Under the background of the deepening of digital China strategy and the diversification of public archives demand, the insufficient sharing and inefficient utilization of archives information resources have become a prominent bottleneck restricting the release of archives value. This paper systematically combs the policy evolution, platform practice and technology application status of file sharing in China, and finds that the lack of metadata standards, vague boundaries of powers and responsibilities, weak security prevention and control, and the interweaving of the concepts of "valuing custody and neglecting utilization" have formed systematic obstacles such as poor cross-domain circulation and mismatch between supply and demand. Therefore, this paper proposes four-dimensional collaborative paths: first, technology empowerment, deployment of alliance chain and zero-knowledge proof to achieve "availability and invisibility", and construction of multi-modal retrieval and personalized recommendation engine; Second, institutional innovation, the development of open value assessment guidelines and "negative list+white list" mechanism, the establishment of joint meetings and third-party performance audits; The third is management optimization, implementing the dual-track talent project of "archives +IT" and reshaping the accurate service process driven by user portraits; Fourth, social coordination, building a digital community of "urban memory" of archives, libraries and museums, and introducing the feedback mechanism of crowdsourcing and cultural and creative income. The research provides an operational framework for the government to formulate an open policy and the digital transformation of institutions, and promotes the archival resources from "physical concentration" to "value aggregation".
We present Y.I.N.-MEMORIA, a comprehensive privacy-preserving architecture addressing fundamental vulnerabilities in AI conversation systems across all platforms, including large language model interfaces, enterprise AI assistants, domain-specific chatbots, and agentic AI systems. The system implements mandatory cryptographic ordering enforcement (DP → ZK → BLINDING → HE, or functional equivalents), mathematically proven unique among 24 permutations, achieving 99.37% accuracy for valid authorizations versus 50.7% for invalid attempts (t = 147.3, p < 10⁻⁵⁰). KEY CONTRIBUTIONS:• Hybrid local-cloud storage with zero-knowledge properties ensuring cloud providers mathematically cannot decrypt conversations• Enterprise Shadow AI governance achieving 99.7% detection across 50+ services via network pattern analysis without plaintext access• Y.A.N.G. constant-time retrieval providing 340× timing attack resistance (reduced leakage from 2.72 to 0.008 bits per 1,000 queries)• Complete defense taxonomy across 8 attack categories with quantified metrics (92-99% detection rates)• Advanced cryptographic primitives including post-quantum aggregate signatures (90% size reduction), threshold token generation, VRFs, adaptive differential privacy (4-tier ε system), federated unlearning (SISA), and incremental Merkle tree encryption• Four complete deployment architectures (cloud-only, local-only, mobile-only, enterprise gateway) validated across 4 hardware platforms and 5 operating systems• Y.I.N. CERTIFY compliance verification layer enabling machine-readable regulatory certificates for GDPR, DORA, EU AI Act, HIPAA, and Singapore's Model AI Governance Framework for Agentic AI• Synergistic combination claims and negative exclusion claims establishing comprehensive defensive prior art ENHANCED VERSION 10.0 FEATURES:Academic Rigor: 4 formal research questions with quantified success criteria; 3 mathematical security proofs (Privacy Preservation, Computational Soundness, Unbypassability); Ablation studies validating necessity of each component; Cross-platform validation (4 hardware platforms, 5 operating systems, <3% variance); 3 novel attack scenarios with >94% detection rates. Comparative Analysis: Table comparing against 8 major systems (Federated Learning, CrypTen, TF Privacy, Opacus, PySyft, Microsoft SEAL, Zcash). Y.I.N.-MEMORIA demonstrated as only system providing mandatory DP enforcement, ZK verification for AI governance, 340× timing resistance, 99.7% Shadow AI detection, and complete lifecycle coverage. Legal Protection: Doctrine of equivalents coverage (Warner-Jenkinson precedent); Willful infringement notice (Halo Electronics, 3× damages); Comprehensive functional equivalents (12 categories); Minimum performance thresholds excluding weak implementations. Reproducibility Commitment: Complete reference implementation under open-source license; Experimental datasets via Zenodo; Cryptographic test vectors for independent verification; Performance benchmarks across all platforms. Scholarly Depth: 38 peer-reviewed citations (65% increase); Comprehensive related work analysis; Explicit limitations and future research directions; Historical non-obviousness evidence. THREE-PHASE AI LIFECYCLE COVERAGE:Y.I.N.-MEMORIA completes the Y.I.N. Architecture's three-phase AI lifecycle: Training (Y.I.N.-LLM, USPTO 63/941,283), Generation (Article 50 Compliance Engine, USPTO 63/957,571), and Usage (Y.I.N.-MEMORIA, USPTO 63/967,805). The Y.I.N. CERTIFY verification layer spans all three phases. Together, these components provide 643 total claims covering every stage where privacy vulnerabilities can emerge in AI systems. EXPERIMENTAL VALIDATION:85-95% bandwidth reduction, 97% conflict resolution, and compliance scores of 94.7-97.3% for GDPR, HIPAA, DORA, EU AI Act, Singapore MGF for Agentic AI, ISO/IEC 42001, CCPA, and NIS2 Directive. IMPACT METRICS:This architecture prevents Shadow AI breaches costing $4.63M average (20% of all data breaches according to IBM's 2025 Cost of a Data Breach Report), addresses the 20M ChatGPT conversation log discovery precedent (NYT v. OpenAI, January 2026), and satisfies Singapore's Model AI Governance Framework for Agentic AI—the world's first comprehensive government framework for autonomous agents published January 22, 2026 (4 days prior to this work). DEFENSIVE PRIOR ART:This work establishes comprehensive prior art corresponding to USPTO Provisional Application 63/967,805 (438 claims filed January 25, 2026), part of the Y.I.N. Architecture Portfolio (22 applications, 1,360+ total claims). Includes explicit functional equivalents coverage, doctrine of equivalents, and willful infringement notice enabling enhanced damages up to 3× under Halo Electronics precedent. Patent Reference: USPTO Application 63/967,805 (Y.I.N.-MEMORIA) License: CC BY-NC-ND 4.0Corresponding Author: ilyesmazari@hotmail.comVersion: 1.0Publication Date: January 26, 2026
Uma Girish, Greg Gluch, Shafi Goldwasser, Tal Malkin · 6 authors
Position verification schemes are interactive protocols where entities prove their physical location to others; this enables interactive proofs for statements of the form "I am at a location $L$." Although secure position verification cannot be achieved with classical protocols (even with computational assumptions), they are feasible with quantum protocols. In this paper we introduce the notion of zero-knowledge position verification, which generalizes position verification in two ways: 1. enabling entities to prove more sophisticated statements about their locations at different times (for example, "I was NOT near location $L$ at noon yesterday"). 2. maintaining privacy for any other detail about their true location besides the statement they are proving. We construct zero-knowledge position verification from standard position verification and post-quantum one-way functions. The central tool in our construction is a primitive we call position commitments, which allow entities to privately commit to their physical position in a particular moment, which is then revealed at some later time.
The rapid growth of blockchain technologies has enabled decentralized applications based on smart contracts and distributed consensus. However, the increasing number of attacks exploiting protocol logic and network dynamics highlights the limitations of traditional, static security mechanisms. This study proposes an adaptive cognitive security model based on a Q-learning agent to enhance the protection of blockchain protocols. The agent is designed to analyze transaction behavior, assess risk levels, and dynamically select appropriate countermeasures. The proposed approach is evaluated through a dual experimental framework combining large-scale simulation using SimPy and execution on a private blockchain environment implemented with Ganache. Experimental results show a detection rate of approximately 70%, no observed false positives, a response time close to one second, and a very low operational gas cost. These results demonstrate that reinforcement learning can effectively improve the adaptability and responsiveness of blockchain security mechanisms while preserving network performance and economic viability. The study confirms the potential of cognitive and adaptive approaches for building more resilient and autonomous blockchain security systems.
Smart mobility services generate large volumes of sensitive location and identity data, raising critical concerns related to privacy leakage, security vulnerabilities, and trust in large-scale urban deployments. To address these challenges, this paper proposes a blockchain-based privacy-preserving framework for smart mobility services that integrates geo-indistinguishability, pseudonymous authentication, Zero-Knowledge Proofs (ZKPs), and Proof-of-Authority (PoA) consensus into a unified architecture. The framework ensures end-to-end privacy by combining calibrated location obfuscation with decentralized transaction validation and immutable auditability, thereby mitigating both inference-based attacks and reliance on centralized trust. The proposed framework was evaluated using the TAPAS Cologne mobility dataset, comprising 1,000 simulated vehicles and 20 block-chain validators. Experimental results demonstrate that adversarial inference accuracy is reduced to below 12%, while approximately 75% navigation utility is preserved at balanced privacy budgets. Security analysis confirms robust protection against tracking, replay, Sybil, and collusion attacks, with replay attack success rates reduced from 70% to 2% through the enforcement of timestamps and nonces, along with cryptographic verification. Performance evaluation demonstrates that the framework achieves high throughput (1,200 transactions per second) with sub-second latency (0.8 seconds) under realistic transaction loads. Storage growth is optimized to 2.1 GB per million transactions, and the PoA consensus mechanism achieves approximately 30% lower energy consumption compared to Proof-of-Stake-based designs. In addition, resilience ex-periments confirm Byzantine fault tolerance under up to 30% malicious validator participation, without service degradation. Overall, the results demonstrate the practical feasibility of deploying the proposed framework in real-world smart mobility ecosystems that require simultaneous privacy preservation, scalability, and energy efficiency. The framework represents a significant step toward trustwor-thy, privacy-aware, and sustainable smart-city mobility infrastructure, providing a robust foundation for next-generation decentralized mo-bility services.
This study has been undertaken in the burgeoning intersection of financial technology (Fintech) and Environmental, Social, and Governance (ESG) paradigms, a domain that serves the purpose of redefining capital allocation in the 21st century. The research investigates the "Digital-Sustainability Convergence" theory, which posits that digital innovations serve the purpose of democratizing green finance and enhancing transparency. However, a critical review of the literature reveals a phenomenon termed the "Green Mirage," where the digital representation of sustainability obscures a lack of tangible ecological impact. Utilizing a bibliometric analysis based on VOS viewer logic, this paper examines a dataset of academic literature from 2015 to 2025. The findings indicate that while publication volume is on a rise, particularly in China and the United Kingdom, the intellectual structure is fragmented. The analysis identifies a significant gap between technological implementation—such as blockchain and artificial intelligence (AI)—and genuine sustainability outcomes. It is important to note that concepts like "token washing" and "digital greenwashing" have emerged as pivotal retention factors for critical scholarship, suggesting that the sector faces an important challenge in aligning "proof of stake" with "proof of impact." The study concludes that while Fintech serves the purpose of mobilizing retail capital, with 81.5% of investors considering ESG factors, the prevalence of managerial myopia and data asymmetry poses a challenge for the integrity of the ecosystem. Thus, it is important that regulators and practitioners move beyond symbolic compliance to address the structural disconnects identified.
Paul van Vulpen, Sub Software Production, Slinger Jansen, Sjaak Brinkkemper
The rise of Big Tech has created unprecedented concentrations of power. The scaling potential of the modern IT industry is leading to widespread monopolies. For technologies that serve society, a monopoly brings structural dependence, and gives their owners an almost unchallengeable power. To counteract this societal dependence, academia, industry, and society at large proposed various countermeasures to limit the power of technology providers. In this thesis, Paul van Vulpen compares these approaches. The goal is to maintain the benefits of technology while reducing societal dependence on a few powerful actors. This book investigates three approaches. First, software ecosystems outline the collaboration between various interrelated software actors. Second, blockchain and decentralized autonomous organizations offer radical approaches to rethink and decentralize IT governance structures. Finally, digital platform regulations address urgent societal issues that arise from concentrated platform power. The final section concludes that a delicate and organic approach is needed to IT governance. Excessive centralization creates structural risks, but full decentralization is neither practical nor beneficial. The thesis proposes a middle road: Federated Technology Governance (FTG). In FTG, central authority defines architecture, interoperability standards, and maintains the long-term vision. A wide variety of actors handle user interaction, implementation, and collaboration. This framework helps technology providers to create software ecosystems and safeguard the provision of societal benefit for public digital infrastructure. FTG supports the creation of sovereign cloud services, secure operating systems, and public large language models. Could it also be a road to enable technology to serve society and the common good?
Abdullah Umar, Prashant K. Jamwal, Deepak Kumar, Nitin Gupta · 6 authors
Renewable-driven microgrids require transparent and adaptive coordination mechanisms to manage variability in distributed generation and flexible demand. Conventional pricing schemes and centralized demand-side programs are often insufficient to regulate real-time imbalances, leading to inefficient renewable utilization and limited prosumer participation. This work proposes a blockchain-integrated Stackelberg pricing model that combines real-time price regulation, optimal demand-side management, and peer-to-peer energy exchange within a unified operational framework. The Microgrid Energy Management System (MEMS) acts as the Stackelberg leader, setting hourly prices and demand response incentives, while prosumers and consumers respond through optimal export and load-shifting decisions derived from quadratic cost models. A distributed supply–demand balancing algorithm iteratively updates prices to reach the Stackelberg equilibrium, ensuring system-level feasibility. To enable trust and tamper-proof execution, smart-contract architecture is deployed on the Polygon Proof-of-Stake network, supporting participant registration, day-ahead commitments, real-time measurement logging, demand-response validation, and automated settlement with negligible transaction fees. Experimental evaluation using real-world demand and PV profiles shows improved peak-load reduction, higher renewable utilization, and increased user participation. Results demonstrate that the proposed framework enhances operational reliability while enabling transparent and verifiable microgrid energy transactions.
Auditability and reproducibility still are critical challenges for real-time data streams pipelines. Streaming engines are highly dependent on runtime scheduling, window triggers, arrival orders, and uncertainties such as network jitters. These all derive the streaming pipeline platforms to throw non-determinist outputs. In this work, we introduce a blockchain-backed provenance architecture for streaming platform (e.g Kafka Streams) the publishes cryptographic data of a windowed data stream without publishing window payloads on-chain. We used real-time weather data from weather stations in Berlin. Weather records are canonicalized, deduplicated, and aggregated per window, then serialised deterministically. Furthermore, the Merkle root of the records within the window is computed and stored alongside with Kafka offsets boundaries to MultiChain blockchain streams as checkpoints. Our design can enable an independent auditor to verify: (1) the completeness of window payloads, (2) canonical serialization, and (3) correctness of derived analytics such as minimum/maximum/average temperatures. We evaluated our system using real data stream from two weather stations (Berlin-Brandenburg and Berlin-Tempelhof) and showed linear verification cost, deterministic reproducibility, and with a scalable off-chain storage with on-chain cryptographic anchoring. We also demonstrated that the blockchain can afford to be integrated with streaming platforms particularly with our system, and we get satisfactory transactions per second values.
Daniel Commey, Matilda Nkoom, Yousef Alsenani, Sena G. Hounsinou · 5 authors
Virtual Asset Service Providers (VASPs) face a fundamental tension between regulatory compliance and user privacy when detecting cross-institutional money laundering. Current approaches require either sharing sensitive transaction data or operating in isolation, leaving critical cross-chain laundering patterns undetected. We present FedGraph-VASP, a privacy-preserving federated graph learning framework that enables collaborative anti-money laundering (AML) without exposing raw user data. Our key contribution is a Boundary Embedding Exchange protocol that shares only compressed, non-invertible graph neural network representations of boundary accounts. These exchanges are secured using post-quantum cryptography, specifically the NIST-standardized Kyber-512 key encapsulation mechanism combined with AES-256-GCM authenticated encryption. Experiments on the Elliptic Bitcoin dataset with realistic Louvain partitioning show that FedGraph-VASP achieves an F1-score of 0.508, outperforming the state-of-the-art generative baseline FedSage+ (F1 = 0.453) by 12.1 percent on binary fraud detection. We further show robustness under low-connectivity settings where generative imputation degrades performance, while approaching centralized performance (F1 = 0.620) in high-connectivity regimes. We additionally evaluate generalization on an Ethereum fraud detection dataset, where FedGraph-VASP (F1 = 0.635) is less effective under sparse cross-silo connectivity, while FedSage+ excels (F1 = 0.855), outperforming even local training (F1 = 0.785). These results highlight a topology-dependent trade-off: embedding exchange benefits connected transaction graphs, whereas generative imputation can dominate in highly modular sparse graphs. A privacy audit shows embeddings are only partially invertible (R^2 = 0.32), limiting exact feature recovery.
The long-term security of public blockchains strictly depends on the hardness assumptions of the underlying digital signature schemes. In the current scenario, most deployed cryptocurrencies and blockchain platforms rely on elliptic-curve cryptography, which is vulnerable to quantum attacks due to Shor's algorithm. Therefore, it is important to understand how post-quantum (PQ) digital signatures behave when integrated into real blockchain systems. This report presents a blockchain prototype that supports multiple quantum-secure signature algorithms, focusing on CRYSTALS-Dilithium, Falcon and Hawk as lattice-based schemes. This report also describes the design of the prototype and discusses the performance metrics, which include key generation, signing, verification times, key sizes and signature sizes. This report covers the problem, background, and experimental methodology, also providing a detailed comparison of quantum-secure signatures in a blockchain context and extending the analysis to schemes such as HAETAE.
This paper extends the classical Avellaneda-Stoikov framework for optimal market making to blockchain networks with directed acyclic graph (DAG) structure. In DAG-based consensus protocols such as GHOSTDAG, multiple blocks are produced in parallel, creating a branching time structure that fundamentally alters the market maker's optimization problem. We derive a DAG-extended Hamilton-Jacobi-Bellman equation that incorporates the probability distribution over transaction acceptance, showing that optimal spreads depend on the anticipated ordering of parallel blocks. Our main theoretical result demonstrates that market makers achieve O(1/n) variance reduction in inventory risk by distributing quotes across n parallel execution paths, exploiting the transaction-level mutual exclusivity inherent to GHOSTDAG ordering. We extend the framework to K correlated assets (proving portfolio-level variance reduction of O(K/n)) and provide adversarial robustness analysis under bounded hash power attacks. Implementation analysis for the Kaspa network (10 BPS, k=124 post-Crescendo) addresses practical constraints including direct-to-miner submission requirements, fee incentive compatibility, and latency bounds. Monte Carlo simulations validate theoretical predictions, showing Sharpe ratio improvements of 40-82% over single-path strategies under realistic network conditions. This work establishes foundational theory for high-frequency decentralized finance applications on DAG-based blockchains.
This study examines the dynamic and multiscale connectedness among cryptocurrencies, energy markets, macro-financial variables, and environmental indicators in the United States from January 2014 to June 2025. Using a hybrid framework that combines wavelet decomposition with a time-varying parameter vector autoregression (TVP-VAR), we assess spillovers across short-, medium-, and long-term horizons. The results reveal a persistently high level of systemic integration, with the Total Connectedness Index (TCI) ranging between 70 % and 90 % and reaching about 93 % at long horizons. Three contagion regimes are identified: energy-crypto dominance before 2020, financial synchronization during the COVID-19 crisis, and a macro-energy-environmental phase after 2021 that evolves into a digital-sustainability regime by 2025. The multiscale decomposition uncovers hidden directional reversals, Bitcoin price shifts from a short-term volatility transmitter to a long-run structural influencer, while transaction and capitalization variables move from emitters to receivers as horizons lengthen. Robustness tests using a rolling-window VAR confirm the persistence of these dynamics. Overall, the evidence shows that short-term contagion is speculative and energy-driven, whereas long-term connectedness is anchored in inflation, industrial production, and electricity prices. These findings offer actionable insights for investors and policymakers seeking to manage systemic risk and design sustainable strategies at the intersection of digital finance, energy markets, and environmental policy.
The 2025 Annual Meeting of National Neglected Tropical Disease (NTD) Programme Managers (2025 PMM) in the WHO African Region convened stakeholders in Lomé, Togo, under the theme "Innovating for Acceleration: Pathway to NTD Elimination." A key focus was the changing funding environment and the necessity for enhanced integration of NTD services within health systems to guarantee sustainable advancement toward the 2030 elimination goals. The conference was convened in the context of substantial disruptions stemming from the USAID funding pause, which interrupted essential mass drug administration (MDA) programmes and epidemiological monitoring activities across multiple nations. Country experiences highlighted the fragility of external funding dependence and underscored the importance of domestic resource mobilization, decentralized implementation, and programmatic integration. Strategic discussions highlighted opportunities to incorporate NTD services into national health financing mechanisms, and routine health campaigns, alongside leveraging digital tools and partnerships. Participants emphasized the urgency of political commitment, sustained investments, and integrated service delivery models to build resilience and close equity gaps. The meeting further underscored the need for bold, country-led responses and multisectoral collaboration to advance NTD elimination efforts in a rapidly evolving global health financing environment.
Penelitian ini bertujuan untuk membuktikan secara empiris (Proof-of-Concept) bahwa Bahasa Indonesia memiliki kapasitas leksikal untuk menggantikan peran Bahasa Inggris dalam protokol BIP-39 tanpa mendegradasi keamanan matematis sistem. Metode yang digunakan adalah eksperimental terapan dengan mengembangkan wordlist 2048 kata Bahasa Indonesia dan mengimplementasikan algoritma derivasi kunci pada lingkungan browser extension. Hasil pengujian menunjukkan bahwa sistem mampu menghasilkan entropi 128-bit yang ekuivalen dengan standar NIST serta berhasil melakukan tanda tangan digital (ECDSA) yang valid pada jaringan Ethereum Sepolia. Kesimpulan: Bahasa Indonesia terbukti memiliki kesetaraan fungsional dalam konteks kriptografi terapan, namun penggunaannya dibatasi sebagai eksperimen riset dan bukan untuk menggantikan standar global. DISCLAIMER: Penelitian ini bersifat eksperimental. Wordlist Indonesia tidak kompatibel dengan wallet standar (MetaMask, Ledger, dll). Seed phrase yang dibuat tidak dapat di-import ke wallet lain.
Το Πολυσύμπαν (αγγλικά: metaverse), ένα εμβυθιστικό και διασυνδεδεμένο ψηφιακό οικοσύστημα που συνδυάζει την επαυξημένη και την εικονική πραγματικότητα, επαναπροσδιορίζει με ταχύ ρυθμό τα όρια του δικαίου της διανοητικής ιδιοκτησίας. Στα εικονικά αυτά περιβάλλοντα, άτομα και επιχειρήσεις μπορούν να δημιουργούν, να κατέχουν, να εμπορεύονται και να αξιοποιούν οικονομικά ψηφιακά αγαθά — από εικονική τέχνη και μουσική έως άβαταρ (avatars), εικονικά ακίνητα και επώνυμες εμπειρίες. Οι νέες αυτές μορφές δημιουργικότητας, ωστόσο, αναδεικνύουν σημαντικά κενά στα υφιστάμενα νομικά πλαίσια, τα οποία έχουν σχεδιαστεί πρωτίστως για τον φυσικό κόσμο. Στο παρόν άρθρο εξετάζονται οι αναδυόμενες προκλήσεις προστασίας των δικαιωμάτων διανοητικής ιδιοκτησίας (ΔΔΙ) στο metaverse, με έμφαση στο δίκαιο της πνευματικής ιδιοκτησίας, των εμπορικών σημάτων και των διπλωμάτων ευρεσιτεχνίας. Παράλληλα, ενσωματώνονται προσεγγίσεις από την Ευρωπαϊκή Ένωση, τις Ηνωμένες Πολιτείες και την Ινδία, με εξέταση ζητημάτων διασυνοριακής επιβολής, του ρόλου της τεχνητής νοημοσύνης και της αυξανόμενης επιρροής μοντέλων ιδιοκτησίας που βασίζονται στην τεχνολογία blockchain, όπως τα Μη Ανταλλάξιμα Διακριτικά (Non-Fungible Tokens – NFTs). Το άρθρο υποστηρίζει ότι, παρότι το ισχύον δίκαιο παρέχει μερική προστασία, η διαμόρφωση ενός εναρμονισμένου και τεχνολογικά προσαρμοστικού παγκόσμιου ρυθμιστικού πλαισίου είναι απαραίτητη για τη διασφάλιση της καινοτομίας και της δημιουργικότητας στα εικονικά περιβάλλοντα.
Smart contract security is paramount, but identifying intricate business logic vulnerabilities remains a persistent challenge because existing solutions consistently fall short: manual auditing is unscalable, static analysis tools are plagued by false positives, and fuzzers struggle to navigate deep logic states within complex systems. Even emerging AI-based methods suffer from hallucinations, context constraints, and a heavy reliance on expensive, proprietary Large Language Models. In this paper, we introduce Heimdallr, an automated auditing agent designed to overcome these hurdles through four core innovations. By reorganizing code at the function level, Heimdallr minimizes context overhead while preserving essential business logic. It then employs heuristic reasoning to detect complex vulnerabilities and automatically chain functional exploits. Finally, a cascaded verification layer validates these findings to eliminate false positives. Notably, this approach achieves high performance on lightweight, open-source models like GPToss-120B without relying on proprietary systems. Our evaluations demonstrate exceptional performance, as Heimdallr successfully reconstructed 17 out of 20 real-world attacks post June 2025, resulting in total losses of $384M, and uncovered 4 confirmed zero-day vulnerabilities that safeguarded $400M in TVL. Compared to SOTA baselines including both official industrial tools and academic tools, Heimdallr at most reduces analysis time by 97.59% and financial costs by 98.77% while boosting detection precision by over 93.66%. Notably, when applied to auditing contests, Heimdallr can achieve a 92.45% detection rate at a negligible cost of $2.31 per 10K LOC. We provide production-ready auditing services and release valuable benchmarks for future work.
Devika T D, Sangeeth Karunakaran, Basudev Balachandran, S Shinas · 5 authors
Managing crypto investments for retail investors is often hindered by high volatility, poor timing (buying at peaks and selling at lows), and the inherent risks of centralized platforms. This project introduces a decentralized, automated SIP model for crypto investments, offering a non-custodial and multi-asset investment protocol to limit these challenges. The system automates crypto investing like a Systematic Investment Plan (SIP). All SIP rules (amount, frequency, maturity) are enforced automatically by smart contracts, ensuring trustless and transparent execution. Users maintain full custody of their funds in non-custodial wallets like MetaMask, and investments are made directly using stablecoins (USDT/USDC) into crypto pools (BTC, ETH, SOL, BNB). The purchased assets are stored in a smart contract vault until maturity, promoting structured long-term investing and verifiable on-chain transparency. By leveraging smart contracts and dynamic frequency validation, the system provides a consistent, reliable, and non-custodial solution for long-term wealth building in the decentralized Web3 space.
For the past three decades, the architecture of the internet has rested on two primary pillars - communication on the World Wide Web and Value such as Bitcoin/Distributed ledgers. However, a third critical pillar, Private Coordination has remained dependent on centralised intermediaries, effectively creating a surveillance architecture by default. This paper introduces the 'Stateless Pattern', a novel network topology that replaces the traditional 'Fortress' security model (database-centric) with a 'Mist' model (ephemeral relays). By utilising client-side cryptography and self-destructing server instances, we demonstrate a protocol where the server acts as a blind medium rather than a custodian of state. We present empirical data from a live deployment (https://signingroom.io), analysing over 1,900 requests and cache-hit ratios to validate the system's 'Zero-Knowledge' properties and institutional utility. The findings suggest that digital privacy can be commoditised as a utility, technically enforcing specific articles of the universal declaration of human rights not through policy, but through physics.
Yao Zhao, Zhang Sheng, Shengchen Duan, Shen Wang · 6 authors
Obfuscation raises the interpretation cost of smart-contract auditing, yet its signals are hard to transfer across chains. We present HOBFNET, a fast surrogate of OBFPROBE, enabling million-scale cross-chain scoring. The model aligns with tool outputs on Ethereum (PCC 0.9158, MAPE 8.20 percent) and achieves 8-9 ms per contract, yielding a 2.3k-5.2k times speedup. Across BSC, Polygon, and Avalanche, we observe systematic score drift, motivating within-chain percentile queues (p99 as the main queue, p99.9 as an emergency queue). The high-score tail is characterized by rare selectors, external-call enrichment, and low signature density, supporting secondary triage. Cross-chain reuse is tail-enriched and directionally biased from smaller to larger ecosystems. On two publicly alignable cross-chain spillover cases, both fall into the p99 queue, indicating real-world hit value. We deliver a two-tier audit queue and a cross-chain linkage workflow for practical security operations.
Blockchain technology is a Distributed Ledger Technology (DLT) where the digital information is stored across multiple computers and not centralized.Each system stores a copy of DLT to avoid single point of failure.Blockchain stores the information in blocks.All copies are validated and updated simultaneously.There are four main types of blockchain, they are Private / Permissioned, Public / Permissionless, Hybrid and Consortium.Corda is a distributed ledger open-source platform, it was introduced by R3 consortium (R3CEV LLC).It is not a public blockchain, based on agreement network and Peer to Peer (P2P) connections.No native cryptocurrency.Tech stack platform based out of JVM written in Koltin.
Abstract Existing accountability mechanisms based on audit logs, blockchains, and distributed ledgers attempt to prove compliance by recording what happened—transactions, identities, timestamps, or state transitions. While tamper-resistant, these approaches inherently generate behavioural traces that conflict with data-minimisation requirements and enable correlation, profiling, and surveillance. This creates a structural accountability–privacy paradox in modern regulatory frameworks such as the GDPR, which simultaneously require demonstrable compliance (Art. 5(2)) and strict limitation of personal data collection (Art. 5(1)(c)). This paper introduces Ledger-Anchored Validation Receipts (LAVR), a cryptographic mechanism that resolves this paradox by proving that enforcement occurred, rather than recording the underlying activity. LAVR operates exclusively at system finality boundaries—points where actions become irreversible, such as database commits, cross-border data exports, AI output release, payment settlement, or content publication. At each finality point, a hardware-adjacent enforcement gate evaluates a regulatory validation predicate derived from applicable legal constraints. Upon decision (Allow or Deny), the gate generates a minimal, fixed-size receipt that contains only enforcement metadata and explicitly excludes payloads, identities, transaction details, routing information, and fine-grained timestamps. The operational workflow consists of four steps: (1) an execution request reaches a finality boundary; (2) a trusted validation context evaluates scope, purpose, and control predicates; (3) a non-identifying receipt is cryptographically generated; and (4) a hash commitment of the receipt is anchored to a tamper-evident ledger. Unlike blockchain transaction logs, the ledger anchors only receipt commitments—not events—preventing the formation of transaction graphs or behavioural histories. Implemented using commodity hardware primitives (Trusted Execution Environments, SmartNICs, secure elements, and kernel-level finality hooks), LAVR enables accountability without surveillance across GDPR, AI Act, eIDAS, CBDC, NIS2, and Democracy Shield contexts. The approach demonstrates that regulatory simplification and stronger enforcement can be achieved through execution-time cryptographic proof rather than expanded monitoring or deregulation.
Amer A. Hijazi, Ali Alashwal, Milad Baghalzadeh Shishehgarkhaneh, Rodrigo N. Calheiros
. The integration of Blockchain with Building Information Modelling (BIM) addresses persistent challenges of transparency, accountability, interoperability, and trust in construction. Yet, systematic insights into Blockchain–BIM implementation remain limited. This study conducts a Systematic Literature Review (SLR), identifying six lifecycle stages where integration occurs, supported by 29 workflows and 30 technical methods. Applications include blockchain-secured design reviews, provenance tracking, automated procurement, smart payments, and immutable handover records. BIM data types—design metadata, cost and schedule data, IoT evidence, and compliance records—are mapped to smart contract functions and blockchain platforms. Key mechanisms such as hybrid on/off-chain storage, cryptographic hashing, access controls, and watermarking are comparatively analyzed. Results show permissioned platforms (e.g., Hyperledger Fabric) enable controlled collaboration, while public ones (e.g., Ethereum) support transparency and tokenization. The review provides a structured taxonomy and conceptual framework to advance theory and guide Blockchain–BIM adoption in complex construction projects.
This Insights Report examines a structural shift in doctoral-level output from dissertation-centred “knowledge artifacts” toward “capability proof” evidenced through validated prototypes, engineered systems, design dossiers, pilot data, and – in some models – venture formation. It synthesizes six reference cases: Harbin Institute of Technology’s product-based PhD defense pilot; Xi’an Jiaotong–Liverpool University Taicang’s XEC + X³ venture-creation system; Germany’s SPRIND–Deep Science Ventures Venture Science Doctorate (with Helmholtz Munich partnership); Canada’s Invention to Innovation (i2I) translational training model; Europe’s eurx.ai researcher-to-founder infrastructure; and the Dutch EngD design doctorate. A heuristic “Shift Index” (0–5) is used to compare programme logics across five dimensions: thesis substitution, hybrid evaluation panels, embedded commercialization pathways, standardized throughput/scale, and IP/deployment orientation. Appendix A contrasts these models with the current doctoral regulations and output logics at Berlin University Alliance institutions (FU Berlin, HU Berlin, TU Berlin; and Charité as applicable) and outlines governance options for experimentation without abandoning academic rigor.