System Architecture

AetherSec’s system architecture is a multi-layered, modular design that tightly integrates AI’s intelligent analysis capabilities with blockchain’s decentralized features to create an efficient and scalable security ecosystem. Below is a detailed breakdown of the architecture and how its layers collaborate.

Data Collection Layer

Function

The data collection layer serves as AetherSec’s foundation, extracting real-time data from blockchain networks to provide input for AI analysis.

Implementation

- On-Chain Data: Captures transaction records, contract state changes, and event logs (Event Logs) by listening to blockchain nodes (e.g., Ethereum’s Geth or BSC’s Full Node).

- Off-Chain Supplements: Incorporates threat intelligence from decentralized storage (e.g., IPFS) and external data submitted by the community (e.g., known malicious address lists).

- Data Standardization: Converts multi-source data (e.g., transaction amounts, Gas usage, call frequencies) into a uniform format for AI processing.

Role of Blockchain

- Data is stored with block hashes and timestamps, ensuring authenticity and traceability.

- Light nodes or oracles optimize data collection efficiency, reducing reliance on full nodes.

AI Processing Layer

Function

The AI processing layer runs Aether Guardian, handling threat detection, behavior analysis, and response strategy generation, forming the system’s intelligent core.

Implementation

- Distributed Computing: Aether Guardian instances operate across multiple nodes, each processing local data and generating preliminary threat assessments.

- Model Collaboration: Federated learning aggregates model updates from nodes, periodically producing a global threat detection model stored on the blockchain.

- Real-Time Inference: Employs efficient algorithms (e.g., GRU-based sequence analysis or lightweight CNNs) to process data streams in real time, outputting threat confidence scores.

Role of Blockchain

- Model updates are recorded as encrypted hashes on-chain, ensuring version control and consistency.

- Inference results across nodes are validated via consensus mechanisms (e.g., PoS), preventing erroneous judgments from individual nodes from affecting the system.

Blockchain Execution Layer

Function

The blockchain execution layer stores critical data, executes security policies, and logs operations, serving as the system’s trusted execution environment.

Implementation

- Data Storage: Threat detection results, AI model parameters, and response records are stored on-chain or in decentralized storage (e.g., Arweave), linked via hash indices.

- Smart Contract Logic: Predefines multiple response rules, e.g., automatically pausing transactions and notifying users if the threat score exceeds 80%.

- Consensus Mechanism: Uses efficient consensus (e.g., DPoS or PBFT) to ensure node agreement on threat responses.

AI Interaction

- The AI processing layer passes threat assessments as parameters to smart contracts (e.g., “pause transaction ID: 0x123”).

- Post-execution, smart contracts provide feedback to AI for further optimization (e.g., adjusting response thresholds).

Community Interaction Layer

Function

The community interaction layer connects users, node operators, and developers through token incentives and governance mechanisms, driving ecosystem growth.

Implementation

- Incentive Distribution: Smart contracts automatically allocate AETH tokens based on node computational contributions or threat intelligence submissions.

- Governance Voting: The community proposes and votes on system upgrades (e.g., adding new threat detection modules) via an on-chain DAO.

- User Interface: Provides a decentralized application (DApp) for users to view security status, submit intelligence, or subscribe to services.

Role of Blockchain

- The entire process of voting and reward distribution is recorded on-chain, ensuring transparency.

- AETH token circulation and burning are managed via blockchain to maintain economic balance.

System Workflow

1. Data Collection: The data layer captures transactions and contract activities from the blockchain, forwarding them to the AI processing layer.

2. Threat Analysis: Aether Guardian analyzes the data, generates threat reports, and uploads them to the blockchain.

3. Policy Execution: The blockchain execution layer triggers responses via smart contracts (e.g., freezing suspicious accounts).

4. Community Feedback: Nodes validate results, users provide feedback, and the incentive layer distributes rewards while updating models.

5. Iterative Optimization: AI refines itself based on execution feedback and community input, with new model versions recorded on-chain.

Architectural Advantages

- Modularity: Independent layers facilitate upgrades and scalability.

- Decentralization: No single-point dependencies enhance system resilience.

- Efficient Collaboration: Clear division of roles between AI and blockchain ensures seamless data flow.