Future Features: Adaptive AI Routing

As blockchain analytics tools become more sophisticated, privacy protocols must evolve to stay ahead. The next frontier for Verdant Privacy is the integration of Machine Learning (ML) into our routing logic. This initiative is known as Adaptive AI Routing.

The Limitation of Randomness

Current privacy tools often rely on mathematical randomness (RNG) to determine delays and split amounts. However, true randomness is distinct from "human" behavior. Advanced AI models used by surveillance firms can sometimes distinguish between a programmed random pattern and a genuine human pattern.

The AI Solution

Verdant plans to train a lightweight Neural Network on public Solana blockchain data. The goal of this AI is to learn what "normal" behavior looks like for different types of users.

1. Predictive Congestion Analysis The AI model will analyze historical chain data to predict gas fee spikes and network congestion. It will then optimize routing schedules to execute transactions during cost-efficient windows, or conversely, during high-traffic windows to better hide the transaction in the crowd.

2. Mimicry Algorithms Instead of simply delaying a transaction by a random number of seconds, the AI will schedule transactions based on human probability curves.

• Example: If a user usually trades between 08:00 and 17:00 UTC, the AI will prioritize routing traffic during these hours and reduce activity during the user's "sleep" cycle.

3. Adversarial Pathfinding We intend to build a "Red Team" AI that constantly attempts to de-anonymize our own testnet traffic. The routing engine will use this feedback loop to continuously learn which patterns are most traceable and automatically adjust its strategy to avoid them.