Zektra Architecture

Zektra’s architecture is composed of four primary layers working in synergy:

A. Encrypted Data Layer (Owner-Side Encryption + Encrypted Vaults)

• Data owners encrypt datasets locally before uploading.

• Encrypted datasets are stored in decentralized vaults or owner-preferred storage.

• Keys remain solely with data owners—Zektra never sees plaintext.

This ensures absolute data sovereignty and immunity from leaks.

B. ZK Training Layer (Homomorphic Computation + ZK Proof-of-Training)

This is the core engine of Zektra.

• Training occurs directly on encrypted data via homomorphic encryption.

• Each computation step produces a zero-knowledge proof verifying correctness.

• Gradient updates, loss functions, and model transformations are validated cryptographically.

This ensures training integrity without revealing dataset contents.

C. Compute Layer (Staked Nodes + Decentralized Processing)

A robust network of compute providers:

• Nodes stake $ZEKTRA to join the network.

• Jobs are assigned based on stake, performance, and reliability.

• Incorrect computation leads to proof failure and slashing.

• Compute providers earn rewards by producing valid proofs.

This creates a reliable, scalable, trustless training environment.

D. Marketplace & Governance Layer (Datasets, Models, Payments, DAO)

Zektra includes a permissionless marketplace where:

• Data owners list encrypted datasets.

• Developers submit training jobs.

• Compute providers bid or compete for workloads.

• $ZEKTRA is used for payments, staking, rewards, and governance.

A decentralized governance DAO manages upgrades, economic parameters, and ecosystem growth.