AI-Powered SLS

Using AI to enhance transaction-level security for Zayn Network participants

The AI-powered Sequencer Level Security (SLS) on Zayn Network will be implemented using a sophisticated multi-step technical approach. The central sequencer will integrate an AI-driven transaction analysis module that simulates and inspects incoming transactions in real time. This module employs machine learning models trained on historical blockchain data to identify patterns indicative of malicious activities, such as reentrancy attacks, exploitative token transfers, or abnormal transaction sequences. The system's hybrid detection approach consists of two layers of transaction assessment: isolated simulation and contextual simulation. In the isolated simulation, each transaction is analyzed independently at the chain's current state, allowing for parallel processing of transactions. This initial phase focuses on flagging transactions that immediately display high-risk attributes, providing a rapid first line of defense. However, isolated simulation alone can miss multi-transaction exploits or those dependent on specific block conditions.

To address this, the second layer—contextual simulation—comes into play. Here, transactions are sequentially simulated within the context of their specific block, accounting for how earlier transactions might alter the blockchain's state and impact the ones that follow. This sequential simulation detects complex, multi-step exploits that isolated checks might overlook, such as an attack that depends on prior state changes within the same block. During this phase, each transaction is analyzed in conjunction with its potential dependencies on other transactions, allowing the AI model to identify interactions that could lead to vulnerabilities. This thorough analysis ensures that malicious transactions are not simply detected based on isolated behaviors but also on their broader impact within the network. Transactions identified as suspicious are quarantined for further evaluation and must meet specific release criteria before inclusion in the block, adding an extra layer of security to the network's operations.

Operationally, the AI-powered SLS will serve as a proactive security mechanism within Zayn Network's transaction processing. The sequencer will maintain a dynamic quarantine pool where flagged transactions are periodically reviewed against a set of release criteria, including time-based rules, administrative intervention, and staking requirements. This setup enables the network to adapt to varying risk levels and operational needs. The AI model will continue to evolve, updating its detection capabilities as it learns from ongoing transaction patterns. A dedicated operational team will oversee the AI’s performance, fine-tuning its algorithms and responding to exceptional cases, ensuring that the SLS protocol remains both robust and efficient in protecting the network's integrity without compromising transaction throughput.