Ika Network Supported by the Sui Foundation: Sub-second MPC Technology Innovation

1. Overview and Positioning of the Ika Network

Ika Network is an innovative infrastructure based on multi-party secure computing ( MPC ) technology, strategically supported by the Sui Foundation. Its most notable feature is sub-second response speed, which is a first in MPC solutions. Ika is highly compatible with the underlying design of the Sui blockchain in terms of parallel processing, decentralized architecture, and will be directly integrated into the Sui development ecosystem in the future, providing plug-and-play cross-chain security modules for Sui Move smart contracts.

Ika is building a new type of security verification layer, serving both as a dedicated signature protocol for the Sui ecosystem and providing standardized cross-chain solutions for the entire industry. Its layered design balances protocol flexibility and development convenience, and is expected to become an important practical case for the large-scale application of MPC technology in multi-chain scenarios.

1.1 Core Technology Analysis

The technical implementation of the Ika network revolves around high-performance distributed signatures, with key innovations including:

• 2PC-MPC Signing Protocol: The user's private key signing operation is decomposed into a process involving both the "user" and the "Ika network" as participating roles, using a broadcasting model to reduce communication overhead.

• Parallel processing: Utilize parallel computing to decompose a single signature operation into multiple concurrent subtasks, significantly improving speed in conjunction with Sui's object parallel model.

• Large-scale node network: Supports thousands of nodes participating in signing, with each node holding only a part of the key fragment, enhancing security.

• Cross-chain control and chain abstraction: Allows smart contracts on other chains to directly control accounts in the Ika network (dWallet), enabling cross-chain verification by deploying lightweight clients of the corresponding chain.

1.2 The impact of Ika on the Sui ecosystem

The launch of Ika may have the following impacts on Sui:

• Enhance cross-chain interoperability capabilities, supporting low-latency access to the Sui network for assets such as Bitcoin and Ethereum.

• Provides a decentralized asset custody mechanism to enhance security.

• Simplify cross-chain interaction processes and achieve chain abstraction.

• Provide a multi-party verification mechanism for AI automation applications to enhance security and credibility.

1.3 Challenges faced by Ika

The main challenges faced by Ika include:

• There are already various mature cross-chain solutions in the market, and Ika needs to seek a balance between decentralization and performance to break through.

• The issue of difficulty in revoking signature permissions in the MPC scheme still needs to be resolved.

• Dependence on the stability of the Sui network, as well as the adaptation requirements brought by future upgrades to the Sui consensus mechanism.

2. Comparison of Projects Based on FHE, TEE, ZKP, or MPC

2.1 FHE

Zama & Concrete:

• General compiler based on MLIR
• Layered Bootstrapping Strategy
• Mixed encoding support
• Key Packaging Mechanism

Fhenix:

• Optimization for the EVM instruction set
• Encrypted Virtual Register
• Off-chain oracle bridging module

2.2 TEE

Oasis Network:

• Layered Trusted Root Concept
• ParaTime interface uses Cap'n Proto serialization
• Durable Log Module

2.3 ZKP

Aztec:

• Noir compilation
• Incremental Recursive Technology
• Parallelized Depth-First Search Algorithm
• Light Node Mode

2.4 MPC

Partisia Blockchain:

• Extension based on the SPDZ protocol
• The preprocessing module generates Beaver triples
• gRPC communication, TLS 1.3 encrypted channel
• Dynamic load balancing parallel sharding mechanism

3. Privacy Computing FHE, TEE, ZKP and MPC

Overview of Different Privacy Computing Solutions

• Fully Homomorphic Encryption ( FHE ): allows arbitrary computation on encrypted data, theoretically complete but with high computational overhead.

• Trusted Execution Environment ( TEE ): A hardware-provided isolated execution environment, with performance close to native but reliant on hardware trust.

• Multi-Party Computation ( MPC ): Allows multiple parties to compute together without revealing their respective inputs, no single point of trust but with high communication overhead.

• Zero-Knowledge Proof ( ZKP ): A method to verify that a statement is true without revealing additional information, typical implementations include zk-SNARK and zk-STARK.

Adaptation scenarios of 3.2 FHE, TEE, ZKP and MPC

• Cross-chain signing: MPC and TEE are more suitable, FHE theory is feasible but has high overhead.

• DeFi multi-signature wallets, etc.: MPC is mainstream, TEE is also applied, and FHE is mainly used for upper-layer privacy logic.

• AI and Data Privacy: FHE has obvious advantages, MPC is used for federated learning, and TEE can run models directly in a protected environment.

3.3 The differences among various schemes

• Performance and Latency: FHE is the highest, TEE is the lowest, ZKP and MPC are in between.

• Trust assumptions: FHE and ZKP are based on mathematical problems, TEE relies on hardware, and MPC depends on the behavior of participants.

• Scalability: ZKP and MPC are easily horizontally scalable, while FHE and TEE are limited by computational resources.

• Integration Difficulty: TEE is the lowest, ZKP and FHE require specialized circuits, and MPC requires protocol stack integration.

IV. Market Perspective: "FHE is Superior to TEE, ZKP, or MPC" Analysis

FHE is not superior to other schemes in all aspects. Different technologies have their own advantages and limitations:

• ZKP is suitable for off-chain complex computation verification.
• MPC is suitable for multi-party private state sharing computation.
• TEE is mature in mobile and cloud environments.
• FHE is applicable for processing extremely sensitive data, but requires hardware acceleration.

The future privacy computing ecosystem may tend to integrate multiple complementary technologies to build modular solutions. For example, Nillion combines MPC, FHE, TEE, and ZKP to achieve a balance between security, cost, and performance. The choice of technology should be based on specific application requirements and performance trade-offs.