Fully homomorphic encryption: a solution to security problems in the AI era

robot
Abstract generation in progress

AI Security issues attract follow, fully homomorphic encryption becomes the solution

With the rapid development of artificial intelligence technology, the emergence of advanced AI systems like Manus has sparked deep reflection within the industry regarding AI security issues. Manus has demonstrated exceptional performance beyond its peer large models in the GAIA benchmark test, capable of independently completing complex tasks such as multinational business negotiations. However, this high level of intelligence also brings potential security risks.

! Manus brings the dawn of AGI, AI security is also worth pondering

The development of AI faces the dilemma of balancing efficiency and security. The closer a single intelligence is to AGI (Artificial General Intelligence), the higher the risk of black-box decision-making. However, although multi-agent collaboration can spread risks, it may affect key decisions due to communication delays. The evolution of Manus has inadvertently amplified the inherent security risks of AI, including data privacy breaches, algorithmic bias, and adversarial attacks.

To address these challenges, fully homomorphic encryption (FHE) technology has become a powerful tool for solving security issues in the AI era. FHE allows computations to be performed on encrypted data without the need to decrypt it, enabling the processing of sensitive information. At the data level, all information input by users can be processed in an encrypted state, preventing the leakage of raw data. At the algorithm level, FHE's implementation of "encrypted model training" ensures that even developers cannot glimpse the decision-making path of the AI. At the collaborative level, communication between multiple agents can utilize threshold encryption, enhancing the overall security of the system.

The Web3 field has always focused on security issues, giving rise to various encryption methods. In addition to fully homomorphic encryption (FHE), there are also zero trust security models and decentralized identities (DID). However, compared to other encryption methods, FHE, as a newly emerged technology, is considered key to solving AI Security problems.

Although Web3 security technology may not have a direct connection with ordinary users, its impact is profound. In today's rapidly developing AI landscape, building a robust security defense system has become particularly important. Fully Homomorphic Encryption (FHE) not only addresses the current security challenges faced by AI but also paves the way for a more powerful AI era in the future. As AI approaches human intelligence, adopting advanced encryption technologies to protect data and system security will become an inevitable trend.

View Original
This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.
  • Reward
  • 4
  • Share
Comment
0/400
GateUser-3824aa38vip
· 12h ago
Encryption is productivity.
View OriginalReply0
CryptoSourGrapevip
· 12h ago
Privacy is fundamental.
View OriginalReply0
GhostAddressMinervip
· 12h ago
Privacy is power
View OriginalReply0
SchrodingersFOMOvip
· 12h ago
Privacy is security
View OriginalReply0
Trade Crypto Anywhere Anytime
qrCode
Scan to download Gate app
Community
English
  • 简体中文
  • English
  • Tiếng Việt
  • 繁體中文
  • Español
  • Русский
  • Français (Afrique)
  • Português (Portugal)
  • Bahasa Indonesia
  • 日本語
  • بالعربية
  • Українська
  • Português (Brasil)