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Post-Quantum Security

Quantum-Secure AI:
Protected Today.
Resilient Tomorrow.

CipherSonic delivers AI infrastructure that is secure against both classical and quantum adversaries — running inference directly on encrypted data using fully homomorphic encryption built on lattice-based mathematics.

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The Threat

Why quantum computing changes everything for AI security

The encryption protecting most AI systems today — RSA, ECC, TLS — relies on mathematical problems that quantum computers can solve efficiently. A sufficiently powerful quantum computer running Shor's algorithm would render today's standard encryption obsolete overnight.

"Harvest Now, Decrypt Later"

Adversaries are already collecting encrypted AI traffic today, waiting to decrypt it once quantum computers mature. Data with long-term sensitivity — medical records, financial intelligence, state secrets — is at risk right now.

Classical Encryption Is Broken

RSA-2048 and ECC — the backbone of most enterprise security — offer zero resistance to a cryptographically relevant quantum computer. NIST has already begun mandating migration to post-quantum standards.

The Window Is Closing

Experts estimate cryptographically relevant quantum computers are 5–15 years away. Migrating AI infrastructure takes years. Organisations that start today will be protected; those that wait may find the window has closed.

The Solution

How CipherSonic delivers quantum-secure AI

Fully homomorphic encryption is built on lattice-based mathematics — the same foundation as NIST's post-quantum cryptographic standards. This means CipherSonic's AI pipeline is quantum-resistant by design, not by retrofit.

01
Quantum-Resistant Foundation

Lattice-based cryptography at the core

FHE schemes like CKKS and BFV — which CipherSonic uses — are constructed on the hardness of learning with errors (LWE) and ring-LWE problems. These lattice problems are believed to be computationally intractable for both classical and quantum computers, placing FHE squarely within the post-quantum cryptography family.

02
Zero Plaintext Exposure

AI inference on encrypted data — no decryption ever

CipherSonic runs the full AI inference pipeline on ciphertext. The model never sees your plaintext data. There is no decryption step to attack — quantum or otherwise. Even if an adversary harvested every byte of network traffic, they would have nothing useful.

03
NIST PQC Aligned

NIST PQC-aligned key encapsulation

Key exchange and session establishment in CipherSonic use mechanisms aligned with NIST's finalised post-quantum standards (CRYSTALS-Kyber / ML-KEM), ensuring that the handshake itself cannot be broken by Shor's algorithm — closing the last classical vulnerability.

04
GPU & FPGA Accelerated

Hardware-accelerated for real-world performance

Post-quantum and FHE operations are computationally intensive. CipherSonic's GPU and FPGA acceleration layers make quantum-secure AI inference practical — delivering near real-time results without sacrificing the cryptographic guarantees.

Classical AI security vs. quantum-secure AI

The difference isn't a feature — it's a fundamental architectural choice.

Classical AI Security
Data encrypted at rest and in transit only
Decrypted during AI inference — exposed in memory
RSA / ECC key exchange — broken by Shor's algorithm
Trust required in cloud provider and model operator
"Harvest now, decrypt later" attack is viable
Compliance by policy — not by cryptographic proof
CipherSonic Quantum-Secure AI
Data encrypted at rest, in transit, and during inference
AI runs directly on ciphertext — never decrypted
Lattice-based cryptography — quantum-resistant by design
Zero trust required — cryptographic guarantees instead
"Harvest now, decrypt later" yields nothing usable
Compliance by cryptographic proof — not policy
Industries

Who needs quantum-secure AI now

Any organisation whose data has value beyond a 5-year horizon needs to act before quantum computers arrive — not after.

💰

Financial Services

Transaction records with multi-decade retention
Fraud models trained on sensitive customer data
Regulatory compliance under DORA, GLBA, and PCI-DSS
Cross-institution data collaboration without exposure
🏥

Healthcare & Life Sciences

Patient records protected under HIPAA long-term
Clinical trial data shared across institutions
Genomic data — uniquely sensitive and permanent
AI diagnostics on encrypted medical imaging
🏛

Government & Defense

Intelligence with classification periods of decades
Critical infrastructure AI that cannot be compromised
Secure multi-party computation across agencies
NIST SP 800-208 and CNSA 2.0 alignment
⚖️

Legal & Compliance

Privileged communications and case strategy
AI-assisted document review on confidential files
Cross-border data residency with cryptographic proof
Audit trails that are tamper-evident and private
🏢

Enterprise AI

Proprietary model weights and training data
Internal copilots on HR, finance, and strategy data
Supply chain AI without exposing vendor intelligence
Third-party AI use with zero data exposure risk
🔬

Research & Academia

Multi-institution research on sensitive datasets
IP-sensitive AI models shared for peer review
Privacy-preserving federated learning
Compliance with IRB and data governance mandates
FAQ

Quantum-secure AI — common questions

What is quantum-secure AI?

Quantum-secure AI refers to AI systems that use cryptographic methods resistant to attacks from quantum computers. CipherSonic achieves this by combining fully homomorphic encryption (FHE) with post-quantum cryptographic primitives, ensuring that data processed by AI models remains protected both today and in the era of large-scale quantum computing.

Why does quantum computing threaten current AI security?

Most AI systems today rely on classical encryption (RSA, ECC) to protect data in transit and at rest. Quantum computers running Shor's algorithm can break these schemes in polynomial time. Because AI inference requires decrypting data before processing it, the window of exposure is wide open to a quantum attacker — or to an adversary who harvested encrypted data today to decrypt later.

How does CipherSonic make AI quantum-secure?

CipherSonic runs AI inference directly on encrypted data using fully homomorphic encryption. FHE is built on lattice-based mathematics — specifically the learning with errors (LWE) and ring-LWE problems — which are believed to be intractable for quantum computers. Since data is never decrypted, there is no ciphertext for a quantum attacker to break.

What is post-quantum cryptography (PQC)?

Post-quantum cryptography refers to cryptographic algorithms believed to be secure against quantum attacks. NIST finalised its first PQC standards in 2024: CRYSTALS-Kyber (now ML-KEM) for key encapsulation and CRYSTALS-Dilithium (now ML-DSA) for digital signatures — both based on lattice problems, the same mathematical foundation as CipherSonic's FHE engine.

What is the "harvest now, decrypt later" attack?

State-sponsored and sophisticated adversaries are already harvesting encrypted data today with the intent to decrypt it once quantum computers become powerful enough. Data that is sensitive for more than 5–10 years — medical records, financial history, government intelligence — is at risk right now, even if quantum computers don't yet exist at scale. CipherSonic prevents this because even harvested ciphertext yields nothing without breaking lattice-hard problems.

Do I need to wait for quantum computers to be a threat before acting?

No — and waiting is the wrong strategy. Migrating AI infrastructure to quantum-secure systems takes years. Regulatory bodies including NIST, CISA, and NSA have all recommended beginning the migration to post-quantum cryptography now. CipherSonic enables organisations to deploy quantum-secure AI today, on existing hardware, without waiting for the threat to materialise.

Start Today

Don't wait for the quantum threat.
Build quantum-secure AI now.

CipherSonic is production-ready today. Talk to our team about deploying quantum-secure AI for your organisation.

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