Description The Poisonous Lattice v3.0 presents a complementary adaptive security architecture designed for post-breach protection in post-quantum environments. Unlike classical cryptographic systems that primarily aim to prevent unauthorized access, the Poisonous Lattice (PL) framework explores an intrusion-reactive approach in which adversarial access attempts trigger entropy-driven informational degradation mechanisms. The framework combines: density operator theory, von Neumann entropy dynamics, Lindblad-type open quantum system evolution, stochastic Lyapunov convergence analysis, and LWE-coupled adaptive noise injection to model the progressive collapse of extractable informational structure toward the maximum-entropy state. Version 3.0 introduces: a formally specified threat model, peer-review calibrated theorem language, expanded limitations and security assumptions, behavioral FPGA emulation analyses, AXI4-Lite hardware interface specifications, false-positive and latency modeling, and a multi-phase deployment roadmap extending from proof-of-concept simulation toward FPGA, ASIC, and standardization pathways. This work is not proposed as a replacement for standardized post-quantum cryptography. Instead, it is positioned as a complementary Layer-3 adaptive anti-extraction architecture intended to operate after adversarial boundary breach conditions have already occurred. The repository includes: the main peer-review edition paper, supplementary threat-model documentation, FPGA behavioral interface specifications, roadmap and standardization strategy documents, simulation source code, telemetry outputs, and behavioral RTL-oriented research artifacts. Research areas include: post-quantum security, adaptive cyber defense, anti-tamper architectures, open quantum systems, runtime information neutralization, hardware security, and entropy-reactive security systems.
Description The Poisonous Lattice v3.0 presents a complementary adaptive security architecture designed for post-breach protection in post-quantum environments. Unlike classical cryptographic systems that primarily aim to prevent unauthorized access, the Poisonous Lattice (PL) framework explores an intrusion-reactive approach in which adversarial access attempts trigger entropy-driven informational degradation mechanisms. The framework combines: density operator theory, von Neumann entropy dynamics, Lindblad-type open quantum system evolution, stochastic Lyapunov convergence analysis, and LWE-coupled adaptive noise injection to model the progressive collapse of extractable informational structure toward the maximum-entropy state. Version 3.0 introduces: a formally specified threat model, peer-review calibrated theorem language, expanded limitations and security assumptions, behavioral FPGA emulation analyses, AXI4-Lite hardware interface specifications, false-positive and latency modeling, and a multi-phase deployment roadmap extending from proof-of-concept simulation toward FPGA, ASIC, and standardization pathways. This work is not proposed as a replacement for standardized post-quantum cryptography. Instead, it is positioned as a complementary Layer-3 adaptive anti-extraction architecture intended to operate after adversarial boundary breach conditions have already occurred. The repository includes: the main peer-review edition paper, supplementary threat-model documentation, FPGA behavioral interface specifications, roadmap and standardization strategy documents, simulation source code, telemetry outputs, and behavioral RTL-oriented research artifacts. Research areas include: post-quantum security, adaptive cyber defense, anti-tamper architectures, open quantum systems, runtime information neutralization, hardware security, and entropy-reactive security systems.
The Poisonous Lattice Framework introduces an adaptive entropy-reactive security architecture in which adversarial access attempts trigger controlled informational collapse toward maximum-entropy states.Unlike classical cryptographic paradigms based solely on passive secrecy and computational hardness, the framework proposes active information neutralization: under intrusion conditions, the system dynamically degrades extractable informational structure through entropy injection and stochastic collapse dynamics.The framework combines:density operator theory,von Neumann entropy dynamics,Lindblad-type master equations,stochastic Lyapunov stability analysis,quantum information geometry,and adaptive post-quantum LWE-inspired degradation mechanisms.Theoretical results include:global asymptotic convergence toward the maximally mixed state,entropy monotonicity under adaptive collapse,stochastic stability guarantees,Holevo-bounded adversarial information extraction,and adaptive noise-coupled security degradation.This work is presented as a theoretical research framework and mathematical demonstrator for:adaptive cyber defense,anti-tamper architectures,intrusion-reactive information systems,post-quantum security concepts,and entropy-driven runtime protection mechanisms.The framework does not claim unconditional cryptographic security or production-ready implementation. Future work includes simulation validation, hardware-oriented architectures, runtime telemetry analysis, and experimental anti-extraction systems. �
This revised technical note presents the unified edition of the Poisonous Lattice research program, spanning versions v1.0–v8.0 and integrating three complementary hardware-security layers. Layer 1 introduces an entropy-reactive collapse mechanism designed to reduce the distinguishability of secret-correlated physical states following detected intrusion. It includes an unconditional Lyapunov convergence result, a conditional ensemble-distinguishability contraction proposition, and an explicitly unproved research hypothesis concerning statistical and computational indistinguishability under lattice-based assumptions. Layer 2 develops the Omega-PQC structural health-monitoring and ML-KEM operational-risk framework. It combines entropy-source degradation, side-channel exposure, protocol fallback, cryptographic bill-of-materials inconsistency, and key-lifecycle risk into normalized structural-trust indicators. The proposed QCAS v1.1 mappings are presented as model-estimated candidate alignment scores pending independent assessment and do not constitute a claim of certification or conformity. Layer 3 introduces the Dirac-Triggered Poisonous Lattice (DTPL), a normalized multi-physical anomaly-detection architecture based on Clifford-algebra operators. Power, electromagnetic, optical, thermal, quantum-state, and control-integrity channels are mapped into a composite operator score combining manifold distance, spectral deviation, eigenspace rotation, and dynamic drift. When validated thresholds are exceeded, the architecture initiates controlled information separation, isolated poisoning, secure erasure, and key reconfiguration. The revised edition incorporates pre-publication review corrections. The former Holevo-information claim has been reformulated as a conditional ensemble-distinguishability result; the computational-indistinguishability statement has been reclassified as a research hypothesis; the previous ML-KEM-768 “538-bit security” statement has been removed; Lyapunov time constants and strict-monotonicity assumptions have been corrected; dimensional channel normalization has been added to the DTPL operator; and the technology-readiness levels have been revised. Consolidated model-based simulations cover eleven scenarios using 100-run Monte Carlo analyses, bootstrap confidence intervals, and pre-attack false-trigger estimates. These results demonstrate internal model consistency under the stated assumptions but do not constitute physical implementation validation. The current estimated maturity is TRL 3 for Layers 1 and 2 and TRL 2–3 for Layer 3. A unified experimental roadmap is provided for FPGA synthesis, side-channel testing, entropy validation, multi-physical sensing, information-leakage measurement, and secure key-renewal experiments required for progression toward TRL 4 and TRL 5. The principal contribution of this work is a unified defensive architecture connecting physical-attack detection, post-quantum implementation assurance, structural trust monitoring, controlled information poisoning, domain separation, and secure reconfiguration within a single research framework.
Poisonous Lattice v7.0 introduces a QCAS-aligned dynamic structural assurance framework for post-quantum cryptographic (PQC) systems.While modern PQC standards focus on quantum-resistant algorithms and assurance frameworks validate deployment practices, long-term quantum security also requires continuous monitoring of operational degradation, implementation drift, and structural resilience.This work proposes the Ω-PQC Structural Health Monitor, a time-dependent assurance model designed to evaluate the evolving state of PQC infrastructures through:• entropy degradation monitoring• side-channel drift indicators• downgrade/fallback anomaly detection• key lifecycle risk assessment• Live-CBOM structural consistency trackingThe framework introduces:• Ω_PQC(t) structural health metric• D_PQC(t) degradation model• Quantum Risk Index (QRI)• Lyapunov-based recovery analysis• error-bounded decision regions• SAFE / WARNING / CRITICAL operational statesSimulation scenarios evaluate:• normal PQC operation• entropy poisoning• side-channel drift• downgrade attacks• recovery behaviorPoisonous Lattice v7.0 does not replace NIST PQC standards, cryptographic proofs, or QCAS-style assurance methodologies. Instead, it explores a complementary continuous structural monitoring layer for future quantum-safe infrastructures.The goal is to move from a static question:“Is the system quantum-safe today?”toward a dynamic question:“Does the quantum-safe system remain structurally healthy over time?”
The advent of quantum computing introduces fundamental challenges to contemporary cybersecurity, particularly by undermining the security assumptions of widely deployed cryptographic schemes. In parallel, the increasing sophistication, stealth, and adaptability of modern cyber threats expose the limitations of traditional, reactive security monitoring approaches. These developments motivate a shift toward defense strategies that are both quantum-resilient and intelligence-driven. This paper presents a comprehensive review of the convergence between post-quantum cryptography (PQC) and AI-driven threat hunting, focusing on the design and evolution of quantum-resilient defense frameworks. Rather than emphasizing empirical performance comparisons or speculative quantitative claims, the review adopts a concept-centric and analytically grounded perspective. It examines the foundational principles of post-quantum cryptography, the role of artificial intelligence in proactive threat hunting, and the emerging need to integrate cryptographic assurance with adaptive, learning-based security mechanisms. Existing architectural models, trust and risk abstractions, and formal security properties are analyzed to highlight how AI techniques can complement PQC by enabling continuous threat inference, contextual awareness, and adaptive response in post-quantum environments. The paper further synthesizes current research into a unified conceptual framework that captures the interaction between quantum-resistant cryptographic primitives and AI-based threat hunting processes. Key research gaps and open challenges are identified, including issues related to scalability, explainability, validation under future threat models, and the co-evolution of cryptographic and intelligent defense mechanisms. By consolidating fragmented research directions into a coherent analytical narrative, this review aims to serve as a foundational reference for future work on integrated, quantum-resilient cybersecurity architectures.
This ninth volume closes a critical gap in post-quantum cryptography (PQC) by deriving hybrid, thermodynamic-augmented security reductions for lattice-based architectures. The work shifts the definition of cryptographic resilience from model-relative computational assumptions (Tier-1) to a physically conserved resource strictly bounded by the irreversible laws of thermodynamics and fractal phase-space geometry (Tier-2). The proposed construction, Thermodynamic-LWE (T-LWE), mandates noise generation via physically irreducible Enclave-Oracle Physical Unclonable Functions (PUFs) and utilizes heavy-tailed Lévy/Cauchy distributions to enforce physical interaction limits. By integrating Landauer's principle for the cost of quantum Mamun, SM (2026) …………………………….1 Theoretical and Physical Boundaries of Lattice-Based Post-Quantum Cryptography: An Anatomical Critique of Thermodynamic Entropy Bounds Integrated into Security Reductions (Vol-IX) K S C state preparation and the Fannes-Audenaert inequality for von Neumann entropy continuity, the analysis proves that any quantum adversary attempting sophisticated extraction algorithms incurs a non-bypassable information-theoretic penalty. This penalty is exponentially amplified by the multifractal topology (Df) of the noise distribution. The resulting framework furnishes the global cryptographic community with deployable, entropy-augmented security proofs, anchoring quantum resilience to immutable physical laws. Also available on Academia.edu: https://www.academia.edu/attachments/132780724/download_file?s=portfolio
The rapid advancement of quantum computing threatens to undermine classical cryptographic primitives, creating an urgent need for post-quantum secure alternatives. Lattice-based Attribute-Based Encryption (ABE) has emerged as a promising direction, combining fine-grained access control with quantum resistance derived from lattice assumptions such as Learning With Errors (LWE) and Ring-LWE. This paper presents a systematic literature review of lattice-based ABE schemes published between 2022 and 2025, following the PRISMA methodology to ensure a rigorous and transparent study selection process. From an initial corpus of more than 7,800 studies retrieved across IEEE Xplore, SpringerLink, Elsevier ScienceDirect, MDPI, and Google Scholar, 1,236 studies were screened, resulting in 90 works selected for in-depth qualitative and quantitative synthesis. The review analyzes the evolution of lattice-based ABE in terms of mathematical foundations, security models, performance characteristics, and application domains. Particular emphasis is placed on emerging use cases in cloud computing, the Internet of Things (IoT), healthcare, financial systems, and government compliance, each evaluated against requirements such as revocation support, lightweight design, searchability, and multi-authority governance. Quantitative synthesis reveals uneven feature coverage across the literature: searchability is supported in 45.6% of schemes and lightweight constructions in 36.7%, whereas policy hiding (16.7%) and revocation (22.2%) remain comparatively underexplored. Performance trends indicate ciphertext sizes averaging 5.8 kB per attribute, with only 12% of schemes achieving compact representations below 2 kB. Moreover, fewer than 36% of surveyed constructions provide IND-CCA security, highlighting persistent challenges in achieving robustness against adaptive adversaries. By integrating structured research questions with quantitative trend analysis, this study offers both descriptive and evidence-backed insights into the current state of lattice-based ABE. The findings identify critical gaps in efficiency, security guarantees, and standardization, and inform a forward-looking research roadmap emphasizing lightweight revocation mechanisms, efficient policy hiding, stronger IND-CCA security models, and the need for standardized benchmarking frameworks. This survey thus serves as a comprehensive reference for researchers and practitioners working on post-quantum secure access control systems, particularly in privacy-sensitive domains such as healthcare.