This paper evaluates quantum and AI-accelerated risks to TLS 1.3 cryptographic dependencies under an evidence-tiered model, distinguishing mechanism-backed threats (Shor algorithm against RSA and ECC) from contingency-backed risks to lattice-based post-quantum cryptography (PQC) and hypothesis-only risks to hash-based and symmetric primitives. We do not identify any known breaks of ML-KEM, ML-DSA, SLH-DSA, or AES-256. Instead, we use explicit scenario assumptions, organized as a four-scenario capability model with parameters and pseudocode for reproducibility, to stress-test migration timelines accompanied by parameter sensitivity analysis and explicit falsification analysis. The primary methodological contribution is a reproducible scenario-estimation instrument together with its explicit update mechanics: every parameter is a named, anchored quantity that can be varied and the model rerun; a stated protocol maps observed conformance to, or deviation from, the modeled curves onto revisions of specific parameters, so progressive refinements can be tested against accumulating historical data. The paper is a methodological companion to quantum resource-estimation studies and to expert-elicitation timeline surveys such as the Global Risk Institute quantum threat reports, with its revision rules stated explicitly. As of mid-2026, the model does not show any NIST-approved algorithms as broken. Instead, the vulnerability spectrum under different scenarios shows RSA risk crossing the 50% threshold between 2030-2032 and the PQC risk becoming a non-zero risk after 2032-2035 under contingency scenarios conditional on the unproven dimension-collapse. We urge PQC migration as mandatory per the 2030 and 2031 federal deadlines and by Mosca HNDL reasoning, and that crypto-agility and hybrid cryptographic deployment be considered necessary complements to any PQC migration efforts.
This paper evaluates quantum and AI-accelerated risks to TLS 1.3 cryptographic dependencies under an evidence-tiered model, distinguishing mechanism-backed threats (Shor algorithm against RSA and ECC) from contingency-backed risks to lattice-based post-quantum cryptography (PQC) and hypothesis-only risks to hash-based and symmetric primitives. We do not identify any known breaks of ML-KEM, ML-DSA, SLH-DSA, or AES-256. Instead, we use explicit scenario assumptions, organized as a four-scenario capability model with parameters and pseudocode for reproducibility, to stress-test migration timelines accompanied by parameter sensitivity analysis and explicit falsification analysis. The primary methodological contribution is a reproducible scenario-estimation instrument together with its explicit update mechanics: every parameter is a named, anchored quantity that can be varied and the model rerun; a stated protocol maps observed conformance to, or deviation from, the modeled curves onto revisions of specific parameters, so progressive refinements can be tested against accumulating historical data. The paper is a methodological companion to quantum resource-estimation studies and to expert-elicitation timeline surveys such as the Global Risk Institute quantum threat reports, with its revision rules stated explicitly. As of mid-2026, the model does not show any NIST-approved algorithms as broken. Instead, the vulnerability spectrum under different scenarios shows RSA risk crossing the 50% threshold between 2030-2032 and the PQC risk becoming a non-zero risk after 2032-2035 under contingency scenarios conditional on the unproven dimension-collapse. We urge PQC migration as mandatory per the 2030 and 2031 federal deadlines and by Mosca HNDL reasoning, and that crypto-agility and hybrid cryptographic deployment be considered necessary complements to any PQC migration efforts.
This review conducts an anatomical reading of Grover, Haile, Pedersen, Uner and Erickson (2026), A Scenario-Based Evaluation of CRQC+AI Vulnerability Spectrum for TLS 1.3 Cryptographic Dependencies. The source paper does not claim a known break of any NIST-standardised post-quantum primitive. Its distinctive contribution is an evidence-tiered, parameterised, and explicitly revisable estimation instrument that separates mechanism-backed risk (Shor against RSA and elliptic-curve schemes) from contingency-backed lattice risk (an unproven effective-dimension collapse parameter ρ) and hypothesis-only risk to hash-based and symmetric primitives. The present review reconstructs the three coupled instruments (engineering-channel model, capability model, cryptanalytic cost model), enumerates strengths and weaknesses, and situates the work against ten competing families of quantum-threat modelling: Mosca–Global Risk Institute expert elicitation; Gidney-class resource estimation; NIST IR 8547 policy calendars; NSA CNSA 2.0 mandates; vendor hardware roadmaps; core-SVP / BKZ lattice costing; NIST MAXDEPTH Grover accounting; Gershteyn–Alber Quantum Horizon Monte Carlo; single-point Q-Day / Y2Q countdowns; and Rose's-Law hardware envelopes. Ontologically, the paper shifts the object of forecasting from a unique Q-Day event to a graded spectrum of primitive-erosion states. Also available on Academia.edu: https://www.academia.edu/attachments/134024130/download_file?s=portfolio
Abstract—The advent of fault-tolerant Cryptanalytically Relevant Quantum Computers (CRQCs) presents an existential threat to modern information security. Shor's polynomial-time quantum algorithm renders widely deployed public-key cryptographic primitives—including RSA, Diffie-Hellman (DH), and Elliptic Curve Cryptography (ECDH/ECDSA)—completely vulnerable to private key derivation. Furthermore, 'Harvest Now, Decrypt Later' (HNDL) adversarial campaigns actively intercept and store encrypted enterprise telemetry today, anticipating future quantum decryption capabilities. In response, the National Institute of Standards and Technology (NIST) finalized its primary Post-Quantum Cryptography (PQC) standards in FIPS 203 (ML-KEM), FIPS 204 (ML-DSA), and FIPS 205 (SLH-DSA). However, transitioning complex enterprise IT ecosystems to quantum-resistant primitives introduces severe architectural and computational disruptions: public key and signature sizes increase by several orders of magnitude, cryptographic handshake latencies escalate, network packets experience Maximum Transmission Unit (MTU) fragmentation, and legacy Hardware Security Modules (HSMs) lack microarchitectural support for lattice-based polynomial arithmetic. This paper provides an exhaustive, mathematically grounded technical survey and architectural roadmap for enterprise PQC migration. We formalize the Module Learning with Errors (M-LWE) and Module Short Integer Solution (M-SIS) hardness foundations, evaluate hybrid classical/post-quantum cryptographic transition models across standard transport protocols (TLS 1.3, IKEv2/IPsec, SSH), and formulate an enterprise Crypto-Agility Maturity Model. Furthermore, we construct an empirical enterprise testbed measuring throughput, connection establishment latency, memory footprints, and packet fragmentation across legacy and quantum-resistant suites. Our results show that while ML-KEM-768 achieves microsecond-level encapsulation, its 1,088-byte ciphertext expands TLS ClientHello payloads into multiple TCP segments under constrained networks. Finally, we establish open research directions in post-quantum identity federations, stateful hash signature tracking, and hardware-accelerated polynomial arithmetic. Index Terms—Post-Quantum Cryptography (PQC), FIPS 203 (ML-KEM), FIPS 204 (ML-DSA), Crypto-Agility, TLS 1.3, Lattice-Based Cryptography, Harvest Now Decrypt Later, Hardware Security Modules (HSM), Enterprise Migration.
The arrival of cryptographically relevant quantum computers (CRQCs) represents an existential threat to the public-key cryptographic infrastructure underpinning global enterprise operations. Enterprise security today relies on RSA and elliptic-curve cryptography (ECC) for TLS, VPNs, PKI, code signing, and identity systems—all of which are fundamentally broken by Shor's algorithm on a sufficiently powerful quantum computer. The defining risk is time-shifted compromise: adversaries can harvest encrypted traffic today and decrypt it once CRQCs exist, a threat already underway according to U.S. intelligence assessments. NIST finalized three post-quantum cryptographic (PQC) standards in August 2024 (FIPS 203/204/205) and mandates deprecation of quantum-vulnerable algorithms by 2035. Yet only 5% of organizations have implemented quantum-safe encryption and 95% lack formal quantum transition plans. This paper provides a comprehensive, threat-driven analysis across seven dimensions: quantum algorithm impact, harvest-now-decrypt-later (HNDL) threat models, enterprise asset risks (PKI, TLS, VPNs, code signing, cloud, IoT, identity, blockchain, supply chain), sector-specific vulnerabilities (financial services, healthcare, critical infrastructure), cryptographic primitive analysis, migration standards and roadmaps, and enterprise readiness gaps. The convergence of HNDL attacks already underway, multi-decade data sensitivity windows, and 12–15 year enterprise migration timelines means the migration deadline has, for most sectors, already passed.
Abstract Cryptographically relevant quantum computers (CRQCs) would break widely deployed public-key cryptography (RSA/ECC) via Shor’s algorithm, enabling retroactive decryption of captured ciphertext (“harvest now, decrypt later”). This paper presents an enterprise-cloud transition framework that couples (i) standards-based algorithm selection using NIST’s post-quantum standards (FIPS 203–205), (ii) a cloud threat model that distinguishes retroactive confidentiality loss from forward integrity/authentication risks, and (iii) a quantitative timing-risk model grounded in Mosca’s inequality. Using a public expert-elicitation distribution for Q-day timing and a reproducible Monte Carlo estimator, we compare migration strategies and key planning parameters (migration start year, migration duration, and confidentiality lifetime). We also contrast this probabilistic view with common deterministic single-date Q-day planning, highlighting how tail uncertainty can materially change exposure estimates and recommended start years. For a representative enterprise case ( X=10 X = 10 years, Y=6 Y = 6 years), delaying the migration start from 2026 to 2030 increases the expected exposed fraction of the confidentiality window from 0.37 to 0.54 under a midline timeline. We also provide cloud-specific implementation guidance (crypto inventory, hybrid TLS/QUIC and service-mesh deployments, PKI readiness, and governance), and summarize performance and interoperability drivers arising from larger post-quantum key material.
Advancing quantum computing capabilities pose an existential threat to the public-key cryptographic infrastructure—RSA, elliptic curve cryptography (ECC), and Diffie-Hellman key exchange—that secures national security systems, critical infrastructure, and classified communications. National Security Memorandum 10 (NSM-10) mandates that federal agencies complete migration to post-quantum cryptography (PQC) by 2035, yet the feasibility of achieving this deadline remains empirically unquantified. This quantitative study assessed four interrelated dimensions of the post-quantum migration challenge for U.S. national security systems through analysis of six curated datasets: quantum hardware metrics (N = 46), PQC algorithm benchmarks (N = 24), National Vulnerability Database cryptographic vulnerabilities (N = 856), cryptographic library vulnerabilities (N = 39), federal agency migration data (N = 22), and PQC TLS network performance data (N = 19). Analytical methods included polynomial and logistic regression, Kruskal-Wallis tests, chi-square analysis, logistic regression, and Monte Carlo simulation (10,000 iterations). Results revealed four convergent findings. First, a cubic polynomial model (R² = .906) projected that a cryptographically relevant quantum computer (CRQC) could compromise RSA-2048 by approximately 2042, while a logistic saturation model (R² = .991) suggested a potential qubit plateau at approximately 1,237 qubits. Second, statistically significant performance differences existed across PQC algorithm families (p < .01), with ML-KEM demonstrating the fastest key generation (12–31 µs) and effect sizes up to η² = .893. Third, implementation vulnerabilities constituted 82.1% of cryptographic CVEs, with no significant association with severity (χ² = 4.216, p = .239). Fourth, the probability of all federal agencies completing migration by 2035 was 0.03% (median completion: 2041.2). These findings reveal a significant urgency-readiness gap between quantum threat emergence and federal migration capacity. Algorithm migration alone addresses less than 20% of the cryptographic vulnerability surface. Risk-based prioritization, phased compliance frameworks, and concurrent investment in implementation security are recommended to bridge the gap between the quantum threat timeline and organizational readiness.
The emergence of cryptographically relevant quantum computers (CRQCs) would compromise today’s dominant public-key primitives (RSA, DiffieHellman, ECDSA), threatening long-lived confidentiality, authentication, and integrity guarantees across AI pipelines and blockchain networks. This manuscript proposes a unified, quantum-resilient architecture that blends NISTstandardized post-quantum cryptography (PQC)—MLKEM for key establishment and ML-DSA or SLH-DSA for digital signatures—with defense-in-depth controls for AI model protection, data privacy, and blockchain protocol evolution. We first motivate the need for migration by outlining quantum attacks (Shor for factoring and discrete logarithms; Grover for quadratic search speedups) and summarize PQC standardization milestones and transition guidance. We then review the literature on lattice-based and hash-based cryptography, homomorphic encryption for privacy-preserving AI, and secure aggregation/differential privacy as complementary privacy technologies. Building on this foundation, we present a methodology for designing and evaluating quantum-resistant AI and blockchain systems, including key-lifecycle hardening, protocol-level hybrids, and crypto-agility. A simulated deployment (1,000 clients; 16 validator nodes; TLS 1.3 with ML-KEM and hybrid handshakes; blockchain transactions signed with ML-DSA and SLH-DSA) measures handshake and signing overheads, throughput, and model-training privacy-utility trade-offs. Results indicate that: (i) PQC-only handshakes add modest latency yet remain acceptable for online APIs; (ii) hybrid ECDHE+ML-KEM offers near-term defense against “store-now-decrypt-later,” with predictable cost; (iii) ML-DSA is practical for blockchain validation at common block sizes, while SLH-DSA suits firmware/codesigning and archival integrity; and (iv) combining PQC with secure aggregation and differentially private training preserves model utility with bounded overhead.