DSM: Decentralized State Machine - Solving the "Double Spend Problem" without the need for global consensus, unlocking a new paradigm

Cryptography
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TL;DR

The Decentralized State Machine (DSM) introduces a mathematically enforced trust layer for the internet that eliminates consensus mechanisms, third-party validators, and centralized infrastructure. DSM enables quantum-resistant, deterministic state transitions for digital identity and value exchange with immediate finality, offline capability, and tamper-proof forward-only state progression through bilateral state isolation and cryptographically verified state transitions.

DSM prevents double spending without global consensus through:

  • Forward-only hash chains: S_{n+1} = H(S_n \| R_{n+1})
  • Entropy evolution per state: e_{n+1} = H(e_n \| op_{n+1} \| (n+1))
  • Co-signed pre-commitments: C_{pre} = H(H(S_n) \| \text{"op"} \| e_{n+1})
  • Local balance enforcement: B_n = B_{n-1} + \Delta_n, with \sum \Delta_i \leq B_n
  • Bilateral state isolation: double spends are contained per relationship
  • Recovery and invalidation: S_{new} = H(I(S_k) \| R_{new})

These mechanisms guarantee that every state is unique, irreversible, and mathematically verifiable without requiring miners, validators, or a global ledger.

Background

The modern internet relies heavily on centralized trust systems controlled by corporations, governments, and intermediaries to manage authentication, identity, and value transfer. These models introduce fundamental vulnerabilities:

  • Third-Party Control: Governments and corporations serve as gatekeepers for access to identity systems and financial infrastructure
  • Security Risks: Centralized data stores and password-based systems remain vulnerable to breaches and fraud
  • Censorship & Exclusion: Institutions can arbitrarily revoke access to identity, funds, or services
  • Consensus Overhead: Blockchains require energy-intensive consensus mechanisms (e.g., mining, staking) to establish global transaction validity

Even Bitcoin, which introduced decentralized money, never fully achieved Satoshi’s vision of a purely peer-to-peer system due to:

  • Dependence on Miners: Transactions require validation through Proof-of-Work, creating bottlenecks
  • Global Consensus Requirement: A shared ledger that all nodes must agree upon limits scalability
  • Finality Delays: Multiple confirmations introduce waiting times that make microtransactions impractical
  • Limited Offline Capability: Transactions must be relayed through an online network

Second-layer solutions like Lightning Network introduce their own limitations:

  • Liquidity Constraints: Pre-funded channels limit transaction freedom
  • Routing Problems: Payments require successful routing paths between peers
  • Centralization Risks: Large hubs become dominant liquidity providers

Proposal

DSM represents a fundamental shift from approval-based to proof-based security models. Instead of requesting access and waiting for third-party approval, users present the next valid state, which is instantly verifiable using deterministic cryptography.

Core Verification Principle

Each new state stores a reference to the hash of its predecessor:

S_{n+1}.prev\_hash = H(S_n)

To validate a sequence of states from S_i to S_j, DSM confirms that each state properly references its predecessor:

Verify(S_i, S_j) = \bigwedge_{n=i+1}^{j} (S_n.prev\_hash = H(S_{n-1}))

Sparse Index for Efficient Lookups

DSM implements a sparse index to expedite lookups:

SI = \{S_0, S_k, S_{2k}, ..., S_{nk}\}

Where k is a checkpoint interval. To retrieve state S_m:

GetCheckpoint(m) = \max\{S_{ik} \mid ik < m\}

Then traverse forward:

Traverse(S_{ik}, m) = [S_{ik}, S_{ik+1}, ..., S_m]

Bilateral State Isolation

DSM isolates state evolution into bilateral relationships. Each entity E_i stores its own chain:

Chain_{E_i} = \{S^{E_i}_0, S^{E_i}_1, ..., S^{E_i}_n\}

For any pair of entities (E_i, E_j), their interactions produce relationship-specific state pairs:

Rel_{E_i,E_j} = \{(S^{E_i}_{m_1}, S^{E_j}_{p_1}), (S^{E_i}_{m_2}, S^{E_j}_{p_2}), ...\}

Deterministic Entropy Evolution

Let e_n denote the entropy seed for state S_n. The transition to S_{n+1} incorporates:

e_{n+1} = H(e_n \| op_{n+1} \| (n+1))

Where op_{n+1} represents the operation for the state transition.

Transaction Workflows

Bilateral (Offline) Transactions

  1. Entity A generates a cryptographic pre-commitment:
    C_{pre} = H(H(S_n) \| \text{"transfer 10 tokens to Entity B"} \| e_{n+1})

  2. Entity A and B establish physical proximity in a disconnected environment

  3. Entity A generates successor state S_{n+1} with transaction parameters

  4. Both entities co-sign the pre-commitment hash and finalize state S_{n+1}

  5. Finality is achieved immediately, with no need for network connectivity

Double Spend Protection (Offline):

  • Only one valid S_{n+1} can be derived from S_n
  • Alternate forks break e_{n+1} and are invalid
  • Unsigned or improperly signed successors are rejected
  • All transitions include balance deltas, constrained by:
    \sum \Delta_i \leq B_n, where B_n = B_{n-1} + \Delta_n

Unilateral (Online) Transactions

  1. Entity A retrieves and verifies Entity B’s genesis state
  2. A generates a successor S_{n+1} representing a token transfer
  3. A submits S_{n+1} to a decentralized directory
  4. B retrieves and verifies S_{n+1} later

Deterministic Smart Commitments

DSM uses hash-bound logic instead of scripts:

C_{commit} = H(S_n \| P)

Where P includes the commitment parameters:

  • Time-locked: C_{time} = H(S_n \| recipient \| amount \| \text{"after"} \| T)
  • Condition-based: C_{cond} = H(S_n \| recipient \| amount \| \text{"if"} \| condition \| O)
  • Recurring: C_{recur} = H(S_n \| recipient \| amount \| \text{"every"} \| period \| end\_date)

Deterministic Limbo Vault (DLV)

Defined as:

V = (L, C, H)

  • L: \Omega \rightarrow \{0,1\} — encoded lock logic
  • C = \{c_1, ..., c_n\} — cryptographic conditions
  • H: \{0,1\}^* \rightarrow \{0,1\}^\lambda — secure hash function

Unlocking key:

sk_V = H(L \| C \| \sigma)

Where \sigma is the proof of fulfillment.

Economic Model

DSM uses a subscription-based model:

R_{total} = R_{storage} + R_{treasury} + R_{ecosystem}

No per-transaction fees. This aligns with cloud billing or internet access rather than toll-based microeconomics.

Advantages

Mathematically Guaranteed Double Spend Prevention

DSM replaces trust-based mechanisms with provable math:

  • Forward-only states: S_{n+1}.prev\_hash = H(S_n)
  • Entropy enforcement: e_{n+1} = H(e_n \| op_{n+1} \| (n+1))
  • Balance constraint: \sum \Delta_i \leq B_n
  • Co-signing: no transaction finalizes without mutual signatures (offline)
  • Relationship isolation: double spends cannot propagate across relationships
  • Recovery: S_{new} = H(I(S_k) \| R_{new}) permanently invalidates compromised branches

Transcending the CAP Theorem

DSM avoids centralized tradeoffs:

  • Per-relationship state: G_{DSM} = \{R_{i,j} : i \neq j\}
  • Localized consistency:
    \forall (i,j) \neq (k,l), ConsistencyDomain(R_{i,j}) \cap ConsistencyDomain(R_{k,l}) = \emptyset
  • Atomic ops per relationship:
    Execute(op, R_{i,j}) \not\Rightarrow Affects(R_{k,l})

Thus:

C_{DSM}(S) \wedge A_{DSM}(S) \wedge P_{DSM}(S) = true

Offline Transactions

  • Instant finality
  • No routing, no liquidity constraints
  • Fully peer-to-peer
  • Works with Bluetooth, NFC, or QR

Privacy and Security

  • No global ledger
  • Post-quantum secure: SPHINCS+, Kyber, BLAKE3
  • Selective disclosure

Verification

V(H, S_n, S_{n+1}, \sigma_C) \rightarrow \{true, false\}

  • Data Availability:
    \forall s \in S, \forall t \in T, Accept(s,t) \Leftrightarrow Complete(Verification(s,t))
  • Computational Integrity:
    Pr[V(H, S_n, S'_{n+1}, \sigma_C) = true \mid S'_{n+1} \neq Compute(S_n, op)] \leq \varepsilon(\lambda)
  • Signature chain:
    Valid(S_i \rightarrow S_{i+1}) \Rightarrow \exists \sigma_i : Verify(pk_i, H(S_{i+1}), \sigma_i) = true

Performance Benchmarks

System TPS (Per Device) Latency Bytes Energy Offline
DSM (Desktop) 220k–250k 5 ms 64 1 J 10
DSM (Mobile) 150k–180k 5 ms 64 1 J 10
DSM (Raspberry Pi 4) 25k–30k 5 ms 64 1 J 10

Measured on single-threaded tests. Even with 40% degradation, DSM remains orders of magnitude faster than consensus-based systems.

Conclusion

DSM replaces consensus with cryptographic truth:

  • Identity = deterministic self-evolving hash state
  • Value = balance verified via state delta history
  • Authorization = signatures and entropy-bound transitions
  • Finality = math, not miner approval

This creates a new class of digital infrastructure — one where control, ownership, and security are enforced by math rather than trust. A decentralized, offline-capable, PQR, self-verifying internet is no longer theoretical — DSM makes it real.

For comprehensive details on the theoretical foundations, implementation architecture, and security proofs, please consult:

:bangbang:READ FULL PAPER BEFORE COMMENTING :point_down:

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If everything was built on top of DSM and all devices were to install it locally, we would have a fully quantum resistant as well as other attacks like phishing (Nothing to steal - no static keys) Internet tomorrow as well as offline payments with true finality. No need to keep dumping billions of dollars into a solution. Its already here.

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I didn’t follow how this avoids double spends for offline transactions. Can you explain that?

1 Like
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It’s well documented here:

I appreciate your inquiry. If you are still left with gaps in the logic after reading through the full paper, then feel free to reach out again, and I will be happy to acknowledge the gaps if there is any and fill them in here in that scenario, I would see that it would make sense to. It’s just that this could very quickly become a lot bigger bigger than a TL;DR in a hurry if I re-explain information that is available in the reference document.

Thank you

1 Like
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I just wonder where are you going to get users to get 100,000 TPS.

TPS is a meaningless number because you can run anything at any TPS if you have enough computational power. This is CS101

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So what, is solving the double spend problem without consensus 202? Keep your eye on the prize.

Let me clarify something that’s getting missed: DSM doesn’t have the same overhead as blockchains. There’s no global consensus, no mining, no staking, and no mempools. Synchronization isn’t continuous — it’s event-based and minimal. You literally pick up where you left off, per relationship.

Each connection between users maintains its own bilateral hash chain. That means:

  • If I transact with you, that’s our shared chain.
  • If I transact with someone else, it’s a completely separate chain.
  • There’s no bleedover. No waiting. No shared bottleneck.

So yes, the TPS benchmarks are accurate, because each relationship is self-contained and state transitions are locally verifiable. And that’s the whole point: removing consensus removes the bottleneck. It’s one of the most painful parts of blockchain architecture, and we removed it. Cleanly. Mathematically.

What’s frustrating is watching people dismiss this because they’re already invested in systems built on that pain. Ethics go out the window when profit enters the room, and too many people in this space are here for the exit, not the mission. That’s fine — stay there. But don’t come around later saying “I believed in this all along” after it works. We’ve seen that playbook before.

People bash the new thing. Then they ignore it. Then they say it won’t work. And finally, when it does, they claim they were there from the beginning. Not this time. This isn’t ideology. It’s math. And when math wins, there are no excuses left.

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Anyone reading this and then thinking how it might affect their bank accounts and that’s your first thought well forgive me if I’m not sad for you. Don’t worry it doesn’t mean the party is over. It just means you might need to shift your strategy a little, roll up your sleeves again, like you had to a few years back in the first place. Heaven forbid. Pretty naïve if you didn’t think it was it going to happen eventually that’s my opinion.

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I agree with @keyneom that this doesn’t sound like it solves the double spend problem. If Alice’s wallet is in two places at the same time, say US and China, and she simultaneously does a local transaction with counterparties Bob and David in US and China (respectively), there is no way to know at that instant (limited by speed of light) that there is nowhere else in the world that her wallet is actively trying to spend the same money.

This theoretical framework shows us that there must be some mechanism to come to global consensus on which of those two transactions are valid after they have both been signed, and it shows that it is impossible (because physics) to protect against double spends without some kind of global information coordination system.

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Her wallet cannot exist in two places simultaneously—it’s device-bound by design. That’s not what he said; you’re making a separate claim altogether, which is fine. However, please review the main paper thoroughly—ideally several times—before commenting further. These concepts are novel and require careful consideration. Everything you’re questioning has already been documented clearly, so I kindly ask that you take the necessary time to read and fully grasp the material before responding. You seem to do this on all my posts and I’m kind of exasperated by it, so I’m just going to have to ignore your comments from now on.

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There are way too many garbage papers out there to read 119 pages digging for an answer, especially when your summaries in various places seem to just ignore the real problem entirely.

You cannot prevent data from being copied, though you can try to reduce the risk of it with trusted execution environments (which have been broken repeatedly in history). Perhaps with non-copyable, single use, quantum keys you could achieve such a thing, but that is purely theoretical at this point. If you are just suggesting the use of TEEs, then I recommend stating that clearly in the various summaries you have provided, because if you accept TEEs as secure then a lot of problems get much easier.

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READ! My god man. Take a hint. I’m trying to be polite here but come on. Then just stay away from my work please. You’re the only one who does this so… I’m not here to cater to you. Do you understand that?

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To everyone else here:

I genuinely welcome comments and questions—that’s why I’m sharing this. I enjoy meaningful discussion and debate, especially on topics as novel as this. But for that to happen, the conversation needs to be informed. That starts with reading the summary, and ideally, the full paper.

What’s missing from this summary are critical pieces—like how the ID is generated, how each ID’s Genesis state is formed, the concept of Genesis IDs, and several other mechanisms that make the system work. Including all of that would turn this into the full paper, not a summary.

If I had more time, maybe I could strike a better balance between brevity and depth. But the truth is: this system doesn’t build directly on existing frameworks. Components like limbo vaults are entirely new, which makes them hard to explain in a few lines. The fact that it’s not even account based your balance gets baked right into your state, which is your ID as well for authentication that continuously evolves. keys are ephemeral one time use is another one. No static keys as your balance is based into the state, like I just mentioned. The list goes on. They’re not just tweaks on what’s already out there—they’re original. So if you’re genuinely curious, I really do encourage you to read the full paper. That’s where all of this comes together.

Otherwise, I end up reposting the entire thing bit by bit here, which defeats the point of having a summary in the first place. That’s why there’s a link—so anyone interested can explore further.

Once you’ve gone through it, I’d love to hear your thoughts. That’s the whole reason this is being shared—to open the door for real questions, real feedback, and real collaboration. But if you haven’t read it and you start asking questions that are clearly answered in the paper, it slows everything down and derails what could be a really valuable exchange.

Where I’m from, it’s just kind of expected—you wouldn’t comment on a book you haven’t read, let alone challenge its thesis based on the back cover. Same idea here.

Bottom line: if you’re interested, dive into the material. If something doesn’t make sense or doesn’t seem to hold up—then bring it up. That’s the kind of dialogue that helps everyone learn, including me. I want to walk away from this having learned something too. Thanks.

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There is a Dev Docs that’s more high-level and directly related to the SDK and also how to change your way of thinking which the paper doesn’t go into and I think is quite helpful.

There’s a Pokémon trading example in the repo too: Pokemon Trade Example on DSM

Core is fully implemented and well tested. Right now I’m just finishing up the decentralized storage nodes.

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DRAM-Based Dual-Binding Random Walk (DBRW)

A Technical Summary

Problem Solved:

Modern apps can be “cloned” simply by copying their files or VM/container images, bypassing software-only or enclave-only checks.
DBRW’s solution:
By tying together a device’s unique DRAM timing fingerprint and its specific execution environment, DBRW ensures the app only runs where it was originally installed.

How It Works:

  1. Random Walk Memory Interrogation

    • Generate a forward-only hash chain of length k.
    • At each step, use the chain to select a pseudorandom DRAM address and record its read timing.
    • These timing variations form a hardware fingerprint that’s infeasible to predict on another device.

  2. Environment Fingerprinting

    • Collect j contextual values—installation path, inode numbers, namespace/container IDs—that are unique to this VM or container instance.

  3. Dual-Binding

    • Combine the DRAM fingerprint and the environment data into one hash:
      H_{\text{bind}} = H\bigl(\mathrm{WalkHash}\,\|\,\mathrm{EnvParams}\bigr)
    • Neither component can be validated without the other.

  4. Forward-Only Hash Chain

    • Every step feeds into the next in a one-way chain, preventing any rollback or replay of earlier states.

Key Theorems:

Cross-Device Security:

P[\text{success}] \;\le\; 2^{-\alpha \cdot k}\;+\;\mathrm{negl}(\lambda)

where

  • \alpha = entropy per DRAM measurement
  • k = walk length
  • \lambda = security parameter

Same-Device Partition Security:

P[\text{success}] \;\le\; 2^{-\beta \cdot j}\;+\;\mathrm{negl}(\lambda)

where

  • \beta = entropy per environment parameter
  • j = number of environment parameters

Proof Insights:

  • Cross-Device: An attacker must either guess all k DRAM timings (probability 2^{-\alpha \cdot k}) or break the hash chain (negligible).
  • Same-Device Partition: DRAM patterns carry over, so success hinges on matching all j environment attributes (probability 2^{-\beta \cdot j}) or finding a hash collision.

Critical Performance Metrics:

  • False acceptance rate: 2.1 \times 10^{-11} (cross-device), 5.7 \times 10^{-10} (same-device)
  • Verification time: 25 – 45 ms (imperceptible to users)
  • Network: Fully offline—no connectivity required
  • Robustness: Accurate across 0–70 °C and ±10 % CPU load
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Drop-In Cloning Protection for Any System Technical Paper: Dual-Binding Random Walk (DBRW)

FULL PAPER :memo::point_up_2:

DBRW is a portable, cryptographic anti-cloning protocol that prevents both same-device (container-based) and cross-device (hardware-based) cloning attacks. It securely binds applications to their physical hardware and execution context without requiring any secure enclave or online validation. Simple to integrate into any app, blockchain, or runtime — DBRW is a drop-in defense layer for tamper resistance, state continuity, and rollback prevention across all platforms.

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There should be a way to shrink the paper :slight_smile: Einstein’s paper on the photoelectric effect was just one page, and he won a Nobel Prize for it. Every additional page exponentially decreases the number of people who will read the paper :slight_smile:

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thats why its easier to just show them and they try it for themselves :wink:. thanks so much for your insights!