Chainfeeds Briefing:
Ika is building a new security verification layer: serving as a dedicated signature protocol for the Sui ecosystem while also providing standardized cross-chain solutions for the entire industry.
Article Source:
https://ybbcapital.substack.com/p/from-suis-sub-second-mpc-network
Article Author:
YBB Capital
Perspective:
YBB Capital: Differences between various solutions: 1) Performance and Latency: FHE (Zama/Fhenix) has high latency due to frequent bootstrapping, but provides the strongest data protection in encrypted state; TEE (Oasis) has the lowest latency, close to normal execution, but requires hardware trust; ZKP (Aztec) has controllable batch proof delay, with single transaction latency between the two; MPC (Partisia) has medium-low latency, most affected by network communication. 2) Trust Assumptions: FHE and ZKP are based on mathematical difficulties, requiring no third-party trust; TEE relies on hardware and manufacturers, with firmware vulnerability risks; MPC relies on semi-honest or at most t anomaly models, sensitive to participant numbers and behavior. 3) Scalability: ZKP Rollup (Aztec) and MPC sharding (Partisia) naturally support horizontal expansion; FHE and TEE expansion requires consideration of computational resources and hardware node supply. 4) Integration Difficulty: TEE projects have the lowest access threshold, with minimal programming model changes; ZKP and FHE require specialized circuits and compilation processes; MPC needs protocol stack integration and inter-node communication. It seems that whether FHE, TEE, ZKP, or MPC, all face a Blockchain Trilemma in solving practical use cases: "performance, cost, security". Although FHE is theoretically attractive for privacy protection, it is not superior to TEE, MPC, or ZKP in all aspects. Poor performance makes FHE difficult to popularize, with computational speed far behind other solutions. In applications sensitive to real-time performance and cost, TEE, MPC, or ZKP are often more feasible. Trust and applicable scenarios also differ, with TEE and MPC offering different trust models and deployment convenience, while ZKP focuses on verifying correctness. As industry perspectives suggest, different privacy tools have their advantages and limitations, with no "one-size-fits-all" optimal solution. For off-chain complex computation verification, ZKP can efficiently solve issues; for computations requiring multiple parties to share private states, MPC is more direct; TEE provides mature support in mobile and cloud environments; while FHE is suitable for extremely sensitive data processing, but currently requires hardware acceleration. FHE is not "universally superior", and technology choice should depend on application needs and performance trade-offs. Future privacy computing will likely be a result of multiple complementary and integrated technologies, rather than a single solution winning out. For instance, Ika's design emphasizes key sharing and signature coordination (users always retain one private key), with its core value being decentralized asset control without custody. In comparison, ZKP excels at generating mathematical proofs for on-chain state or computation result verification. They are not simple substitutes or competitors, but more like complementary technologies: ZKP can verify cross-chain interaction correctness, reducing trust in bridge providers, while Ika's MPC network provides a "bottom-level foundation of asset control rights" that can be combined with ZKP to build more complex systems. Additionally, Nillion is beginning to merge multiple privacy technologies to enhance overall capabilities, with its blind computing architecture seamlessly integrating MPC, FHE, TEE, and ZKP to balance security, cost, and performance. Therefore, the future privacy computing ecosystem will tend to use the most suitable technology components to construct modular solutions.
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