Can ML-KEM be used for purposes other than exchanging AES-GCM keys

Question

ML-KEM (Message-Locked Key Encapsulation Mechanism) is primarily used for key exchange. What other scenarios beyond AES-GCM key distribution can benefit from its unique properties?

Answer 1

Yes, ML-KEM (Message-Locked Key Encapsulation Mechanism) can be used for scenarios beyond just exchanging AES-GCM keys. Its unique properties of deriving keys based on message content while maintaining confidentiality and security make it suitable for various other applications.

1. Secure Data Deduplication

• Purpose: Deduplicate data by storing only one copy of identical files across a storage system.
• How ML-KEM Helps:
  • The encryption key is derived from the content itself.
  • Identical files will generate the same key and ciphertext, enabling deduplication without compromising confidentiality.
• Example: Cloud storage systems where the same file is uploaded multiple times by different users.

2. Content-Based Access Control

• Purpose: Grant access to encrypted content only if the correct plaintext is known.
• How ML-KEM Helps:
  • The key encapsulation mechanism ties decryption capability to the correct content, ensuring that only entities with the right message can access the corresponding data.
• Example: Secure voting or lottery systems where decryption is conditional on specific inputs.

3. Encrypted Database Search

• Purpose: Enable secure search operations on encrypted data.
• How ML-KEM Helps:
  • Derives deterministic keys for consistent data, allowing specific records to be identified and decrypted based on content without revealing other data.
• Example: Searching for encrypted documents in a database using content-based encryption.

4. Secure File Sharing

• Purpose: Allow multiple parties to access the same encrypted data securely.
• How ML-KEM Helps:
  • Encapsulated keys can be distributed securely based on the shared content, enabling collaborative environments.
• Example: A group of researchers sharing encrypted datasets tied to specific content.

5. Policy-Based Encryption

• Purpose: Enforce encryption policies tied to specific data characteristics.
• How ML-KEM Helps:
  • The key encapsulation can be linked to metadata or attributes, enabling encryption that aligns with policy requirements.
• Example: Encrypting sensitive financial data with keys derived from specific transaction details.