU Rendering

Feature	Parallel Execution Scheduling	Sharding
Strategy	Concurrent execution of non-conflicting transactions within a single blockchain	Partitioning the blockchain into multiple shards, each processing a subset of transactions
Advantages	Increased transaction throughput, faster confirmation times, reduced fees	Enhanced scalability, improved network capacity, potential for increased decentralisation
Challenges	Complexity of dependency analysis, potential for security vulnerabilities	Complexity of cross-shard communication, potential for increased centralisation
Suitability	Suitable for blockchains with relatively low transaction volumes or those where maintaining a single, unified state is crucial	Suitable for blockchains with high transaction volumes or those where scalability is a primary concern

DEX	Best For
Uniswap	Largest DEX, high liquidity, popular for trading ERC-20 tokens on Ethereum
AwakenSwap	Multi-chain DEX, user-friendly interface, good for beginners
SushiSwap	Similar to Uniswap, offers yield farming opportunities and staking rewards
PancakeSwap	Leading DEX on Binance Smart Chain, lower fees, good for BEP-20 token trading
Curve Finance	Stablecoin trading and low slippage, ideal for large trades with minimal price impact
Balancer	Automated portfolio management and customisable liquidity pools
1inch	DEX aggregator, finds best prices across multiple DEXs, saves on gas fees
Kyber Network	Instant token swaps and high liquidity, suitable for quick trades
Bancor	Automated market making and single-sided liquidity provision, reduces impermanent loss risk
ZKSwap	Layer-2 DEX on ZK-Rollups, offers faster and cheaper transactions with improved scalability
dYdX	Decentralised derivatives exchange, offering perpetual contracts and margin trading

Feature	Description
Accuracy	High accuracy in data analysis and trade execution is crucial for minimising errors and maximising profit potential
Real-time Analysis	Ability to perform real-time market analysis to seize opportunities as they arise
Backtesting Capabilities	Essential for testing strategies against historical data to ensure reliability and effectiveness
Customisation	Offers flexibility to tailor trading strategies according to your specific needs and market conditions
Security	Strong security measures to protect against hacking and unauthorised access
User-Friendly Interface	Easy-to-navigate interface, allowing even beginners to deploy and manage trades effortlessly
Technical Support	Reliable customer support to assist with any technical issues or questions
Compatibility	Integration with various platforms and brokers for a seamless trading experience
Performance Metrics	Ability to provide transparent and accurate info on historical performance, and key metrics like moving averages. Low latency arbitrage strategies give insights into trading performance and decision-making accuracy.
Cost	The cost of using AI trading bots can vary depending on fee model (i.e. monthly subscription vs commission)

Feature	Decentralised Exchanges (DEXs)	Centralised Exchanges (CEXs)
Security	Higher security due to no central point of failure	Lower security, prone to large-scale hacks
Control Over Assets	Full control over private keys and assets	Users must trust the exchange with their private keys
Regulation	Less regulated, offering more freedom	Heavily regulated, leading to restrictions
Liquidity	Rising liquidity without significantly impacting market price	Higher liquidity, with more users and trading pairs
Ease of Use	More complex, requiring knowledge of wallets and keys	User-friendly interfaces, suitable for beginners

Benefit	Description
Expands smart contract capabilities	AI oracles enable smart contracts to access and process real-world data, significantly broadening their potential use cases beyond simple on-chain transactions
Automation and efficiency	By automating data retrieval and validation, AI oracles streamline processes, reduce manual intervention, and improve efficiency across various industries
Trust and transparency	AI oracles, especially decentralised ones, enhance trust and transparency by providing verifiable and tamper-proof data sources for smart contracts
Innovation and new possibilities	The combination of AI and blockchain through oracles opens up new avenues for innovation, enabling the creation of decentralised applications that were previously unimaginable

	Sharding	Layer 2 Solutions	Sidechains
Definition	Divides blockchain into smaller pieces called shards, each processing its own transactions and smart contracts	Builds secondary protocols on top of the main blockchain to handle transactions off-chain	Separate blockchains linked to the main chain, allowing for independent transaction processing
Scalability	Increases capacity by parallel processing across multiple shards	Offloads transactions from the main chain to enhance speed without altering base layer	Expands network capacity by adding parallel chains
Security	Maintains security through cross-shard communication and consensus mechanisms	Security is partially dependent on the underlying blockchain, with some added risks	Potentially weaker security compared to the main chain, risk of isolated attack vectors
Complexity	Requires sophisticated coordination and consensus among shards	Involves complex off-chain protocols and transaction routing	Needs robust mechanisms for cross-chain communication and consensus
Examples	Ethereum 2.0	Bitcoin's Lightning Network, Ethereum's Optimistic Rollups	Polygon, Rootstock

Consensus Mechanism	Energy Consumption	Scalability	Security	Decentralisation	Example Blockchains
Proof of Work (PoW)	High	Low	High	High	Bitcoin, Ethereum (historically)
Proof of Stake (PoS)	Low	High	Medium	Medium	Ethereum 2.0, Cardano, Solana
Delegated Proof of Stake (DPoS)	Low	High	Medium	Low	EOS, Tron, Steemit
Practical Byzantine Fault Tolerance (PBFT)	Low	Medium	High	Low	Hyperledger Fabric
Proof of Authority (PoA)	Low	High	Medium	Low	VeChain, POA Network
Proof of Elapsed Time (PoET)	Low	Medium	Medium	Low	Hyperledger Sawtooth
DAG-based consensus	Low	High	Medium	Varies	Hashgraph, IOTA

	aelf Playground	Remix IDE	EthFiddle	ChainIDE
Chain focus	aelf	Ethereum	Ethereum	More than 14 chains (Ethereum, Polygon, etc.)
Interface	Sleek and simple	Comprehensive and advanced	Spartan and focused	Neat, yet comprehensive
Core features	Smart contract templatesAI smart contract auditsSmart contract testingBuilt-in deployment	Visual debuggerSupport for pluginsAI-powered co-pilotConnectivity to local filesystems	Automatic compilationsOne-click sharing	Support for various public and consortium blockchainsOne-stop debugging, testing, and deploymentPre-installed plugins
Ease of use	High	Moderate	Low	Moderate
Target audience	Beginner developers	Intermediate to advanced developers	Advanced developers	Intermediate to advanced developers

Stablecoin Type	Description	Examples
Fiat-collateralised	Backed by fiat currencies held in reserve by the issuer	USDT, USDC, PYUSD
Crypto-collateralised	Backed by other cryptocurrencies, often over-collateralised to account for price fluctuations	DAI, MIM
Algorithmic	Use algorithms and smart contracts to maintain price stability without collateral	FRAX, UST

Agent Type	Description	Learning Model
Reactive Agents	Respond to current situations without memory of past events	Basic rule-based systems or decision trees
Model-Based Agents	Use an internal model of the world to make decisions	Bayesian networks or Markov Decision Processes (MDPs)
Goal-Based Agents	Have a specific goal and plan actions to achieve it	Reinforcement learning (RL)
Utility-Based Agents	Maximise a utility function to evaluate and achieve goals	Multi-objective optimisation algorithms or advanced RL models
Learning Agents	Continuously improve performance based on experiences	Deep learning, LLMs, or GANs
Collaborative Agents	Work together to achieve a common goal	Federated learning
Autonomous Agents	Operate without human intervention	Deep reinforcement learning, hybrid models
Intelligent Agents (General AI)	Capable of general intelligence, similar to humans	Very large, complex models combining deep learning, NLP, and RL
Social Agents	Interact with humans in a natural way	LLMs for NLP tasks, smaller models for emotion recognition

VC Fund	Description
Andreessen Horowitz (a16z)	A major player investing in layer 1s, DeFi, NFTs, and more
Pantera Capital	Focused exclusively on blockchain and crypto-related ventures
Polychain Capital	Known for making early investments in blockchain innovators
Coinbase Ventures	The investment arm of Coinbase, backing promising crypto start-ups
Digital Currency Group (DCG)	Ensures the growth and development of the global financial system
Blockchain Capital	One of the first VC funds to focus exclusively on blockchain technology
Paradigm	Invests in disruptive blockchain projects and crypto trading
Binance Labs	The VC and incubator arm of Binance, supporting blockchain start-ups
Solana Ventures	Invests in projects based on the Solana blockchain ecosystem
Borderless Capital	Primarily backs ventures within the Algorand ecosystem
ParaFi Capital	Focuses on DeFi projects and protocols
Hack VC	Supports early-stage Web3 and AI start-ups

ZKP Type	Description	Application
Interactive Zero-Knowledge Proofs	Involve multiple rounds of interaction between prover and verifier	Authentication and secure communication protocols
Non-Interactive Zero-Knowledge Proofs	Require a single message from prover to verifier, useful for scalability	Blockchain transactions and decentralised systems
Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs)	Provide succinct and easily verifiable proofs	Cryptocurrencies and smart contracts
Zero-Knowledge Succinct Transparent Arguments of Knowledge (zk-STARKs)	Offer transparency and post-quantum security	Scalable blockchain solutions and privacy-focused applications
Zero-Knowledge Sigma Protocols	Three-step, interactive proofs used in complex computations	Multi-party computations and authentication mechanisms
Zero-Knowledge Set Membership	Prove membership of an element in a set without revealing details	Privacy-preserving database queries

Blockchain	Explorer(s)	Description
Bitcoin	Blockchain.com, Blockchair	Blockchain.com: User-friendly with comprehensive data and chartsBlockchair: Supports multiple blockchains, offers advanced filtering.
Ethereum	Etherscan, Blockscout	Etherscan: Go-to Ethereum explorer with detailed information on transactions, contracts, and tokensBlockscout: Open-source, fast, and community-focused
Solana	Solscan, Explorer.solana.com	Solscan: A popular choice with a user-friendly interfaceExplorer.solana.com: Offers detailed insights into Solana's high-speed transactions and on-chain activity
Layer 2 (General)	Arbiscan, Starkscan	Arbiscan (Arbitrum): Tracks activity on the Arbitrum layer-2 networkStarkscan (StarkNet): Provides insights into transactions and state changes on StarkNet, a zero-knowledge rollup solution

Family	Description
Lattice-based cryptography	Relies on the difficulty of solving problems in lattices (geometric structures with repeating points). It is currently considered one of the most promising candidates for post-quantum cryptography due to its strong security guarantees and efficiency.
Code-based cryptography	Uses error-correcting codes to create cryptographic systems. It has a long history of research and is known for its strong security properties.
Hash-based cryptography	Based on the security of cryptographic hash functions. It is one of the oldest and well-studied forms of post-quantum cryptography.
Multivariate cryptography	Uses systems of multivariate polynomial equations over finite fields. It is known for its efficiency and potential for use in digital signatures.
Isogeny-based cryptography	Based on the difficulty of finding isogenies (maps) between elliptic curves. It is a relatively new area of research but has shown promising security properties.

Feature	Mini Apps	Telegram Bots	Web2 Apps
Functionality	Multi-purpose, Web3-friendly	Single-purpose, task-oriented	Comprehensive features
UX/UI	Interactive, seamless integration	Basic, text-based interactions	Polished, highly interactive
Security	Decentralised-friendly, blockchain linked	Centralised, minimal encryption	Centralised, variable security
Privacy	Minimal data collection	Limited data use	High data collection
Examples	Catizen, Blum, Maoyan Movie (猫眼电影), Hamster Kombat	Skeddy Bot, File to Bot, BotFather	Instagram, TikTok, Grab, Zoom, Youtube

Blockchain Type	Description	Unique Feature
Public	Open and permissionless networks, allowing anyone to participate in the process of validating transactions and adding blocks to the chain	Decentralisation and transparency: No single entity controls the network, and all transactions are publicly auditable
Private	Permissioned networks, where access and participation are restricted to authorised entities	Privacy and control: Offer greater control over data and access. Suitable for enterprise applications.
Hybrid	Combine elements of both public and private blockchains	Balance of openness and control: Organisations get the benefits of both worlds
Consortium	Semi-private blockchains, where a group of organisations governs the network	Collaboration and efficiency: Facilitate collaboration and data sharing among a select group of participants

For Developers	For Users
Monetisation opportunities	Greater access to a diverse and expanding pool of high-quality AI data and models
Increased visibility and collaboration opportunities	Cost savings, improved efficiencies in transactions
Fairer compensation and recognition	Retention of control over personal data

Category	Projects	Key Features
Digital Assets	Alethea AI, SUI Agents	iNFTs, CharacterGPT, AI personas, project validation
Gaming & Entertainment	AI Arena, AI Waifu	AI-powered NFTs, PvP battles, virtual characters, interactive storytelling
DeFi & Trading	Zerebro, Based Agent by Coinbase, Sekoia	AI trading bots, privacy-preserving DeFi, zero-knowledge proofs
Productivity	aixbt, aevatar Intelligence	Task automation, Web3 integration, blockchain development
Knowledge Management	Truth Terminal, Ocean Protocol	Fact-checking, data marketplaces, decentralised knowledge

Feature	Smart Contracts	AI-powered Smart Contracts
Data analysis	Limited	Comprehensive
Decision-making	Predefined	Dynamic and adaptive
Learning capability	No	Yes, through machine learning
Predictive analytics	No	Yes
Efficiency	High	Even higher
Accuracy	Good	Excellent

Aggregated Blockchain	Description
Polygon AggLayer	A prominent layer-2 scaling solution for Ethereum, AggLayer creates a unified network of interconnected chains for shared liquidity and interoperability
Cosmos Network	Focused on 'Internet of Blockchains'. Enables interoperability between different sovereign blockchains. The Inter-Blockchain Communication protocol (IBC) allows chains to communicate and exchange assets with each other.
Polkadot	Parachains that can communicate and share data through the Polkadot Relay Chain, enabling a variety of use cases, including DeFi, identity management, and supply chain tracking
Avalanche	Creation of subnets, custom blockchains that can interoperate with each other

Factor	What It Means	Why It Matters
Computing Costs and API Pricing	Proprietary models like GPT-4 charge per token, while open-source models like LLaMA allow free self-hosting.	Helps businesses balance performance with budget constraints—important for scaling AI applications.
Deployment Options	Cloud-hosted APIs (OpenAI, Google) vs. self-hosted models (LLaMA, NeoX) for on-premise security.	On-premise AI is better for data privacy, while cloud models offer ease of integration and lower maintenance.
Customisation	Open-source models allow deeper modification, whereas closed models provide strong out-of-the-box performance.	Businesses needing domain-specific AI agents may prefer fine-tuning, while general-use AI benefits from pre-trained efficiency.
Performance Benchmarks	LLMs vary in reasoning depth, response speed, and ability to retain context across interactions.	Affects real-time AI applications like customer support and decision-making automation.