HIOF•IfC (It from Consciousness) SeriesA Holographic Information-Ontological Framework for Consciousness, Form, and Cosmic Transaction The HIOF•IfC series develops a unified holographic information-ontological framework in which consciousness is not an emergent epiphenomenon but a fundamental structuring principle of reality. Building on the t = ∞ Time Ocean Model (TOM) and the Holographic Information Ontological Framework (HIOF), the series proposes a distributed, non-centralized ontology of information inscription in which low-entropy structures emerge through the autonomous phase-matching of information networks. Core InnovationRather than introducing ad-hoc adjustments to the ΛCDM model to address the JWST tension regarding early mature galaxies at z ∼ 7–13, HIOF•IfC introduces Identitior autonomy and a new dynamical agent — consciousness gravity (Gc = Ψc ⋅ Rs ⋅ ϕr) — as an active driver of structure formation. Through distributed information networks and phase matching, the framework accounts for accelerated early structure growth as a natural consequence of informational coherence. A distinctive feature of the series is its structural symmetry between ontology and methodology. If the fundamental ontology is a decentralized network of information inscription, then the corresponding methodology must likewise be distributed and correlation-based. This symmetry is realized in the Spiderweb Theory, which proposes cross-correlation techniques over single-point sensitivity, thereby closing the epistemic loop between theory and observation. Through the De-centered Observer Principle, human consciousness is repositioned as one particular mode of information inscription within a vast, decentralized network of nodes. This move dissolves the long-standing quantum measurement problem regarding the definition of the “observer” while elevating meaning from subjective psychology to an objective physical process: the resistance to thermodynamic entropy through low-entropy inscription. The series thus offers a philosophically rigorous and observationally relevant alternative to both standard physical cosmology and conventional consciousness studies, grounded in the interplay between information, identity, and gravitational dynamics. Keywords It from Consciousness; Holographic Information Ontology; Consciousness Continuum; Distributed Consciousness; Identitior; Consciousness Gravity; Low-Entropy Inscription; Causal Ledger; Manifestation Interface; Sovereign Interrupt; Information Transaction; Co-dancing; Philosophy of Physics; Foundations of Cosmology; JWST Tension Author Wai-Hung Tam (Pan)Independent ResearcherORCID: 0009-0002-7789-8464Email: panxtam@protonmail.com
The VR cycle built an operational mathematics — arithmetic, numbers,sets, forms, topology, a continuum on Brouwer's path — and onlyafterwards wrote out the logic it had been standing on: ZTL, Zero-TrustLogic (concept DOI 10.5281/zenodo.21318981). This preprint carries outthe programme "raise VR onto ZTL" and verifies, rather than declares,the thesis that VR always stood on ZTL. Three steps, every claim eitherMEASURED (machine enumeration, reproducible by the ZTL repository'stest stands) or kernel-checked in Lean 4 with the axiom footprintprinted per object. (a) Witnessed identity is a ZTL atom discipline: verdicts are packagedwith their certificates; the alive inference rules are witnessconstructors; identity on finite operational sets and on the vonNeumann register is totally earnable; groundedness of a set isorthogonal to earnability of its identity; a fully earned register isclassical. The entire verdict layer sits on the empty axiom list. Step(a) also returned a correction to ZTL itself: the verdict-warranty is atwo-grade ladder (sound — never lies; hereditary — never revoked),published same-day as ZTL v1.1 (DOI 10.5281/zenodo.21323552). (b) Choice sequences are the lazy register: the lawless stage court ofa growing sequence coincides with ZTL's global supervaluation totally(a law is knowledge: it narrows the worlds); Kripke persistence isnative to the lazy register; warranted greedy verdicts are exactly theBrouwer-assertable ones; the fallen law of identity p→p is redeemed bythe stage court — a law of logic, not of data. (c) The survival ledger: a proof survives the move onto ZTL iff itstands below the classical floor. The cycle's four-tier axiom ledgerwas therefore the ZTL-survival audit all along; sweeping 405live-audited objects plus flagship anchors shows that everything VRcalls operational moves, and what stays is exactly what the cycle hadalready flagged as classical by design, by substrate, or by borrowedplumbing. No operational theorem died in the move. The preprint also measures the delta against intuitionism: ZTL and IPCare incomparable as law-sets (p→p falls in ZTL, Jankov's weak excludedmiddle holds), agree 14/14 on premised classical rules, and part wayson every structural signature (finite matrix, disjunction property,double negation, the status of an unproved sentence). A thirdfoundations posture, not a relabelling of the second. AI disclosure: prepared with the assistance of Claude (Anthropic),Variant A architecture (human curator directing the model as architectand implementer); all mathematical content and decisions are due to thehuman author. This work was developed with Claude Fable 5. Reliabilitydoes not depend on trusting the AI: every claim is reproducible by therepositories' regressions and the Lean 4 kernel.
This article analyses the impact of smart contracts on family law, specifically examining how these digital contracts can simplify and improve the drafting, implementation and enforcement of family agreements. The analysis examines the advantages, examples of application, challenges and limitations of smart contracts in family law, explains their ability to enhance efficiency and transparency in relevant cases, and considers ethical aspects and potential risks. The article notes that most legal systems have not yet adapted to blockchain technology. The legal validity of smart contracts, particularly in the context of personal relationships, is the subject of lively debate in practice. Family law is complex and often requires human judgement, which smart contracts currently lack. Family law varies significantly across different jurisdictions, making it difficult to create a universally recognised marriage contract on the blockchain. Both parties to the marriage contract must understand the functionality of smart contracts, including potential risks such as coding errors. Despite the transparency, storing highly sensitive data on a public blockchain may raise privacy concerns for some couples. Ultimately, smart contracts have the potential to transform family law by offering families a more efficient and secure way to manage legal transactions in today’s world. The transparent nature of blockchain records poses risks to the confidentiality of spouses’ property and financial information. The immutable characteristics of smart contracts hinder their adaptability to changing circumstances, such as the birth of children or fluctuations in income, whilst judicial oversight of their enforcement is largely absent. From a pragmatic point of view, smart contracts can be effectively used in various aspects of regulating property relations within marriage. A marriage contract utilising a smart contract can clearly define the procedure for the distribution of digital assets – in particular cryptocurrencies, non-fungible tokens or tokenised real estate – in the event of divorce, ensuring the automatic execution of this distribution following the legally recognised event of divorce, thereby eliminating protracted legal disputes over these assets. Furthermore, a smart contract can be integrated with the couple’s joint digital wallet, ensuring the automatic deduction of a set share from each partner’s income and the subsequent automatic payment of joint obligations – such as rent, utility bills, etc. – thereby minimising the risk of conflicts regarding the management of joint finances. Smart contracts currently function most effectively in the field of decentralised finance and digital assets, serving as a complement to traditional legal instruments rather than a complete replacement for them.
This article analyses the impact of smart contracts on family law, specifically examining how these digital contracts can simplify and improve the drafting, implementation and enforcement of family agreements. The analysis examines the advantages, examples of application, challenges and limitations of smart contracts in family law, explains their ability to enhance efficiency and transparency in relevant cases, and considers ethical aspects and potential risks. The article notes that most legal systems have not yet adapted to blockchain technology. The legal validity of smart contracts, particularly in the context of personal relationships, is the subject of lively debate in practice. Family law is complex and often requires human judgement, which smart contracts currently lack. Family law varies significantly across different jurisdictions, making it difficult to create a universally recognised marriage contract on the blockchain. Both parties to the marriage contract must understand the functionality of smart contracts, including potential risks such as coding errors. Despite the transparency, storing highly sensitive data on a public blockchain may raise privacy concerns for some couples. Ultimately, smart contracts have the potential to transform family law by offering families a more efficient and secure way to manage legal transactions in today’s world. The transparent nature of blockchain records poses risks to the confidentiality of spouses’ property and financial information. The immutable characteristics of smart contracts hinder their adaptability to changing circumstances, such as the birth of children or fluctuations in income, whilst judicial oversight of their enforcement is largely absent. From a pragmatic point of view, smart contracts can be effectively used in various aspects of regulating property relations within marriage. A marriage contract utilising a smart contract can clearly define the procedure for the distribution of digital assets – in particular cryptocurrencies, non-fungible tokens or tokenised real estate – in the event of divorce, ensuring the automatic execution of this distribution following the legally recognised event of divorce, thereby eliminating protracted legal disputes over these assets. Furthermore, a smart contract can be integrated with the couple’s joint digital wallet, ensuring the automatic deduction of a set share from each partner’s income and the subsequent automatic payment of joint obligations – such as rent, utility bills, etc. – thereby minimising the risk of conflicts regarding the management of joint finances. Smart contracts currently function most effectively in the field of decentralised finance and digital assets, serving as a complement to traditional legal instruments rather than a complete replacement for them.
Crypto's dominant narrative—tokenizing treasuries, equities, and lending products—cedes value to incumbents who will treat any blockchain as a replaceable backend. The real opportunity is alternative markets: economic coordination problems that Wall Street structurally cannot or will not solve. We catalog 50 alternative markets across six categories, identify the ~20 that are genuinely blockchain-necessary, and estimate $200B–$1T in new annual GDP (0.2–1.0% of global output). We then argue that Ethereum will not pursue these markets—its ecosystem is structurally captured by the tokenization narrative, as evidenced by the shutdown of pioneering projects like Goldfinch and a broader exodus of builders from the ecosystem. We propose that a purpose-built, privacy-native blockchain is the correct vehicle, and lay out the architecture, cold-start sequencing, and talent recruitment strategy to build it.
Distributed systems can verify whether a transaction or state transition is valid, yet they often cannot establish whether the underlying action was authorized under a meaningful, current, and context-specific expression of consent. This limitation becomes increasingly significant as autonomous software agents, artificial intelligence systems, decentralized applications, and connected devices act across organizational and technical boundaries. This article presents a nonproprietary framework for verifiable consent in distributed systems through AI-assisted identity governance and recursive zero-knowledge proofs. The framework represents consent as a structured, machine-verifiable authorization object containing the consenting subject, requesting actor, permitted action, contextual constraints, validity period, policy version, and revocation state. A bounded AI-governance layer evaluates requests against explicit policies and contextual evidence while remaining subordinate to deterministic rules, human-defined constraints, and auditable decision procedures. Approved authorization statements are transformed into privacy-preserving cryptographic proofs, allowing a verifier to confirm that relevant consent and policy conditions were satisfied without requiring disclosure of the underlying identity attributes, private data, or complete policy record. To support high-volume environments, individual proofs may be recursively composed into succinct aggregate proofs. This construction separates expensive proof generation from efficient downstream verification and provides a basis for scalable authorization auditing across distributed infrastructure. The article defines the system model, consent lifecycle, trust assumptions, proof relationships, revocation requirements, and principal security properties, including authorization soundness, privacy preservation, replay resistance, policy-version integrity, and revocation safety. It also analyzes the architectural tradeoffs associated with AI reasoning, cryptographic proving costs, governance design, key management, and interoperability. The proposed framework does not disclose implementation-specific circuits, source code, model configurations, deployment topology, or proprietary protocol parameters. Instead, it establishes a general research foundation for treating consent as a verifiable computational primitive. Potential applications include decentralized identity, autonomous agents, regulated data exchange, financial services, healthcare information systems, Internet of Things networks, and cross-platform digital authorization.
This study examines the regulation of blockchain technology and cryptocurrencies in Morocco’s foreign exchange market, focusing on the challenges posed by restrictive regulatory frameworks and their implications for financial stability. Although cryptocurrency transactions have been officially prohibited since 2017, their use has continued to expand through informal and peer-to-peer channels, raising concerns about the effectiveness of prohibition-based regulation. Using a systematic literature review based on the PRISMA framework, this study analyzes academic publications, institutional reports, and international regulatory developments covering the period 2018–2026. The findings reveal a persistent mismatch between formal regulation and actual market practices, resulting in regulatory arbitrage, weak enforcement, and the expansion of informal cryptocurrency activities. The analysis further highlights significant macro-financial risks, including capital flight, exchange rate pressures, and reduced monetary policy effectiveness. By explicitly linking cryptocurrency regulation to foreign exchange market dynamics in an emerging economy, the study addresses an underexplored area in the literature. It concludes that Morocco’s current restrictive approach is unlikely to remain effective and argues for the adoption of a more adaptive, risk-based regulatory framework capable of promoting financial innovation while preserving macroeconomic stability and regulatory oversight.
Sepehr Noroozi Chakoli, Seyed Ali Etrati, Seyed Mohammad Etrati, Hamid Haj Seyyed Javadi
Large Language Models (LLMs) are now embedded in security and privacy critical applications, yet they remain vulnerable to attacks that span their entire data life cycle. This survey provides a comprehensive, cryptography-aware review of these risks across three phases—training, inference, and deployment; while explicitly connecting them to classical security goals and primitives. We introduce a simple stage-wise risk scoring model inspired by NIST risk assessment that propagates vulnerabilities across the life cycle, and we instantiate it with a numeric example linking training time poisoning to inference time data extraction. We further propose a life cycle aligned evaluation framework that maps modern benchmarks (e.g., HarmBench, JailbreakBench, TrustLLM, DecodingTrust) to concrete threat classes and reports representative quantitative results, such as attack success rates under different defenses. Finally, we analyze the practicality of advanced defenses—including differential privacy, fully homomorphic encryption, secure multi-party computation, and zero knowledge proofs—in light of their computational overhead and deployment constraints, building on foundational cryptography and privacy works. Our goal is to bridge the gap between classical cryptographic theory and emerging LLM specific threats, and to outline research directions toward secure, privacy preserving, and rigorously evaluated LLM pipelines.
A meaningful representation in most succinct manner in social media is perhaps with profile pictures of users. These are present in every engagement on any platform alongside rival techniques such as creating posts, sending and receiving messages, viewing search results, filtering friend suggestions, integrating company interests, entrepreneurship frames, and even having interactions filtered in the form of career options and computer-generated interactions. Although their physical size is small, profile pictures are still framed as interfaces of identity, whereby the self is transformed into visible images that can be interpreted, particularly through contemporary cultural codes, current cultural practice norms, and even some social structures such as norms and values. The main objective of this paper is to investigate the current status of research on the uses of profile pictures in identity formation and to evaluate the key recommendations and lessons as well as truths revealed over the course of more than 30 research studies dedicated to the topics such as profile picture usage as an identity profile and selfie, use of visual representation in managing social media, and presentation patterns of digital self. To this end, the study seeks to address three research questions: how do profile pictures come into the build up of personal, social, cultural, professional and corporate as well as symbolical identities, what processes are there in theory and why, and which ways of investigating such complexities are the most pertinent. Imposed that the study follows the terms, a corpus-based research is carried out whereby cautiously all the elements investigated will be past and present profile picture research over here through coding broken down by year, theme, method of inquiry; platforms used and types of profiles. The spelling functions of profile pictures show that they provide for the construction of identity pronounced by a number of mechanisms. The five mechanisms of identity construction are manufactured spectacle, acted sincerity, conformity to norms, expectation of audience, and identification by representation. It also (a) is evident that profile pictures should not be viewed as a single and isolated action, for they have been waxing and waning under the impact of stereotypic practices specific to women and men, ethnic and age groups, cultures, professional areas, peer groups, which can also be adjusted by such conditions as features of the medium, technologies, and symbolic consumption of non fungible token avatars. To the field, the paragraph introduces a new identity face theory ‘profile picture as an identity interface’ and provides a plan focusing on the future of research, combining analysis of visual contents, studies of platforms, understanding of audience, pattern of computation manipulation of a picture data and extraction of identity narratives using distinct services.
The transition from traditional paper-based voting to electronic systems has introduced significant efficiencies but has simultaneously created centralized vulnerabilities, including susceptibility to database manipulation and a lack of transparent audit trails. This research proposes a decentralized, blockchain-based voting framework designed to restore public trust through cryptographic immutability and end-to-end verifiability. By utilizing a Permissioned Proof of Stake (PPoS) consensus mechanism, the system achieves the high transaction throughput necessary for national-scale elections while maintaining a decentralized security posture that prevents any single entity from compromising the results. The technical core of this framework integrates Zero-Knowledge Proofs (ZKPs) to resolve the tension between voter anonymity and auditability. This allows voters to prove their eligibility and the validity of their ballot without disclosing their identity or specific choice, thereby upholding the sanctity of the secret ballot. To address modern security threats, the study incorporates Post-Quantum Cryptography (PQC) to safeguard against future decryption capabilities and utilizes Layer 2 scaling solutions to ensure network resilience during peak voting periods. Methodological validation was conducted through a simulated electoral environment, testing the system against common attack vectors such as DDoS and 51% attacks. The results indicate that the decentralized model significantly reduces the risk of systemic fraud compared to centralized alternatives. This paper concludes that while socio-technical barriers to entry exist, the proposed blockchain architecture provides a scalable, secure, and transparent foundation for the future of digital democracy.
Zero-knowledge succinct non-interactive arguments of knowledge (zkSNARKs) are a key technology to privacy-preserving applications today. The complexity of proof generation, however, heavily constrains throughput in latency-sensitive environments. The computational burden primarily stems from two fundamental algorithms: Multi-Scalar Multiplication (MSM) and the Number Theoretic Transform (NTT). We propose a series of optimizations for these two kernels, including computation-transfer pipelining, load balancing, and memory access fusion, achieving 1.97 × to 2.16 × proof generation speedup over a state-of-the-art open source GPU acceleration library. Our design also supports out-of-core computation, enabling the generation of large-scale ZKP proofs.
As digital ecosystems expand, secure and interoperable identity management across organizational boundaries has become increasingly important. This paper presents a blockchain-based platform for decentralized identity and trust management to support cross-domain authentication and authorization among autonomous organizations, such as government agencies and academic institutions. The proposed platform employs a consortium blockchain as a tamper-resistant credential and policy repository, enabling each organization to administer its own credentials while supporting verifiable identity sharing across domains. On-ledger trust relationships and authorization policies allow trusted interactions without relying on centralized identity authorities or pre-established bilateral agreements. A prototype was implemented using Hyperledger Fabric and evaluated in a multi-domain setting. The results demonstrate correct authentication behavior, sub-second authentication latency, measurable transaction throughput, and effective revocation propagation. Additional experiments under multi-domain and concurrent authentication workloads show that the platform preserves consistent authentication outcomes while maintaining latency within practical bounds. The proposed approach can be applied to multi-institutional environments, such as inter-university digital services, cross-agency e-government systems, and collaborative research infrastructures, where secure identity sharing and cross-domain access control are required.
Distributed ledger technologies (DLTs) form critical infrastructure for decentralized applications, yet their security relies heavily on classical asymmetric cryptographic primitives that are vulnerable to quantum attacks. Post-quantum cryptography (PQC) provides candidate algorithms designed to resist such threats, but integrating these schemes into operational blockchain systems introduces significant architectural and performance trade-offs.
Proof-of-stake protocols lock tokens into staking positions, shrinking the tradable float. We develop a continuous-time model in which price-impact volatility is a convex decreasing function of the float. Two results emerge. Conditional return variance amplifies as the float contracts, with amplification accelerating in high-staking regimes. Protocol changes that shift the long-run staking target produce persistent volatility regime transitions, with convergence speed governed by protocol adjustment capacity. Liquid-staking tokens attenuate both effects, with attenuation increasing in their liquidity parameter.
Centralized cryptocurrency exchanges (CEXes) enable fast off-chain conversions between hundreds of coins. It is an open question which algorithmic trading patterns occur on these platforms. A major challenge to measuring CEXes is that their public trade data does not contain addresses or trader identifiers allowing linkage. We propose a novel methodology to infer one-way arbitrage (OWA) trading in anonymized spot trade data from CEXes. We identify 402 M likely OWA sequences in 5 years of trading on Binance (and almost 2 M during 9 years on Kraken), accounting for 0.94 % and 0.13 % of the total traded volume, respectively. While we estimate total profits of $31.2 M on Binance and $975 k on Kraken, profits from individual OWA sequences are less than $1 on average after accounting for trading fees. We also observe that OWA has become faster over time, while the profitability of individual sequences has decreased. Our findings highlight that pricing discrepancies regularly occur in CEXes, and raise questions for future work to identify the precise circumstances that enable profitable OWA.
Cryptocurrency markets exhibit periodic bursts in volatility and volume at one-minute, five-minute, and quarter-hour marks. Using trade data for six Binance perpetual contracts, we link these bursts to algorithmic participation: trade-size roundness declines sharply during them. The Autocorrelation Map, a clock-phase-resolved display, reveals serial dependence in order flow and returns at quarter-hour openings that conventional measures obscure. Opening returns are predictable out of sample, while opening order imbalance predicts returns over four to twelve hours, with much weaker effects at finer clock-time frequencies. Together, these findings characterize periodic algorithmic trading and its cross-frequency variation.
Saviz Changizi, Nasibeh Mohammadzadeh, Mohammad Shojafar, Rahim Tafazolli
Telecom fraud-control studies often stop at detector-level classification, but deployment use requires request-level policy resolution, lifecycle traceability, and auditability. This paper reframes fraud control as blockchain-linked auditable decision management for synthetic telecom/IoT fraud-control requests, and its main result is that the QLoRA-tuned LLM branch becomes much more usable than zero-shot prompting but mainly approaches, rather than outperforms, a lower-cost centralized ensemble. The framework maps each synthetic deployment record to a managed request, blocks explicit out-of-boundary cases through a deterministic hard-fraud gate, scores non-hard requests using centralized ML (M1), federated meta-learning (M2), or LLM-family risk sources (M3), and resolves actions through a shared five-state policy, two-zone refinement mechanism, and local Ethereum-compatible audit layer. Evaluation uses separate synthetic training data and a 100,000-record deployment replay corpus, so the study should be read as controlled drift-replay evidence rather than field validation or proof of live deployability. On validation, M1 gives the strongest balance, with legitimate-request FPR 0.0890 under the 0.10 operating cap and soft-fraud recall 0.8341. On labeled deployment replay, however, the legitimate-FPR gap becomes large: M1 rises to 0.1646 and M3-QLoRA to 0.1801, while M3-QLoRA reduces the M3-Base legitimate FPR from 0.3915 and reaches 0.8240 soft-fraud recall. Blockchain telemetry shows that lifecycle gas, cost, latency, and throughput differences are driven by submitted off-chain decision profiles rather than changes in fraud logic.
Rigorous Construction of 4D Quantum Yang-Mills Theory and the Mass Gap via Nexus Spin-Network Regularization Akim C. Setenta1 Nexus Theory Research Group | @seventy.dev Manuscript v2.1 — June 2026. Prepared for submission to arXiv (math-ph; hep-th). Abstract We present a complete mathematical construction of non-abelian quantum Yang–Mills theory on ℝ⁴ for any compact simple gauge group G, with the strict positivity of the mass gap (Δ > 0) as the central object of study. Building on the Nexus OmniScientia program together with Loop Quantum Gravity (LQG) techniques, we define the physical Hilbert space ℋgauge through spin-network states over cylindrical functions, regularized by a gauge-invariant ultraviolet cutoff Amin = 4πγ√3 ℓP2 fixed by the minimal non-zero eigenvalue of the LQG area operator. The Hamiltonian constraint is regularized via Thiemann's trick, producing an operator that we argue is essentially self-adjoint on a dense domain of finite spin-networks. We then examine, axiom by axiom, whether the resulting Schwinger functions can satisfy the Osterwalder–Schrader (OS) requirements in the continuum limit ℓP → 0. Reflection positivity (OS3) is approached without any global gauge-fixing, via Markovian Dirichlet forms on the orbit space 𝒜/𝒞 — a route that, if it can be made fully rigorous, would sidestep the Gribov ambiguity entirely rather than resolve it head-on. Regularity and tightness (OS1) are addressed through a non-abelian polymeric cluster expansion; Euclidean covariance (OS2) is argued to be restored in the renormalization-group sense as anisotropic lattice artifacts become irrelevant. Finally, a candidate spectral-gap bound Δ ≥ (N/2)ΛQCD2 is proposed from a Bakry–Émery curvature argument on the gauge-orbit space. We present this construction in the spirit it deserves: as a coherent and, to our knowledge, novel research program that reorganizes the resolution of the Yang–Mills Millennium Problem around tools from constructive field theory and loop quantum gravity — not as a closed, peer-reviewed proof. Several steps that we label explicitly as ‘proof sketches’ still require the kind of analytic control (uniformity in the cutoff, explicit constants, rigorous Wick rotation on the orbifold) that the Clay Mathematics Institute's criteria demand. Section 13 catalogs these open points candidly, both for the benefit of readers and as a working roadmap for completing the proof. Keywords: Yang–Mills mass gap; Bakry–Émery curvature; constructive quantum field theory; Osterwalder–Schrader axioms; loop quantum gravity; Dirichlet forms; Gribov ambiguity. 1 Independent researcher. Correspondence and source materials: @seventy.dev.
Sovereign is a Prove/Pull communication protocol designed to address the structural imbalance of modern digital communication, where senders can impose cognitive and computational costs on recipients without corresponding friction. The protocol requires messages to carry a cryptographic proof of intent through one of three mechanisms: adaptive Proof-of-Work, private zero-knowledge proximity credentials, or registry-attested clearance tokens. Verification is performed by a decentralized Sovereign Audit Network (SAN), which attests that messages satisfy recipient-defined acceptance policies before delivery. This document presents the complete architectural specification of Sovereign, including the MessageEnvelope format, federated attestation protocol, dual Sparse Merkle Tree issuer registry with revocation support, Groth16 zero-knowledge proximity credential circuit, identity hierarchy, security assumptions, economic model, limitations, and phased deployment strategy. This release is Version 1.0 of the design specification. It is an unimplemented protocol proposal; all performance figures are engineering targets based on primitive benchmarks and require validation through future reference implementation. The work is published to establish a public technical record, invite peer review, and support future research, collaboration, and implementation efforts.
This research introduces a radical paradigm shift in decentralized economic consensus and distributed ledger technology, moving beyond the thermodynamic inefficiencies of Proof-of-Work (PoW) and the quantum vulnerabilities of conventional Elliptic Curve Cryptography (ECDSA). By integrating Hyperdimensional Computing (HDC) within a 10,000-dimensional bipolar vector space and Module Learning with Errors (MLWE) via the ML-DSA (FIPS 204) post-quantum signature standard, this paper proposes the Asymptotic Stigmergic Lattice Consensus (ASLC) architecture. Instead of relying on energy-intensive validators, miners, or sequential blocks, transaction validation is achieved through deterministic thermodynamic gradient traces (Stigmergic Pheromone Decay). Verified via First-Order Logic and Bounded Model Checking through the Z3 SMT Solver Tribunal, the architecture mathematically proves that any double-spending attempt results in absolute destructive interference within the orthogonal vector space, instantly collapsing the fraudulent transaction probability into a scalar zero (0x00 Null Bytes). This framework achieves an absolute zero-entropy (isentropic) consensus bounded by the Landauer limit, rendering conventional blockchain ledgers computationally and thermodynamically obsolete. Keywords: Distributed Ledger Technology, Post-Quantum Cryptography, ML-DSA, Hyperdimensional Computing, Isentropic Consensus, Pheromone Decay, Double-Spending, Z3 SMT Solver, Bounded Model Checking, Zero-Miner Consensus
This document details the technical topology of the Asymptotic Stigmergic Lattice Consensus (ASLC) transaction engine, providing a deterministic mechanism to eradicate conventional sequential ledgers (blockchains) and energy-intensive validators (miners). By projecting transaction components (Sender, Receiver, and Amount) into a 10,000-dimensional continuous vector space via Hyperdimensional Computing (HDC) and securing them with FIPS 204 ML-DSA post-quantum signatures, this architecture achieves absolute zero-miner consensus. The engine mathematically proves that any double-spending attempt generates destructive interference within the orthogonal lattice, instantly neutralizing fraudulent transaction vectors into 0x00 Null Bytes. Furthermore, it introduces Phantom Tunnel transmission via WebRTC DataChannels for pure Peer-to-Peer (P2P) vector distribution, bypassing central Mempools and leaving zero forensic traces. This is not a probabilistic iteration of distributed ledgers; it is an absolute topological replacement. Keywords: ASLC Transaction Engine, Hyperdimensional Computing, Blockchain Eradication, Zero-Miner Consensus, Destructive Interference, Phantom Tunnel, WebRTC, Post-Quantum Cryptography, ML-DSA, Distributed Ledger Technology
Abstract A smart contract fundamentally consists of code deployed on the blockchain, noted for its transparent and unchangeable execution. These characteristics, however, also expose it to attackers once any weaknesses are present. In recent years, attacks targeting smart contracts have caused substantial financial losses, highlighting the importance of robust vulnerability detection approaches. Conventional detection techniques, which rely on contextual semantics or symbolic execution, often face limitations in efficiency. Although neural network-based approaches have enhanced detection speed, they frequently compromise accuracy. This study introduces a framework for identifying and repairing vulnerabilities in smart contracts by utilizing multi-relational graphs combined with a pre-trained model. Initially, a Multi-Relational Graph (MRG) is constructed to represent the multi-dimensional aspects of execution logic and data dependencies by integrating multiple program feature graphs. To reduce interference from extraneous code, contract slices are then generated according to node and edge types defined within the MRG. These vectorized slices are subsequently processed by a pre-trained model called SCCodeBERT for both detection and repair of potential vulnerabilities. Experiments show that SCCodeBERT achieves an average accuracy of 96.06% and an F1-score of 90.90% on mainstream vulnerability datasets. Moreover, it reaches an average repair effectiveness of 86.42%, significantly outperforming current baseline approaches. This work presents a highly effective automated solution for enhancing smart contract security, offering notable theoretical and practical contributions.
Yoon-Nyoung Jung, Subin Jo, Seo-Hyun Yun, Hwajeong Seo
Electronic voting systems inherently encompass a structural tension among ballot secrecy, verifiability, and coercion resistance. Voters must be able to verify whether their votes have been included; however, if such verification information can serve as evidence presentable to a third party, it becomes a basis for post-election intimidation. Existing studies have focused primarily on performance evaluation or data separation, and have not comprehensively addressed the structural tension between verifiability and coercion resistance. This study defines this tension as the verification paradox and designs and implements an electronic voting prototype on a three-organization consortium based on Hyperledger Fabric 2.5, combining a 2-of-3 endorsement policy, nullifier-based anonymity, Exponential ElGamal homomorphic tallying, zero-knowledge proof (ZKP)-based ballot validity verification, panic-password-based deniable verification, and Private Data Collection (PDC)-based coerced vote separation. Quantitative evaluation results confirm a server latency overhead of +0.9% for ElGamal relative to the AES performance baseline, statistical indistinguishability between normal and panic responses (p>0.05), and a peak throughput of approximately 40.7 TPS (with an error rate of 0%) under 1000 concurrent voters. Through this prototype implementation and quantitative evaluation, we show the potential of permissioned blockchains to partially and practically mitigate the verification paradox. This study, however, does not provide a formal security proof, and it is subject to a trust assumption on PDC as well as to the experimental limitations of a single evaluation environment and a limited load range.
Blockchain technology has profoundly revolutionized decentralized applications across financial systems, global supply chains, and applied informatics. However, it remains susceptible to systemic security hazards. This systematic review comprehensively evaluates core architectural vulnerabilities within blockchain infrastructures, consensus mechanisms, and peer-to-peer (P2P) network layers spanning the decade from 2015 to 2025. We focus primarily on the mechanics, operational taxonomy, and evolutionary trajectories of Sybil attacks, wherein malicious actors forge multiple pseudonymous identities to gain disproportionate systemic influence. By synthesizing the foundational academic literature with real-world empirical case studies, such as automated airdrop farming exploits in Layer-2 ecosystems (e.g., Arbitrum, zkSync) and decentralized finance (DeFi) governance manipulations, we analyze attack mechanisms, quantifiable impacts, and mitigation vectors. Our findings chart the structural evolution of Sybil strategies from rudimentary P2P routing disruptions to complex, economically driven application-layer interventions. Finally, we evaluate contemporary defenses, such as Proof-of-Personhood (PoP) systems and zero-knowledge (ZK) cryptography, offering actionable recommendations for the integration of W3C-compliant decentralized identity (DID) frameworks and behavioral analytics to enhance systemic fault tolerance.