Quantum computers are likely to render the current public-key cryptography used for protecting modern internet traffic, digital signatures, and encryption useless. <\/p>\n\n\n\n
In response, NIST<\/a> has developed ML-KEM as the main post-quantum key encapsulation method. The guide below will introduce the concept of ML-KEM, how it functions, in which projects it is used, and how organisations can implement it.<\/p>\n\n\n\n ML-KEM is a Module-Lattice-Based Key-Encapsulation Mechanism<\/strong>. NIST standardised it in FIPS 203 as the main algorithm for post-quantum key exchange.<\/p>\n\n\n\n The task of ML-KEM is very simple but crucial at the same time: two entities generate a common secret key over an insecure channel that everyone can listen to or even interfere with. Once the common secret is obtained, the parties may encrypt the information using any conventional symmetric ciphering algorithm, e.g., AES.<\/p>\n\n\n\n ML-KEM differs from RSA and other key-exchange schemes<\/strong> since it is resistant not only to classical computers but also to quantum ones. Thus, it can serve as the basis for future-proof TLS, VPNs, and messaging services.<\/p>\n<\/blockquote>\n\n\n\n Massive quantum computers can compromise traditional algorithms like RSA, Diffie-Hellman, and Elliptic Curve cryptography using Shor\u2019s algorithm. All the data protected by these cryptographic algorithms becomes unprotected once such a computer emerges.<\/p>\n\n\n\n NIST started its Post-Quantum Cryptography program in 2016 to develop new algorithms before that moment happens. After multiple rounds of evaluations, in 2022, NIST selected CRYSTALS-Kyber as a key-encapsulation algorithm finalist. The organization optimized this algorithm, set standard parameters, and created ML-KEM, which is described in FIPS 203.<\/p>\n<\/blockquote>\n\n\n\n Modern organisations have an obvious need to protect their data from harvest now, decrypt later attacks<\/a> and to be able to switch to new algorithms once they become standard. ML-KEM provides both requirements.<\/p>\n\n\n\n ML-KEM allows two participants to agree upon a shared secret over an open channel by following three simple steps. While the security of ML-KEM depends on the hardness of the module-lattice problem, the protocol itself remains simple and easy to follow without involving any complex mathematics.<\/p>\n\n\n\n The whole communication takes a few milliseconds and cannot be deciphered by any eavesdropper who observes all the public values.<\/p>\n\n\n\n There are some key features provided by ML-KEM that allow the use of this post-quantum solution in practice.<\/p>\n\n\n\n The result is a set of obvious operational benefits. Small key sizes allow reducing the load on the communication channel and storage space. Hybrid implementation of ML-KEM with classical encryption schemes can be done now and switched to the full implementation later on.<\/p>\n\n\n\n Teams can deploy ML-KEM whenever long-term confidentiality is a must-have and the quantum threat cannot be dismissed. It is already in use in some pilot implementations and updates of standard specifications.<\/p>\n\n\n\n Most teams initially opt for hybrid approaches. They mix ML-KEM with traditional algorithms like X25519 and RSA so that even if one algorithm fails in the future, each connection will remain protected.<\/p>\n\n\n\n Well-tested libraries and services have ready-to-use ML-KEM capabilities. The open-source examples are liboqs for experimenting, OpenSSL version 3.5 and above with hybrid groups implemented, and BoringSSL. The companies that provide ML-KEM in a production setting are AWS through AWS-LC and KMS and Cloudflare via TLS and key management.<\/p>\n\n\n\n Thus, the team will have a standards-compliant library that is secure and maintainable.<\/p>\n\n\n\n Recommended:<\/strong> What is ML-DSA (CRYSTALS-Dilithium)? The Future of Digital Signatures Beyond RSA and ECC<\/a><\/p>\n\n\n\nWhat are the Main Takeaways about ML-KEM?<\/h2>\n\n\n\n
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<\/a>What Is ML-KEM?<\/h2>\n\n\n\n
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<\/a>Why was ML-KEM Created?<\/h2>\n\n\n\n
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<\/a>How does ML-KEM work?<\/h2>\n\n\n\n
<\/a>Key Generation<\/h3>\n\n\n\n
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<\/a>Encapsulation<\/h3>\n\n\n\n
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<\/a>Decapsulation<\/h3>\n\n\n\n
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<\/a>What Are the Important Characteristics and Advantages of ML-KEM?<\/h2>\n\n\n\n
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Where Are ML-KEM Teams Deployed?<\/h2>\n\n\n\n
<\/a>Common Scenarios<\/h3>\n\n\n\n
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Which ML-KEM Implementations and Best Practices Should the Teams Apply?<\/h2>\n\n\n\n
For a reliable deployment, the teams should do the following:<\/h3>\n\n\n\n
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How Does ML-KEM Compare to Traditional Key Exchange?<\/h2>\n\n\n\n