Inferensys

Glossary

Quantum-Safe Cryptography

Cryptographic algorithms designed to be secure against an attack by a cryptographically relevant quantum computer, ensuring the long-term integrity and non-repudiation of archived AI audit trails.
Auditor reviewing AI-generated audit trail on laptop, blockchain-like immutable records visible, home office evening.
POST-QUANTUM SECURITY

What is Quantum-Safe Cryptography?

Quantum-safe cryptography refers to cryptographic algorithms designed to secure data against attacks from both classical and cryptographically relevant quantum computers, ensuring the long-term integrity and non-repudiation of digital assets.

Quantum-safe cryptography, also known as post-quantum cryptography (PQC) , encompasses cryptographic algorithms believed to be secure against cryptanalytic attacks by a large-scale quantum computer. Unlike current public-key systems such as RSA and ECC, which rely on the hardness of integer factorization and discrete logarithms—problems efficiently solvable by Shor's algorithm—PQC algorithms are built on mathematical problems thought to be intractable for both classical and quantum adversaries. These include lattice-based, hash-based, code-based, and multivariate polynomial cryptosystems, which are being standardized by NIST to replace vulnerable classical primitives.

For AI audit trail immutability, the transition to quantum-safe cryptography is critical to prevent 'harvest now, decrypt later' attacks, where encrypted logs are intercepted and stored until a cryptographically relevant quantum computer becomes available. Implementing hybrid schemes that combine classical and PQC algorithms provides defense-in-depth during migration. Key standards include CRYSTALS-Kyber for key encapsulation and CRYSTALS-Dilithium for digital signatures, ensuring that the non-repudiation tokens and hash chains securing AI decision logs remain verifiable over multi-decade compliance horizons.

POST-QUANTUM SECURITY

Key Features of Quantum-Safe Cryptography

Quantum-safe cryptography encompasses algorithmic techniques designed to secure digital signatures and key encapsulation against cryptographically relevant quantum computers, ensuring the long-term integrity of archived AI audit trails.

01

Lattice-Based Cryptography

Relies on the computational hardness of lattice problems like Learning With Errors (LWE) and Ring-LWE. These schemes construct trapdoor functions over high-dimensional algebraic lattices where finding the shortest vector or closest vector is intractable even for Shor's algorithm. CRYSTALS-Kyber (NIST-standardized for KEM) and CRYSTALS-Dilithium (for signatures) are prime examples, offering small key sizes and fast operations compared to other post-quantum families.

02

Hash-Based Signatures

Construct digital signatures solely from the security of cryptographic hash functions, making them well-understood and conservative choices. Stateful schemes like LMS and XMSS require tracking a one-time signature index to prevent key reuse, while stateless schemes like SPHINCS+ eliminate state management at the cost of larger signatures. NIST standardized both XMSS and LMS for firmware signing, and SPHINCS+ for general use.

03

Code-Based Cryptography

Builds on the difficulty of decoding a general linear code, a problem proven NP-complete. The McEliece cryptosystem uses a scrambled, permuted Goppa code as a public key, with the secret trapdoor enabling efficient decoding. Its primary advantage is long-standing confidence—unbroken since 1978—but its public keys are typically hundreds of kilobytes, limiting use to applications where key size is not a primary constraint.

04

Multivariate Cryptography

Based on the hardness of solving systems of multivariate quadratic equations over finite fields, an NP-hard problem. Signatures like Rainbow (a NIST finalist, later broken) and GeMSS use a hidden structure that allows the signer to invert a polynomial map efficiently. While fast and compact, many multivariate schemes have been cryptanalyzed, making parameter selection and conservative design critical for long-term security.

05

Isogeny-Based Cryptography

Uses the mathematical structure of elliptic curve isogenies—rational maps between elliptic curves. SIKE (Supersingular Isogeny Key Encapsulation) was a NIST finalist until a devastating key-recovery attack in 2022. The approach offers the smallest key sizes of any post-quantum family, but active research continues to establish confidence in the underlying hardness assumptions and defend against structural attacks.

06

Hybrid Cryptographic Schemes

Combine a classical algorithm (e.g., ECDH with Curve25519) and a post-quantum algorithm (e.g., Kyber-768) into a single key exchange or signature. The output is secure as long as at least one scheme remains unbroken. This provides a pragmatic migration path: organizations gain quantum resistance immediately while retaining classical fallback security, avoiding a hard cutover that could introduce implementation risk.

QUANTUM-SAFE CRYPTOGRAPHY

Frequently Asked Questions

Essential questions about cryptographic algorithms designed to resist attacks from cryptographically relevant quantum computers, ensuring the long-term integrity and non-repudiation of archived AI audit trails.

Quantum-safe cryptography, also known as post-quantum cryptography (PQC) , refers to cryptographic algorithms designed to be secure against an attack by a cryptographically relevant quantum computer. Unlike classical public-key cryptosystems such as RSA and Elliptic Curve Cryptography (ECC), which rely on the computational difficulty of integer factorization and discrete logarithm problems, quantum-safe algorithms are built on mathematical problems believed to be hard for both classical and quantum computers. These include lattice-based problems like Learning With Errors (LWE) , code-based problems, multivariate polynomial equations, hash-based signatures, and isogeny-based cryptography. The primary mechanism involves constructing trapdoor functions from these hard problems, enabling key encapsulation mechanisms (KEMs) and digital signature schemes that resist Shor's algorithm, which efficiently breaks RSA and ECC on a sufficiently powerful quantum computer.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.