QSymbolic Research

frank@qsymbolic.com

  • Digital Genesis: Why Safe Autonomy Requires Constraints, Not Freedom

    Rethinking adaptive control for safety-critical biological systems

    Autonomous systems are everywhere now—from vehicles to infrastructure to medical devices. Yet in domains where failure is irreversible, most autonomy techniques remain fundamentally unsafe. They learn, adapt, and optimize—but often without hard guarantees that adaptation won’t cross a line that cannot be uncrossed.

    In our recent paper, “Digital Genesis: Constraint-Certified Autonomous Control for Biohybrid Organ Systems,” we argue that this tension is not a bug in current approaches—it’s a consequence of how autonomy itself is framed .

    Digital GenesisDownload

    The central claim is simple but radical:

    True autonomy in safety-critical systems does not come from freedom of action, but from disciplined evolution within inviolable constraints.

    The problem with adaptive control today

    Classical adaptive control, model predictive control (MPC), and even learning-assisted controllers are excellent at reacting to error. They tune parameters, adjust gains, and optimize performance over time. But they share a common weakness: they do not persist as entities.

    Most adaptive controllers:

    • lack memory across long timescales,
    • do not reason about their own survival,
    • and rely on external supervision to recover from failure.

    In biological and biohybrid systems—such as synthetic organs—this is unacceptable. These systems operate continuously, are patient-specific, and tolerate no unsafe excursions. You cannot “reset” a failing liver.

    This is where Digital Genesis begins.

    From controllers to digital organisms

    Digital Genesis introduces a new abstraction: the constrained digital organism.

    A digital organism is not an AI agent. It has no goals of its own, no emergent intent, and no capacity to escape its design. Instead, it is a persistent control entity defined by structure:

    1. A digital genome
      A heritable, mutable control state composed of typed, bounded parameters.
    2. An immutable phenotype constraint envelope
      Absolute limits derived from physics, biology, and regulation. Unsafe behavior is not penalized—it is structurally unrepresentable.
    3. Bounded mutation
      Adaptation occurs through conservative, local parameter changes only.
    4. Predictive validation
      Every candidate adaptation is simulated against a patient- and device-specific model before it is allowed to act.
    5. Deterministic rollback (digital apoptosis)
      If real behavior deviates from validated predictions, the organism immediately reverts to a previously safe genome—irreversibly terminating the failed adaptation.

    Together, these components allow the system to evolve without ever escaping certified safety bounds .

    Why a synthetic liver?

    To demonstrate that this architecture is not just conceptual, the paper grounds Digital Genesis in a concrete, safety-critical application: a synthetic biohybrid liver.

    The liver is an ideal test bed:

    • It is continuously active.
    • Its dynamics are nonlinear and patient-specific.
    • Failure is systemic and irreversible.
    • Its safety limits are clinically well understood.

    In this setting, the digital organism does not control cells directly. The biology performs chemistry. The organism controls the environment: perfusion rates, oxygenation, nutrient levels, and timing.

    Fitness is defined not as task completion, but as homeostasis—balanced detoxification, metabolism, and synthetic function across competing objectives. Adaptation seeks stability, not maximization.

    Crucially, no mutation is ever applied to the physical system without passing predictive validation, and rollback is immediate when deviations occur .

    Autonomy through constraint

    A key insight of Digital Genesis is that constraints are not the enemy of autonomy—they are its enabler.

    By making the constraint envelope absolute and immutable:

    • Every reachable control state is implicitly pre-certified.
    • Safety is enforced by construction, not detection.
    • Rollback is a normal survival reflex, not an emergency measure.

    This reframes autonomy in a way that aligns with medical ethics and regulatory reality. Instead of attempting to certify every possible adaptive trajectory (an impossible task), regulators can certify:

    • the completeness of the constraint envelope,
    • the correctness of validation logic,
    • and the determinism of rollback mechanisms.

    Autonomy becomes trustworthy because it cannot escape control.

    Beyond organs: a general architecture

    While the paper focuses on a synthetic liver, the implications are broader.

    Any system that:

    • operates continuously,
    • faces partial observability,
    • and cannot tolerate unsafe exploration,

    can benefit from constrained digital organisms. Examples include:

    • implantable medical devices,
    • critical infrastructure control,
    • environmental life-support systems,
    • long-lived autonomous cyber-physical platforms.

    In all of these domains, the lesson is the same:

    Where failure cannot be undone, learning must be disciplined, not free.

    A different future for autonomy

    Digital Genesis does not compete with machine learning or reinforcement learning. It deliberately avoids open-ended optimization, black-box policies, and probabilistic safety claims.

    Instead, it offers a different path: evolution within an inviolable cage.

    By embedding safety into the structure of adaptation itself, constrained digital organisms allow systems to change, personalize, and stabilize over time—without ever crossing boundaries that matter.

    In safety-critical systems, that may be the only kind of autonomy worth having.

  • Introducing ENP-P™: Electrical Non-Persistence with Predicate — A CMOS Primitive for Single-Use Secrets

    Modern cryptography still relies on memory elements that persist—electrically stable nodes that remain readable long after software thinks a secret is gone. This architectural assumption underlies a vast ecosystem of attacks: speculative-execution leaks, DMA snooping, cold-boot remanence, fault injection, microarchitectural sampling, and more. Ephemeral secrets in post-quantum cryptography (PQC)—especially large decapsulation keys—are among the most vulnerable.

    My new preprint, A CMOS Electrical Non-Persistence Primitive for Single-Use Secrets, introduces a radically different model: Electrical Non-Persistence with Predicate, or ENP-P™. This is the circuit-level technology behind what I call “read-once memory” or ROOM—a primitive that enforces deterministic single-use semantics in hardware.

    Why ENP-P™ Exists

    A secret stored in SRAM or a flip-flop is electrically stable. Even after a “zeroization” write, it remains observable for part of a cycle, or through residual charge, speculative probing, debugging fabric, or bus reorderings. Software wrappers help but can’t eliminate the fundamental issue: the memory cell wants to persist.

    ENP-P™ starts from the opposite premise:

    The safest secret is one that is disclosed exactly once and then physically ceases to exist.

    ENP-P™ formalizes a simple but overlooked requirement:
    A read must be simultaneously a measurement and an irreversible collapse.

    This collapse is not a synchronous reset. It is a physical grounding event at the storage node—an immediate electrical transition that cannot be delayed, reordered, speculated, or replayed by any microarchitectural feature.

    What ENP-P™ Actually Does

    At the circuit level, ENP-P™ implements three rules:

    1. Predicate-gated visibility:
      The stored secret is masked internally (e.g., XOR’d per word with an 8-bit basis).
      Only if the caller supplies the correct basis in the same cycle as the measurement does the cell reveal the true 256-bit value.
    2. Deterministic, atomic collapse:
      A read triggers a forced electrical collapse—grounding the internal node and destroying all stored charge, independent of the system clock.
      After collapse, the cell is inert and cannot return a second valid output.
    3. No post-use electrical persistence:
      After collapse, no probe—software or physical—can extract the former value, because the former value no longer exists anywhere in RAM, buffers, or the cell’s transistors.

    This gives you two powerful security invariants:

    • Single-use secrecy: the system gets one chance to use a key, and never again.
    • No multi-use leakage window: attacks that rely on lingering electrical state are simply defeated, because the state is gone.

    How ENP-P™ Maps to the Paper

    The TechRxiv paper formalizes ENP-P™ as a measurement–collapse primitive. It shows:

    • A CMOS-compatible 256-bit read-once cell
    • Per-cycle basis-conditioned access (the predicate)
    • A grounding network implementing the collapse
    • Security implications for PQC ephemeral decapsulation secrets
    • Why synchronous reset is not atomic collapse
    • FPGA instantiations using LUT-based collapse approximations
    • How ENP-P™ closes attack surfaces defined in SP 1800-38

    The paper focuses especially on electrical non-persistence, demonstrating that preventing a secret from persisting even for a nanosecond longer than necessary removes entire microarchitectural side channels that existing “zeroization” methods cannot touch.

    Why This Matters for PQC

    Post-quantum KEM decapsulation requires large, ephemeral private values that often persist far longer than intended:

    • They remain in registers, BRAM, L1 caches
    • They may spill into shared buffers
    • They can be captured by DMA or debug fabric
    • They may leak under transient execution
    • They remain electrically in SRAM even after software overwrites them

    ENP-P™ eliminates these exposures by changing the underlying assumption:

    There is no opportunity to leak a secret after the read, because the secret no longer exists.

    This aligns with NIST SP 1800-38 and NSA’s guidance on ephemeral key protection during PQC migration.

    Comparison to “Zeroization” and Flip-Flop Resets

    Engineers often assume that tying a read-enable to a synchronous reset is equivalent. It isn’t:

    MethodCollapse TimingPersistence WindowVulnerable to Glitch / Speculation?
    Synchronous resetNext rising edgeOne full cycleYes
    Asynchronous resetNot clock-bound, but racesSub-cycle persistenceYes
    Software zeroizationMany cyclesMulti-cycleYes
    ENP-P™ collapseImmediate electrical eventNoneNo

    This is why ENP-P™ is a primitive, not a wrapper.

    Applications Beyond PQC

    • Secure-boot enclaves
    • HSMs and TEEs
    • Satellite and autonomous swarm systems
    • Forward-secure key rotation
    • Single-use authorization tokens
    • Anti-capture systems for field devices
    • Supply-chain / attestation architectures

    Anywhere the threat model assumes an attacker with physical, side-channel, or speculative capability, electrical non-persistence removes an attack surface instead of trying to patch it.

    Closing Thoughts

    ENP-P™ marks the beginning of a new class of memory semantics: the secret that is designed not to persist. This paper is the first to formalize and implement it at the CMOS level, demonstrate FPGA prototypes, and analyze its implications for PQC migration.

    If you want deterministic single-use secrecy with provable elimination of electrical persistence, ENP-P™ is the foundation.


  • Announcing: Atomic Memory™ (ROOM) — A CMOS Measurement–Collapse Primitive for Ephemeral Secrets

    I’m pleased to share a new preprint on TechRxiv introducing a hardware security primitive I’ve been developing: Atomic Memory™, also referred to as ROOM (Read-Once Memory).

    The core concept is a measurement–collapse behavior:

    The first authorized read returns the stored value and immediately triggers a deterministic collapse event, eliminating the possibility of subsequent reads.

    This provides a simple but powerful semantic:
    ephemeral secrets can only exist for one controlled, intentional use event.

    Why this matters

    Modern systems suffer from a broad set of early-read and multi-use leakage surfaces:

    • DMA/bus snooping
    • speculative execution
    • stale cache lines
    • cold boot & remanence
    • Rowhammer row-conflict reads
    • MMIO reordering & multi-core contention
    • zeroization race windows

    ROOM directly addresses these by eliminating the architectural assumption that memory must be read-many. Instead, the value is consumed in the same event that collapses it.

    What’s available today

    The repository includes:

    • an FPGA demonstration (1024-cell ROOM array on Intel Cyclone V)
    • same-cycle read-and-collapse semantics implemented in RTL
    • instrumented SignalTap captures
    • TCL scripts for automated evaluation
    • non-commercial evaluation license

    The FPGA version establishes functional semantics — the intended ASIC version moves the collapse into a local combinational transition tied directly to the read gate, eliminating global-clock dependency.

    Use Cases

    • PQC decapsulation keys
    • TLS 1.3 ephemeral secrets
    • secure boot chains
    • attestation tokens
    • one-shot provisioning events
    • malware-resistant ephemeral enclave design

    Links

    Feedback from the hardware security, applied cryptography, and semiconductors community is very welcome.

  • 🎉 Announcing the Atomic Memory™ Reference Repository

    We’re excited to announce the public release of the Atomic Memory™ reference repository:

    https://github.com/fcunnane/AtomicMemory

    This repository contains the full design, FPGA images, test scripts, and documentation for a 1024-cell read-once memory bank built entirely in standard CMOS logic.

    🔍 Why This Matters

    In modern security systems, especially with the increasing focus on post-quantum cryptography and ephemeral key-structures, one of the biggest risks is secrets that live too long: keys that remain in memory, can be replayed, cloned or extracted.

    Atomic Memory™ is designed from the ground up to address that: a memory primitive where each cell can be read exactly once (under correct conditions), and upon misuse or second read, it enters an irreversible collapse state producing entropy instead of the original value.

    Key features:

    • A deterministic read-once semantics: the first correct read returns the stored value; any non-compliant operation collapses the cell.
    • A purely digital implementation in standard CMOS — no exotic process steps, no analog logic.
    • Integrated entropy generation: once collapse happens, the cell transitions into TRNG/PRNG mode, giving obfuscated output instead of the original data.
    • A scalable bank (1024 cells) with shared entropy bus, memory-mapped access, and full test harness.

    📦 What You’ll Find in the Repo

    Here’s a quick overview of the contents of the repository:

    • fpga/collapse_cell.sv — The core cell logic implementing INIT, first-read, collapse semantics. 
    • fpga/collapse_bank.sv — A 1024-cell bank module that instantiates the collapse_cells, handles addressing, the entropy ring oscillator path. 
    • fpga/Atomic1024Bank.sof and fpga/SignalTap.sof — Precompiled FPGA images for Intel Cyclone V SoC (DE-SoC board) with and without instrumentation. 
    • tcl/ folder — TCL scripts (System Console) for automated testing: cell-init, random basis testing, collapse verification. 
    • LICENSE.md — Non-commercial research license. 
    • README.md — Full overview of the project, usage instructions, hardware target, and notes. 

    🛠 How to Get Started

    You can start experimenting today

    git clone https://github.com/fcunnane/AtomicMemory.git
    1. Clone the repo
    2. Load the Atomic1024Bank.sof onto your Intel Cyclone V board (5CSEBA6 / DE-SoC) via Quartus Programmer. 
    3. Run the included TCL scripts in System Console to initialize cells, perform first‐reads and verify collapse behavior.
    4. Inspect the collapse_cell.sv and collapse_bank.sv to understand the logic: how INIT, read pulses, basis validation, collapse state machines operate.
    5. Use the SignalTap.sof build if you want internal waveform visibility: capture collapse transitions, ring oscillator data, etc. 

    📈 What the Release Means

    By releasing this as an open reference implementation, the goal is to enable:

    • Academic review and validation of read-once memory primitives.
    • Hardware security engineers to prototype and integrate ephemeral key-handling into FPGAs or ASICs.
    • Researchers to explore collapse behavior, entropy evolution, side-channel risks, and integration with post-quantum stacks.
    • The wider community to extend the design: larger banks, alternative basis schemes, different interface options (AXI, Avalon-MM, etc.).

    🙋 Get Involved

    We’d love your feedback, ideas, and contributions. Here are ways you can get involved:

    • Open an issue on GitHub if you find bugs, documentation gaps, or want improvements.
    • Fork the repo and experiment: e.g., change cell count, add new interface, test other FPGAs or ASIC flows.
    • Share your results — whether it’s waveform captures, collapse timing measurements, entropy statistics, or integration with your system.
    • Cite the work in academic papers: The README includes citation instructions. 

    🎯 Final Thoughts

    Memory has often been the weak link in secure systems: keys sitting in RAM, secrets living longer than intended, persistent state creating risks. With Atomic Memory™, the paradigm shifts — secrets can now be forgotten by design.

    This release is the first step toward making that paradigm mainstream in hardware security.

    The repo is live now, ready to clone, compile, study, break, and build upon: https://github.com/fcunnane/AtomicMemory/

    Let’s see what you build.

  • 🧠 The ROOM Annealer: Deterministic Collapse Meets Optimization

    When most people hear “annealing,” they think of quantum or simulated annealing — algorithms that wander probabilistically through energy landscapes, slowly cooling toward a global minimum. But what if you could anneal deterministically, in hardware, in a single clock domain?

    That’s the concept behind the ROOM Annealer, a hardware optimization engine built on the same Read-Only-Once Memory (ROOM) primitive that powers our post-algebraic cryptography research at QSymbolic.

    ⚙️ Collapse as a Search Primitive

    At the core of ROOM is a simple but radical idea:

    A memory cell that delivers its true value only once, then collapses into entropy.

    Each collapse cycle yields an irreversible, randomized outcome that can be fed into logic networks or constraint fabrics. When scaled across thousands of cells, these correlated collapses behave like a hardware sampler exploring a high-dimensional energy surface.

    Instead of using thermal or quantum randomness, ROOM uses CMOS determinism — clocked collapse events that unfold according to metadata constraints (basis, phase, parity). This means the system can anneal, sample, or optimize while remaining fully synchronous and predictable in timing.

    🔁 From Entropy to Optimization

    The ROOM Annealer treats its collapse network as an Ising-like lattice, where each cell’s output influences its neighbors through parity constraints. During an anneal pass:

    1. Initialization: a seed entropy source pre-loads the collapse states.
    2. Collapse: each cell releases its one-time value, feeding neighbors.
    3. Update: correlation logic adjusts local states toward lower global energy.
    4. Re-arm: the bank resets with obfuscated entropy for the next sweep.

    Within a few cycles, the system converges toward minimal-energy configurations — solving problems like MAX-CUT, portfolio optimization, or constraint satisfaction.

    Because it’s digital, timing-deterministic, and CMOS-native, ROOM achieves the speed of logic with the dynamics of annealing.

    🧩 What Makes It Different

    ConceptQuantum AnnealingSimulated AnnealingROOM Annealing
    MediumSuperconducting qubitsSoftware RNGCMOS memory cells
    Noise SourceQuantum tunnelingThermal randomnessDeterministic collapse entropy
    ControlAnalog bias currentsTemperature scheduleClock-driven metadata gating
    SpeedMicrosecondsMilliseconds–secondsNanoseconds–microseconds
    PrecisionProbabilisticProbabilisticReproducible deterministic

    In practice, ROOM sits between classical and quantum hardware — a “post-algebraic” layer capable of symbolic superposition without coherence or decoherence problems.

    🔐 Why It Matters

    The same mechanics that make ROOM ideal for one-time keys and secure hardware entropy also make it an ultra-fast optimizer.

    • In cryptography, the annealer can resolve basis mismatches and phase states deterministically, mimicking QKD-style reconciliation in silicon.
    • In machine learning, the same logic can perform hardware Gibbs sampling or energy-based inference orders of magnitude faster than CPU/GPU software.
    • In operations research, ROOM’s one-cycle collapse enables real-time constraint solving on embedded systems where power and latency matter.

    🚀 Looking Ahead

    The next generation of ROOM prototypes (on our Cyclone-V FPGA testbed) will expose an Avalon interface for annealer control — allowing host CPUs to define energy terms, seeds, and collapse policies through simple registers.

    We see the ROOM Annealer as the missing bridge between digital determinism and physical randomness — a way to get the benefits of stochastic optimization without leaving the world of synchronous logic.

    QSymbolic is developing ROOM (Read-Only-Once Memory) as a foundation for post-algebraic cryptography, secure key generation, and hardware optimization. To learn more or discuss collaborations, contact frank@qsymbolic.com.

  • ROOM: Read Only-Once Memory (Verilog Reference Implementation)

    ROOM (Read-Only-Once Memory) is a post-algebraic, quantum-inspired cryptographic primitive developed by QSymbolic LLC.

    Modeled after a quantum measurement enforcing the no-cloning theorem, ROOM ensures that a stored value (e.g., a cryptographic key) can be read once only. On the first valid access, the value is released and the register collapses irreversibly within the same clock cycle. All subsequent reads return obfuscation (pseudorandom or noise-influenced replacement values).

    This repository provides the reference Verilog modules for ROOM as described in the Post-Algebraic Cryptography patent filings.

    https://github.com/fcunnane/QSymbolic

    ⸻

    ✨ Key Features • Read-once enforcement — secrets collapse on first qualified read. • Metadata gating — access requires matching basis, phase, tags, or timing. • Collapse latch — same-cycle disable after release. • Obfuscation source — pseudorandom or entropy-derived replacement values. • Peer-linked collapse — entangled cells propagate collapse for group rekeying. • Entropy harvesting — collapse jitter and metastability seed RNGs.

    ⸻

    📂 Contents • collapse_cell.v — core ROOM cell with collapse latch + obfuscation. • metadata_collapse_register.v — adds metadata predicates (basis, phase, tags). • collapse_register_entangled.v — peer-linked collapse across cells. • collapse_register_keyexchange.v — ephemeral key release with KDF. • qkd_collapse_register.v — BB84-style collapse emulation. • qkd_entangled_pair.v — entangled pair register (E91-style). • mdi_qkd_top.v — measurement-device-independent (MDI) protocol demo. • collapse_rng.v — collapse-derived entropy source. • testbench.v — simulation environment.

    ⸻

    🔒 Security Properties • Post-algebraic & post-quantum: independent of lattice/coding hardness assumptions. • Quantum-inspired: enforces a no-cloning principle at the hardware/software level. • QKD-like intrusion detectability: unauthorized reads collapse secrets into noise, measurable via error rates. • Low power, high efficiency: collapse + KDF cycle costs far less than lattice-based PQC or optical QKD. • Composable: works in FPGA, ASIC, SIM/secure elements, and software.

    ⸻

    🛰️ Applications • Mobile / 6G radios — ultra-low-latency ephemeral rekeying. • Satellites & swarms — low-power, high-efficiency key release; peer collapse for group rekey. • Cloud KMS / HSMs — tamper-resistant ephemeral API/tenant keys. • IoT & secure boot — one-time provisioning and firmware authentication. • ZKPs & homomorphic encryption — collapse-backed entropy for protocols.

    ⸻

    📜 License

    This project is licensed under the PolyForm Noncommercial License 1.0.0. • ✅ Free for personal, research, academic, and other noncommercial purposes. • 🚫 Not permitted for commercial use (products, services, paid offerings) without a license.

    For commercial licensing (semiconductors, telecom, satellite, defense, etc.), please contact: QSymbolic LLC — Francis X. Cunnane III 📧 frank@qsymbolic.com | 🌐 qsymbolic.com

    ⸻

    https://github.com/fcunnane/QSymbolic

    ⚠️ Disclaimer: This software is provided “as is”, without warranty of any kind, express or implied.

  • 🛠 ROOM Enclaves Adoption Pathway

    Stage 1 – FPGA / Prototype (Now)

    • Form: Verilog modules on FPGA (DE10 Nano, dev boards).
    • Goal: Prove collapse-on-read, entanglement, and metadata enforcement in hardware.
    • Value: Establish novelty + patent protection + demo viability.
    • Users: Researchers, DARPA testbeds, cryptography labs.

    Stage 2 – PCIe / External Accelerator (1–3 years)

    • Form: ROOM implemented on a PCIe card (like GPUs or HSMs).
    • Goal: Provide a drop-in “ROOM Engine” for servers. Keys collapse in hardware, but host only sees wrapped or ephemeral outputs.
    • Value: Market entry for enterprises → “Hardware unclonable key accelerator.”
    • Users: Banks, defense contractors, cloud hyperscalers (pilot programs).

    Stage 3 – SoC Security Co-Processor (3–6 years)

    • Form: ROOM integrated as a security block inside SoCs, like AES or SHA accelerators.
    • Goal: Embed ROOM into ARM/Intel/AMD chipsets as a companion primitive for secure enclaves.
    • Value: On-die collapse means no bus exposure; faster adoption in consumer devices (phones, laptops).
    • Users: Mobile security (Apple Secure Enclave, Google Titan), TPM replacements.

    Stage 4 – CPU Enclave Integration (6–10 years)

    • Form: ROOM primitives available as ISA extensions (e.g., ROOM_LOAD, ROOM_ENTANGLE).
    • Goal: Standardize ROOM as part of trusted execution environments (Intel SGX vNext, AMD SEV, ARM TrustZone+).
    • Value: Cloud-scale adoption → ephemeral keys for SaaS, finance, military workloads.
    • Users: Cloud providers, defense, healthcare, governments.

    Stage 5 – Ubiquity (10+ years)

    • Form: ROOM cells as standard CMOS memory primitive, like SRAM or DRAM cells.
    • Goal: Every chip has ROOM at transistor level. Collapse enforced everywhere.
    • Value: Universal “no-cloning on read” security baseline → hardware guarantees instead of software policies.
    • Users: Everyone — from smartphones to satellites.

    🚀 Strategic Takeaway

    ROOM moves up the adoption ladder:

    FPGA → PCIe card → SoC security core → CPU enclave → universal primitive.

    At the CPU-enclave stage, ROOM becomes the de facto hardware standard for unclonable key lifecycles — the logical endpoint for post-algebraic cryptography.

  • CMOS Keys™: The Future of Post-Algebraic Cryptography

    For decades, digital security has relied on algebraic hardness assumptions: factorization, discrete logarithms, and lattices. From RSA to elliptic curves to today’s post-quantum algorithms, the foundation has always been mathematical. But what if the next leap forward doesn’t come from math at all?

    What if security came from the hardware itself?

    Enter CMOS Keys™ — a new class of hardware primitives that collapse on read, enforce forward secrecy by design, and represent the first wave of Post-Algebraic Cryptography.

    Why Algebraic Security Isn’t Enough

    • Cloneable: Traditional keys are just numbers in memory. If an attacker reads them once, they can copy them forever.
    • Persistent: Keys stored in RAM, flash, or HSMs remain available until explicitly erased.
    • Algebra-dependent: Even “post-quantum” cryptography still assumes attackers are limited by certain math problems.

    These weaknesses all share a common trait: they treat keys as static data.

    The CMOS Keys Breakthrough

    CMOS Keys are not just data — they are circuits.

    A CMOS Key is instantiated inside silicon as a read-once memory cell. The moment it is accessed under the correct condition, it delivers its true value and then collapses into an obfuscated state, enforced at the transistor level.

    • 🔒 Read-Once: Keys can only be accessed a single time.
    • ⏳ Ephemeral: The act of use destroys the original.
    • 🛡 Unclonable: There is no static copy to extract or leak.
    • ⚡ Standard CMOS: Built entirely in existing semiconductor processes — no exotic hardware required.

    Post-Algebraic Cryptography

    We call this paradigm Post-Algebraic Cryptography because it steps outside the algebraic assumptions that have defined cryptography since the 1970s.

    Instead of securing secrets with mathematical difficulty, CMOS Keys secure them with physics and circuit behavior. A post-algebraic system does not care whether quantum computers succeed or fail, because its guarantees are not based on factoring, lattices, or any other algebraic structure.

    This is cryptography anchored in hardware collapse, not algebra.

    Applications of CMOS Keys

    • Forward Secrecy by Default: Every key collapses after first use, enforcing perfect forward secrecy without complex protocols.
    • Tamper-Resistant Hardware: CMOS Keys can’t be cloned, even with invasive attacks.
    • HSMs and TPMs: A new generation of security modules where keys are never persistent.
    • Cloud Security: Ephemeral keys that disappear after use, eliminating long-term exposure.
    • Military & Critical Infrastructure: Secure communication without relying on fragile algebraic hardness assumptions.

    Why Now?

    The world is racing to prepare for the post-quantum era, but most efforts still depend on unproven algebraic hardness. CMOS Keys are different: they are manufacturable in today’s silicon fabs, deployable in existing security architectures, and provably eliminate entire categories of attack by design.

    This isn’t just post-quantum.

    This is post-algebraic.

    Closing Vision

    “We’ve tried to protect secrets with math for 50 years. CMOS Keys protect them with physics. This is bigger than post-quantum — this is Post-Algebraic Cryptography.”

    The age of storable keys is ending. The age of CMOS Keys is beginning.