AI Automotive Cybersecurity Specialist vs AI Quantum-Safe Security Specialist

B AI Quantum-Safe Security Specialist Only

• Post-quantum cryptography: ML-KEM (Kyber), ML-DSA (Dilithium), SLH-DSA (SPHINCS+), and hybrid schemes
• Classical cryptographic foundations: RSA, ECC, AES, TLS, PKI, digital signatures
• AI/ML security: adversarial robustness, model poisoning, data poisoning, federated learning privacy
• Quantum threat modeling: Harvest-Now-Decrypt-Later (HNDL) risk assessment, cryptographic agility planning
• Secure AI pipeline design: encrypted inference, homomorphic encryption for ML, secure multi-party computation
• Cryptographic key management and rotation in distributed AI systems
• Formal verification and security proofs for cryptographic protocols
• NIST PQC standards and migration frameworks (SP 800-208, CNSA 2.0)