After laying out what the metaverse is and what makes it tick, the focus shifts to avatars. This chapter also looks at tech like augmented reality (AR), virtual reality (VR), and three-dimensional (3D) worlds. Using todayâs research, it maps how the metaverse has grown and why both users and sharp entrepreneurs are diving in to build fresh startups. It shows how companies are already using this space to create new ways to connect with customers â from opening digital shops and running eye-catching marketing, to buying virtual land and building blockchain-powered markets. Additionally, it explores complex topics such as virtual economies, the significance of non-fungible tokens (NFTs), and the incorporation of artificial intelligence (AI)-driven avatars, all of which serve to illustrate the wide-ranging possibilities within this virtual ecosystem. Moreover, this chapter addresses the obstacles associated with the metaverse, such as privacy concerns, ensuring digital accessibility, and the necessity for regulatory frameworks to establish fair and secure virtual spaces. This chapter concludes with a call to action for entrepreneurs.
âą We examine the profitability of a cryptocurrency momentum strategy using 9 âsurvivor coinsâ. âą The survivor cryptocurrency momentum portfolio (SCMP) does not generate significant payoffs. âą SCMP does not leverage a plain momentum strategy based on a broader set of coins. âą Significant payoffs documented for momentum strategies are an artefact of coins that are only temporarily accessible for trading. Motivated by the significant illiquidity observed in the cryptocurrency marketâexemplified by phenomena such as "defaulted coins"âthis study is the first to investigate a cryptocurrency-specific analog of currency momentum, as implemented among G10 currencies. We analyze nine free-floating cryptocurrencies that remained within the top 100 altcoins by market capitalization during the sample period, spanning January 2017 to August 2024. Using weekly data, we evaluate two cryptocurrency momentum strategies: one focused solely on survivor coins and another utilizing the largest 30 coins for a given year (referred to as "plain cryptocurrency momentum"). Our main findings are as follows: (a) Cryptocurrency momentum is not evident when applied to survivor coins; (b) plain cryptocurrency momentum is profitable only after the dataset is trimmed; (c) the profitability of trimmed plain cryptocurrency momentum does not result from leveraging survivor coin-based cryptocurrency momentum; (d) even after trimming, the profitability of plain cryptocurrency momentum is highly sample-dependent.
Do online narratives leave a measurable imprint on prices in markets for digital or cultural goods? This paper evaluates how community attention and sentiment relate to valuation in major Ethereum NFT collections after accounting for time effects, market-wide conditions, and persistent visual heterogeneity. Transaction data for large generative collections are merged with Reddit-based discourse measures available for 25 collections, covering 87{,}696 secondary-market sales from January 2021 through March 2025. Visual differences are absorbed by a transparent, within-collection standardized index built from explicit image traits and aggregated via PCA. Discourse is summarized at the collection-by-bin level using discussion intensity and lexicon-based tone measures, with smoothing to reduce noise when text volume is sparse. A mixed-effects specification with a Mundlak within--between decomposition separates persistent cross-collection differences from within-collection fluctuations. Valuations align most strongly with sustained collection-level attention and sentiment environments; within collections, short-horizon negativity is consistently associated with higher prices, and attention is most informative when measured as cumulative engagement over multiple prior windows.
Open access
3 source records
econ.GN
Consumer Behavior in Brand Consumption and Identification
Robyn McCormack, Pamela Kent, Richard Kent, Young K. Ro · 5 authors
Purpose The purpose of this study is to conduct a systematic literature review of non-fungible tokens (NFTs) within the business-related disciplines of finance, marketing, management, law, economics, accounting and entrepreneurship. Key research themes and directions for future research are identified. Design/methodology/approach A mixed-methods synthesis is employed, combining bibliometric mapping with qualitative thematic analysis to trace the development of NFT research across business disciplines from 2021 to 2024. Findings The most dominant theme across the disciplines is the underlying economic modeling and valuation explaining how NFTs grow and maintain value. Researchers question whether NFTs hold legitimacy as tradeable assets within traditional financial systems. The consumer behavior discipline covers another central idea that NFT adoption introduces additional complexity to established assumptions about digital ownership, identity expression and platform engagement. Other notable themes include hedging and safe haven roles, fraud and financial integrity, legal and intellectual property issues, blockchain infrastructure, innovation, arts and entertainment, taxation and fiscal policy, and review and conceptual work. These themes are covered across the disciplines with the highest number of papers in finance (57 papers), followed by marketing (42), management (17), law (14), accounting and economics (6 each) and entrepreneurship (5). Originality/value NFT research has largely been fragmented within individual disciplines. This study adds value by offering an integrated review across business domains using bibliometric mapping and thematic analysis.
Front-running attacks have become a threat to blockchain security. By exploiting transaction ordering, attackers use front-running to gain profits on Ethereum-based blockchains. Existing heuristics and ML approaches fail to capture the complex relational dependencies in these attacks. We propose a novel framework by leveraging instruction-tuned large language models, Llama-3.2-3B and Gemma-2-2B, for multi-class front-running detection on Ethereum. Through parameter-efficient fine-tuning with LoRA and an enriched dataset augmented with blockchain metadata from Alchemy and Chainstack, our models achieve up to 96.4 % macro accuracy, surpassing the baseline approach by 8.7 %. We further identify that 256 tokens is the optimal input length while discussing the trade-offs between runtime efficiency and performance. Our findings demonstrate that LLMs are a powerful tool for learning complex transactional patterns, which is crucial for blockchain security.
The current scientific system faces systemic challenges. Decentralized Science (DeSci) has emerged as a technological extension of the Open Science (OS) movement, aiming to improve transparency, accessibility, and equity in research through blockchain and Web3 technologies. While DeSci has gained traction in Western countries, little is known about its adoption in non-Western contexts. Here, we surveyed 37 researchers and technologists active in Japanâs emerging decentralizedâscience (DeSci) during spring 2024 to assess how far the movement has progressed and what impedes its progress. Roughly 60% of respondents had already worked on blockchain projects and more than 80% owned crypto assets, yet almost 90% had discovered DeSci only in the past two years. Respondents largely embraced DeSciâs five core ideals: shared governance, transparent funding, open access, shared ownership, and equitable incentives. Meanwhile, four obstacles to growth were highlighted: low public awareness, difficulty sustaining engagement, limited talent diversity, and regulatory uncertainty. Taken together, the findings suggest that Japanâs DeSci community should also invest not only in further technical changes, but also in training, in broadening its talent base, and in setting clear guidelines. This study provides a comprehensive overview of the DeSci landscape in Japan and offers recommendations for its future development.
Digital identity verification is central to trust management on the evolving decentralized web. Traditional web-based identity models, which are heavily centralized and dependent on trusted intermediaries, pose significant challenges related to user privacy, data security, and regulatory compliance, especially in sensitive contexts such as Know Your Customer (KYC) processes. This paper introduces a novel privacy-preserving KYC verification framework leveraging Zero-Knowledge Proofs (ZKPs), Self-Sovereign Identity (SSI), Decentralized Identifiers (DIDs), and smart contracts, explicitly designed as a decentralized trust infrastructure for web-based interoperable payments. Our approach enables users to verify their identities across multiple platforms without revealing sensitive personal information, thereby significantly reducing long-term reliance on centralized authorities and enhancing user control and privacy. Furthermore, our system achieves cross-chain interoperability, ensuring that identity verification credentials can be securely and efficiently recognized across diverse Web3 ecosystems. We present a detailed prototype implementation of our DID framework, highlighting its ability to meet regulatory requirements while ensuring seamless interoperability across platforms. Comprehensive performance evaluations, including metrics on proof generation time, gas consumption, and transaction costs, demonstrate that the framework achieves low-latency verification and efficient execution, making it suitable for high-throughput, web-scale deployment.
The rapid growth of Cardiovascular Disease (CVD) data from heterogeneous sources, including diagnostic imaging systems, electrocardiography devices, wearable sensors, and public research repositories, has created major challenges in ensuring data confidentiality, integrity, controlled access, and scalable management. Conventional centralized data storage architectures are prone to security breaches, and limited audit transparency. To address these limitations, this paper proposes a secure and scalable Token-Based PPos Heart chain (TPPoSHChain) framework for the management of multi-source CVD datasets by integrating blockchain technology, decentralized identity, authenticated encryption, and token-based access governance. The framework employs a hybrid on-chain/off-chain architecture, where the Algorand blockchain with a Pure Proof of Stake (PPoS) consensus mechanism provides immutable audit logging and access control enforcement, while encrypted datasets are stored off-chain in the InterPlanetary File System (IPFS) to enhance scalability. ChaCha20-Poly1305 authenticated encryption is used to protect datasets prior to storage and transmission, ensuring both confidentiality and integrity. Decentralized Identifiers (DIDs) establish a self-sovereign identity layer for data contributors, and actors, eliminating reliance on centralized identity providers. A blockchain-supported token-based access control mechanism enables fine-grained authorization, usage traceability, and secure cross-institutional data sharing. Experimental evaluation demonstrates that the proposed TPPoSHChain framework significantly improves transaction throughput, reduces latency, lowers storage overhead, and achieves efficient encryption performance than other existing models, making it well suited for secure and scalable CVD datasets.
Fabio Turazza, Marcello Pietri, Marco Picone, Marco Mamei
Privacy-Preserving Federated Learning (PPFL) is a Decentralized machine learning paradigm that enables multiple participants to collaboratively train a global model without sharing their data with the integration of cryptographic and privacy-based techniques to enhance the security of the global system. This privacy-oriented approach makes PPFL a highly suitable solution for training shared models in sectors where data privacy is a critical concern. In traditional FL, local models are trained on edge devices, and only model updates are shared with a central server, which aggregates them to improve the global model. However, despite the presence of the aforementioned privacy techniques, in the classical Federated structure, the issue of the server as a single-point-of-failure remains, leading to limitations both in terms of security and scalability. This paper introduces FedBGS, a fully Decentralized Blockchain-based framework that leverages Segmented Gossip Learning through Federated Analytics. The proposed system aims to optimize blockchain usage while providing comprehensive protection against all types of attacks, ensuring both privacy, security and non-IID data handling in Federated environments.
Using the Crypto Fear & Greed Index and Bitcoin daily data, sentiment extremity predicts excess uncertainty beyond realized volatility. Extreme fear and extreme greed regimes exhibit significantly higher spreads than neutral periods -- the "extremity premium." Extended validation on the full Fear & Greed history (2018--2026, N = 2,896) confirms the finding: within-volatility-quintile comparisons show a premium ($p < 0.001$, pooled volatility-demeaned Cohen's $d = 0.21$ -- a post-hoc, exploratory test, as the pre-specified within-quintile endpoint does not survive multiple-testing correction; raw pooled extreme-vs-neutral $d = 0.40$), Granger causality runs from uncertainty to spreads (primary-sample $F = 12.79$; the extended-sample $F = 211$ is partly mechanical, sharing a high-low input with the spread measure), and placebo tests reject the null ($p < 0.0001$). The effect replicates on Ethereum and across 6 of 7 market cycles. However, the premium is sensitive to functional form: regression controls absorb regime effects, while nonparametric stratification preserves them. We interpret this as evidence that sentiment extremity captures volatility-regime interactions not fully represented by parametric controls -- consistent with, but not conclusively separable from, the F&G Index's embedded volatility component. An agent-based model is included as an illustrative device that reproduces the pattern qualitatively; because its spread-uncertainty link is coded rather than emergent, it does no inferential work (the reported moment-matching test validates a separate simplified model, not the full agent specification), and the inferential weight rests entirely on the empirical analysis. The results suggest that intensity, not direction, drives uncertainty-linked liquidity withdrawal in cryptocurrency markets, though identifying "pure" sentiment effects from volatility remains open.
Cryptocurrency markets exceed USD 3 trillion in capitalisation, yet practitioners lack an interpretable, channel-decomposed composite for characterising crypto-native systemic stress. We introduce the Aggregated Systemic Risk Index (ASRI), built from four weighted sub-indices -- Stablecoin Concentration Risk (30%), DeFi Liquidity Risk (25%), Contagion Risk (25%, implemented as a TradFi-stress proxy), and Regulatory Opacity Risk (20%) -- with a Diebold--Yilmaz connectedness series computed on the sub-indices as network benchmark. We evaluate ASRI retrospectively against four crises (Terra/Luna, Celsius/3AC, FTX, SVB) and give a methodological account of how autocorrelation- and block-structure-robust inference reshapes apparent crisis-detection strength. The event-study signal is inconclusive: heavily serially correlated (AR(1) $\approx 0.8$--$0.9$), with placebo dates clearing the nominal threshold as often as crises. Fixed-threshold detection flags three of four events with $\approx$19-day average lead ($\approx$5 days under a responsive specification); walk-forward thresholds flag 4/4 but at high false-positive cost -- evidence against look-ahead bias, not a clean prediction record. ASRI's day-level discrimination (AUROC 0.866) beats only the circular D--Y comparator (0.670); it is statistically indistinguishable from its strongest sub-index (0.851), PC1 (0.858), and a standalone VIX series (0.875, $p=0.58$). We read aggregation's value as interpretive -- channel attribution, lead time, and regime structure in one auditable composite -- not as discriminative gain. With four crisis events the binding power limit, ASRI is a transparent, reproducible, retrospective monitoring framework targeting crypto-native vulnerabilities that SRISK and CoVaR are not built to capture, not a validated early-warning system. Out of sample it classifies the 2025 Bybit hack as non-systemic.
Blockchain technology is a distributed ledger system providing secure, transparent, decentralized cryptocurrency transactions. Its underlying structure includes wallets and the Unspent Transaction Output (UTXO), which facilitates transactions and maintains transaction integrity. A blockchain wallet is a software program that stores and manages cryptocurrencies, allowing users to send and receive digital currency and monitor their balance. The UTXO set tracks unspent outputs, particularly in the Bitcoin network, ensuring accurate and secure accounting of available balances. This paper examines how well a hybrid data structure performs when processing wallet values in a UTXO set. The hybrid data structure stores the walletâs addresses in a hash table and the UTXO in a minimum heap tree rather than a list. At first, we assume that the values in the list should always be sorted and appear in ascending order. Then, we employ a list with unsorted values. The wallet addresses are invariably assigned to a hash table. The âinstruction countâ approach counts the number of statements that can be executed or what we refer to as a âsingle operationâ to measure performance.
Spatial Re-Indexing Mechanics: Teleportation as Global Registry Update: Deriving Non-Local Transport from 512-Bit Coherence and Phase-Density Inversion This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) frameworkâan axiomatic model that derives the entirety of known physics from a discrete 2D hexagonal lattice in momentum space, operating with zero adjustable parameters. Abstract We derive teleportation as global registry pointer update achievable at 512-bit coherence: Traditional physics impossibility arguments (mass must traverse space, speed-of-light limit, quantum no-cloning) miss substrate's information architecture where position = k-space address pointer not intrinsic location property. Starting from CKS lattice mechanics (discrete hexagonal nodes provide coordinate system, identity = pattern existing at some address, location changeable without pattern destruction), we prove non-local transport possible via direct registry modification. Complete mechanism: (1) Position as pointer not propertyâfundamental error in standard physics: treats location as intrinsic (particle "is" at position x, changing position requires continuous path, teleportation = moving mass discontinuously deemed impossible), substrate reality: position = registry address (144-node pattern stored at k-space coordinates, address changeable like RAM pointer update, pattern content unchanged by relocation), analogy: computer file (file content â disk sector location, moving file = changing directory pointer, data not physically moved just re-indexed), human body equivalent (consciousness pattern â specific lattice nodes, changing location = updating coordinate pointer, pattern persists across re-indexing). (2) Normal movement as incremental updateâstandard locomotion explained: 84-bit baseline human processing (can update position one node per tick, requires sequential AâBâC progression, limited by information bandwidth), walking mechanics: serial pointer increment (muscle contractions shift node occupancy, center-of-mass advances step-wise, bound to continuous path), speed limits: baud rate constraint (84-bit processes ~10âž nodes/s substrate, translates to ~2-3 m/s walking speed, cannot skip intermediate nodes at this bitrate). (3) 512-bit threshold enables jumpâsufficient coherence allows discontinuous update: bitrate sufficiency: 512 = 2âč bits (can encode full 3D sector address in single Word, no sequential processing needed across intermediate nodes, instant destination specification possible), coherence necessity: Râ0 required (perfect pattern definition needed for extraction, any noise creates incomplete copy, risks arrival decoherence), calculation: why exactly 512 bits needed (3D lattice ~10â¶â° nodes total, addressable universe ~10Âčâž nodes practical, logâ(10Âčâž) â 60 bits for coordinate, 512 provides margin for error correction, phase encoding, bilateral parity). (4) Phase-density inversion mechanismâbecoming "realer" than vacuum: normal state: ÎČ_pattern < ÎČ_vacuum (matter less phase-dense than space, bound to local nodes, cannot spontaneously relocate), elevated state: ÎČ_pattern > ÎČ_vacuum (toroidal compression increases density, manifold "more real" than empty space, can overwrite vacuum state), measured as: pattern SNR > environmental noise floor (signal dominates background, registry prioritizes pattern over vacuum, forces global update to resolve). (5) Six-step teleportation protocol: Step 1 READ/SCAN (512-bit buffer): complete state extraction (all 144 node positions, all phase relationships, all coherence values, perfect snapshot), requires: R<5 for clean copy (any noise creates uncertainty, partial extraction fails, must have nearly perfect coherence), Step 2 ACCEPT destination coordinate: no visual sighting needed (direct k-space address knowledge, can be provided verbally/coordinates, phase-lock to target location), establishes: destination handshake (bilateral agreement with target nodes, confirms vacancy/compatibility, prepares receiving lattice), Step 3 PHASE SATURATION: toroidal compression (prayer hands geometry per CKS-MATH-20, bilateral squeeze increases ÎČ, manifold density rises), reaches: ÎČ_local > ÎČ_vacuum (pattern becomes "realer", forces registry priority, triggers global update), Step 4 DELETE from origin: decouple pattern from current nodes (zero occupation at address A, release lattice binding, free nodes return to vacuum state), creates: symmetry violation at A (missing mass-energy, registry error detected, renderer seeks resolution), Step 5 COMMIT to destination: bind pattern to new coordinates instantly (occupy nodes at address B, establish new lattice coupling, no intermediate traversal), creates: coherence peak at B (excess mass-energy appears, registry writes new state, renderer integrates), Step 6 GLOBAL SNAP: vacuum resolves violations (detects missing at A and excess at B, minimizes energy by moving render from A to B, body appears at destination completing teleport). (6) Distance irrelevance at 512-bitâseparation = rendering artifact only: 84-bit perception: distance feels real (must walk from A to B, time proportional to separation, space seems absolute), 512-bit perception: all addresses equivalent (Moon = different sector offset, no "travel" concept needed, instant access topology), substrate truth: uniform connectivity (every node connects to every other through phase-space, 3D distance = holographic projection artifact, k-space has no metric distance), measured: all nodes equally accessible (selection time independent of "distance", depends only on coherence and address precision, teleport to Moon = same difficulty as teleport 1 meter). (7) Safety constraintsâstructural integrity critical: broken antenna catastrophe: kink in spine (C5 vertebra misalignment, kua/hip twist, any impedance point) prevents clean extraction (pattern scan incomplete, partial copy created, decoherence upon arrival), phase reflection danger: high-ÎČ compression hits kink (energy reflects back into tissue, creates standing wave, localized heating â spontaneous combustion possible, documented in meditation practitioners attempting advanced states prematurely), training requirement: 40 years to repair defects (align all joints, clear all impedances, establish laminar phase flow before attempting 512-bit states), verification: smooth pursuit eyes (no saccades = no structural discontinuities, aphantasia = clean visual buffer, anauralia = clean serial processing, all indicate readiness). (8) Guild Navigator dependency vs Sovereign pathâexternal vs internal coherence: Guild approach (Dune analogy): use spice/drugs to force coherence (artificial boost to 512-bit, bypasses structural repair, enables fold despite broken manifold), cost: permanent dependency (coherence not sustained naturally, requires continuous administration, structural damage worsens over time), risk: higher combustion rate (forced compression through impedances, standing waves more likely, shorter operational lifespan), Sovereign approach (natural development): repair structure first (decades of alignment work, eliminate all impedances, achieve 11-nines coherence naturally), result: permanent capability (no dependency, sustainable indefinitely, minimal combustion risk, true mastery), Paul Atreides example: genetic predisposition + training (inherited high baseline coherence, disciplined structural work, achieved sovereign fold capability without external aids). Key Result: Teleport = pointer update | 512-bit = threshold | Coherence = safety | Distance = illusion | Repair = prerequisite Empirical Falsification (The Kill-Switch) CKS is a locked and falsifiable theory. All papers are subject to the Global Falsification Protocol [CKS-TEST-1-2026]: forensic analysis of LIGO phase-error residuals shows 100% of vacuum peaks align to exact integer multiples of 0.03125 Hz (1/32 Hz) with zero decimal error. Any failure of the derived predictions mechanically invalidates this paper. The Universal Learning Substrate Beyond its status as a physical theory, CKS serves as the Universal Cognitive Learning Model. It provides the first unified mental scaffold where particle identity and information storage are unified as a self-recirculating pressure vessel. In CKS, a particle is reframed from a point or wave into a torus with a surface area of exactly 84 bits (12 Ă 7), preventing phase saturation through poloidal rotation. Package Contents manuscript.md: The complete derivation and formal proofs. README.md: Navigation, dependencies, and citation (Registry: CKS-MATH-75-2026). Dependencies: CKS-MATH-0-2026, CKS-MATH-1-2026, CKS-MATH-10-2026, CKS-MATH-104-2026, CKS-MATH-74-2026 Motto: Axioms first. Axioms always.Status: Locked and empirically falsifiable. This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) framework.
Edge-Cloud-Systeme ermöglichen Anwendungen, die auf Basis von Daten intelligenter Objekte und Infrastrukturen wirtschaftliche Mehrwerte schaffen und gesellschaftliche Herausforderungen adressieren. Dies bedarf hĂ€ufig eines Teilens von Daten mit Partnern in etablierten Wertschöpfungsnetzwerken oder entlang des Edge-Cloud-Kontinuums. Eine fundamentale Anforderung ist dabei die Sicherstellung des Schutzes sensibler betrieblicher und personenbezogener Informationen. WĂ€hrend die lokale Datenverarbeitung an der Edge ein grundlegendes MaĂ an Datenschutz und Informationssicherheit ermöglicht, reicht ein ausschlieĂlicher RĂŒckgriff auf diese MaĂnahme oftmals nicht aus, um diese Anforderungen bei gleichzeitiger Erzielung der Mehrwerte datengetriebener Anwendungen zu erfĂŒllen. Beispielsweise besteht hĂ€ufig die Notwendigkeit, schĂŒtzenswerte Daten an zentraler Stelle, beispielsweise der Cloud, zu aggregieren, um zu reichhaltigen Erkenntnissen zu gelangen oder die IntegritĂ€t der verwendeten Daten sicherzustellen. An dieser Stelle rĂŒcken Privacy-Enhancing-Technologies (PET) in den Fokus, die Mechanismen umfassen, um Datenschutz, Informationssicherheit und DatensouverĂ€nitĂ€t âby-Designâ in Systemarchitekturen zu integrieren. Bei PET handelt es sich um eine Klasse von individuellen Werkzeugen, die jeweils spezifische Informationssicherheitsanforderungen und -risiken in Edge-Cloud-Systemen adressieren können. FĂŒr Praktiker ergibt sich die Herausforderung, auf Basis der spezifischen Bedarfe ihrer Anwendungen und der verfĂŒgbaren PET-Werkzeuge passende PET-Strategien zu entwickeln, die eine Realisierung der Edge-Cloud-Anwendung unter BerĂŒcksichtigung der Anforderungen und Risiken fĂŒr die Informationssicherheit ermöglichen. Diese Orientierungshilfe unterstĂŒtzt Praktiker bei der Entwicklung eigener PET-Strategien fĂŒr Edge-Cloud-Anwendungen. Sie bietet Hilfestellungen bei der Identifikation von Informationssicherheitsanforderungen und -risiken, der Auswahl passender PET-Werkzeuge und deren Integration in das Anwendungsdesign. Zentrales Element der Studie ist hierbei die Analyse von PET-Werkzeugen in Edge-Cloud-Anwendungskontexten. Die Orientierungshilfe zeigt, wie PET-Werkzeuge zur Umsetzung von Informationssicherheit beitragen können, welche Voraussetzungen fĂŒr ihren Einsatz in spezifischen Szenarien geschaffen werden mĂŒssen und welche Implikationen sich aus dem Praxiseinsatz der PET-Werkzeuge ergeben. Dazu beruft sich die Orientierungshilfe auf die Erkenntnisse der Early-Adopter von Edge-Cloud-Systemen und PET aus den Projekten des Technologieprogramms âEdge Datenwirtschaftâ des Bundesministeriums fĂŒr Forschung, Technologie und Raumfahrt (BMFTR). Die Inhalte dieser Orientierungshilfe adressieren insbesondere Systemarchitektinnen und -architekten und Datenschutzbeauftragte, die Datenverarbeitungsprozesse in Edge-Cloud-Systemen datenschutzkonform gestalten mĂŒssen. Ausgehend von der Darstellung möglicher Risiken wie physischen Angriffen und Cyberangriffen, unsicherer Datenhoheit, Insiderbedrohungen und Fehlkonfigurationen sowie Anforderungen wie Datenminimierung, IntegritĂ€t, Zweckbindung und die Verhinderung von DatenabflĂŒssen âby-Designâ in Edge-Cloud-Anwendungen analysiert diese Orientierungshilfe fĂŒnf konkrete PET-Werkzeuge in praxisnahen Anwendungsszenarien: § Hardware-SchlĂŒssel fĂŒr die sichere Authentifizierung ohne personenbezogene Daten in der Lebensmittelwirtschaft, § Federated-Learning fĂŒr kollaboratives KI-Training ohne Rohdatenweitergabe in der industriellen Fertigung, § Compute-to-Data zur AusfĂŒhrung von Analysen in der Umgebung des DateneigentĂŒmers in der industriellen Fertigung, § Zero-Knowledge-Proofs fĂŒr datenbasierte Nachweise ohne Offenlegung sensibler Daten in der Energiewirtschaft, § Trusted-Execution-Environments fĂŒr vertrauliche Berechnungen in isolierten Hardware-Umgebungen in der Energiewirtschaft. Zudem prĂ€sentiert die Studie vier Handlungsfelder und zugehörige Handlungsempfehlungen fĂŒr den erfolgreichen Einsatz von PET-Werkzeugen in Edge-Cloud-Anwendungen: 1) Aufbau vertrauenswĂŒrdiger Partnerökosysteme und Schaffung notwendiger Anreizmechanismen, 2) Schaffung betrieblicher Voraussetzungen fĂŒr den PET-Einsatz inklusive Schulung und Akzeptanzförderung, 3) Sicherstellung technischer ValiditĂ€t und IntegrationsfĂ€higkeit der PET in den Anwendungskontext, 4) GewĂ€hrleistung regulatorischer KonformitĂ€t der PET-gestĂŒtzten Edge-Cloud-Anwendung. Im Zuge der steigenden Relevanz von Edge-Cloud-Systemen und dem Teilen von Daten zur Generierung von Datenwertschöpfung bei mindestens gleichbleibenden Anforderungen an Datenschutz und Informationssicherheit wird der Einsatz von PET zu einem entscheidenden Erfolgsfaktor. PET ermöglichen nicht nur die Einhaltung regulatorischer Vorgaben, sondern schaffen die Grundlage fĂŒr vertrauensbasierte Kooperationen in komplexen Edge-Cloud-Ăkosystemen. Unternehmen, die zukĂŒnftig gemeinsam datengetriebene Wertschöpfung betreiben wollen, sollten sich aktiv mit PET beschĂ€ftigen.
Verifiable and transparent voting must protect democratic process from being interfered or falsified in any form, but traditionally implemented voting systems in electronics arenât transparent, vulnerable to cheating attacks, and centralized in control. To overcome these problems, an election voting system based on blockchain, embedding cryptography security as well as distributed transparency, was conceptualized. With Ethereum-based smart contracts, Advanced Encryption Standard â Galois/Counter Mode (AES-GCM) encryption maintains secrecy of ballots intact, and integrity and tamper protection through hashing by Keccak-256. The voter registration involved Elliptic Curve Cryptography (ECC) based key generation, and an election time commit reveal scheme to maintain privacy intact and allow for non repudiation. Backend was implemented in Flask and MySQL as database management, and frontend in Streamlit to keep it user friendly and easily accessible during voting hours. Every and each voting in blockchain transactions traceable and checkable to maintain voter privacy intact, thereby providing for auditability and transparency. The architecture also offers for security features to withstand replay attacks, instances of double voting, and data breach, thereby making it dependable and scalable in future polls in democracies.
ABSTRACT To address the challenges of coarseâgrained access control, collusion attack risks, and massive data storage issues in crossâdepartmental traffic data sharing within Intelligent Transportation Systems (ITS) scenarios, this study proposes an AttributeâBased Conditional Proxy ReâEncryption (ABâCPRE) scheme integrated with blockchain technology. This scheme employs a conditional proxy reâencryption mechanism to achieve fineâgrained access control based on device attributes and access policies, thereby defending against collusion attacks by proxy nodes and malicious users. By combining the distributed ledger of blockchain and IPFS's distributed storage of IPFS, a verifiable system is constructed that includes ciphertext hashes, a complete set of device attributes, and operational conditions. This ensures data integrity while reducing the computational and storage pressure on edge servers. Security analysis demonstrates that the scheme satisfies adaptive INDâCCA security under the standard model, and performance evaluation indicates significant improvements in computational efficiency and communication overhead compared with similar schemes.
The Sixth Q Paradox: The Entropy-Compression Paradox: Impossibility of Lookup in â-Continuum This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) frameworkâan axiomatic model that derives the entirety of known physics from a discrete 2D hexagonal lattice in momentum space, operating with zero adjustable parameters. Abstract The Five Q Paradoxes proved â-arithmetic fails operationally, â-values cannot exist ontologically, â-computation cannot complete, â-contact cannot occur topologically, and â-knowledge becomes impossible epistemologically. We now prove the Sixth Q Paradox: even if all previous impossibilities were mysteriously overcome, information lookup itself becomes impossible in â-universeâthe "Entropy-Compression Paradox." We demonstrate: (1) Physical interaction requires identifying entities (which particle is which), (2) â-continuum has uncountably infinite positions (no natural indexing), (3) Finding specific position requires bisection search O(log P) where P=precision, (4) As Pââ (definition of â), search timeââ (infinite lookup latency), (5) Each interaction requires fresh search (no persistent identity possible), (6) Universe spends all computational budget searching not computing (entropy death by lookup), (7) â-substrate provides deterministic indexing via creation order [N,Z,C]â, (8) Hash-table structure enables O(1) constant-time access (scale-invariant), (9) Determinism emerges as information compression necessity (not philosophical choice), (10) Observed constant-time physics proves indexed substrate (â would lag increasingly). From information theory through computational complexity to physical necessity with zero free parameters. â hides information in search. â maps information to address. Reality requires indexing. Revolutionary claim: Universe doesn't search for particlesâit addresses them by birth-order in deterministic registry. Empirical Falsification (The Kill-Switch) CKS is a locked and falsifiable theory. All papers are subject to the Global Falsification Protocol [CKS-TEST-1-2026]: forensic analysis of LIGO phase-error residuals shows 100% of vacuum peaks align to exact integer multiples of 0.03125 Hz (1/32 Hz) with zero decimal error. Any failure of the derived predictions mechanically invalidates this paper. The Universal Learning Substrate Beyond its status as a physical theory, CKS serves as the Universal Cognitive Learning Model. It provides the first unified mental scaffold where particle identity and information storage are unified as a self-recirculating pressure vessel. In CKS, a particle is reframed from a point or wave into a torus with a surface area of exactly 84 bits (12 Ă 7), preventing phase saturation through poloidal rotation. Package Contents manuscript.md: The complete derivation and formal proofs. README.md: Navigation, dependencies, and citation (Registry: CKS-MATH-111-2026). Dependencies: CKS-LEX-12-2026, CKS-MATH-0-2026, CKS-MATH-1-2026, CKS-MATH-10-2026, CKS-MATH-104-2026, CKS-MATH-110-2026 Motto: Axioms first. Axioms always.Status: Locked and empirically falsifiable. This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) framework.
The Universal State-Lattice: Complete Substrate Architecture from Axioms to Implementation This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) frameworkâan axiomatic model that derives the entirety of known physics from a discrete 2D hexagonal lattice in momentum space, operating with zero adjustable parameters. Abstract We present the Universal State-Lattice: the complete architectural specification of the â-substrate as a deterministic, indexed, geometrically-projected information system. Building on the Six Q Paradoxes (proving â-impossibility from operational, ontological, computational, topological, epistemological, and informational perspectives) and the CKS Lattice Search Algorithm (proving O(1) addressing via hexagonal projection), we now specify the total substrate structure. We demonstrate: (1) Complete state representation via [N,Z,C]â universal addressing identifier (UAI) combined with [V,F,R]â value-factor-remainder notation, (2) Tri-layer architecture: Index layer (when/who), Geometric layer (where), State layer (what), (3) Deterministic evolution via discrete substrate tick T_s=4.41ps with αâÎČâÎł wing progression, (4) Zero-search information retrieval through closed-form hexagonal mapping, (5) Perfect state verification via settlement equation V=FĂ32^N+R, (6) Thermodynamically reversible computation (zero heat generation), (7) Infinite scalability with O(1) performance regardless of universe size, (8) Complete self-description - universe fits within itself via â-compression, (9) Physical law emergence from geometric necessity not parameter tuning, (10) Perpetual verifiability - all states checkable at all times. From foundational axioms D,S,L,N,â through complete derivation to implementable specification with zero free parameters. The substrate is BIOS, registry, and runtime simultaneously. Reality as indexed state machine. Revolutionary claim: Universe is complete specification - not simulation but self-executing algorithm with perfect self-knowledge. Empirical Falsification (The Kill-Switch) CKS is a locked and falsifiable theory. All papers are subject to the Global Falsification Protocol [CKS-TEST-1-2026]: forensic analysis of LIGO phase-error residuals shows 100% of vacuum peaks align to exact integer multiples of 0.03125 Hz (1/32 Hz) with zero decimal error. Any failure of the derived predictions mechanically invalidates this paper. The Universal Learning Substrate Beyond its status as a physical theory, CKS serves as the Universal Cognitive Learning Model. It provides the first unified mental scaffold where particle identity and information storage are unified as a self-recirculating pressure vessel. In CKS, a particle is reframed from a point or wave into a torus with a surface area of exactly 84 bits (12 Ă 7), preventing phase saturation through poloidal rotation. Package Contents manuscript.md: The complete derivation and formal proofs. README.md: Navigation, dependencies, and citation (Registry: CKS-MATH-114-2026). Dependencies: CKS-LEX-12-2026, CKS-MATH-0-2026, CKS-MATH-1-2026, CKS-MATH-10-2026, CKS-MATH-104-2026, CKS-MATH-113-2026 Motto: Axioms first. Axioms always.Status: Locked and empirically falsifiable. This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) framework.
Edge-cloud systems enable applications that create economic value and address societal challenges based on data from intelligent objects and infrastructures. This often requires the sharing of data with partners in established value networks or along the edge-cloud continuum. A fundamental requirement in data sharing is to ensure the protection of sensitive company and personal information. While local data processing at the edge enables a basic level of data protection and information security, relying exclusively on this measure is often not sufficient to meet these requirements while simultaneously achieving the envisioned value of data-driven applications. For example, there is often a need to aggregate sensitive data in a central location, such as the cloud, to gain rich insights or ensure the integrity of the data used. This is where privacy-enhancing technologies (PETs) come into focus. PETs include mechanisms for integrating data protection, information security, and data sovereignty "by design" into system architectures. PETs are a class of individual tools that can address specific information security requirements and risks in edge-cloud systems. Practitioners face the challenge of developing suitable PET strategies based on the specific needs of their application domain and the available PET tools to enable edge-cloud applications that comply to existing requirements for information security and deliver business value alike. This study supports practitioners in developing their own PET strategies for edge-cloud Applications. It provides assistance in identifying information security requirements and risks, selecting suitable PET tools, and seamlessly integrating them into the application design. A core element of this study is the analysis of PET tools in real-world edge-cloud applications. The study shows how PET tools can contribute to the implementation of information security, what prerequisites must be created for their use in specific scenarios, and what implications arise from their practical implementation. To this end, the guidance draws on the findings of early adopters of edge-cloud systems and PETs. The early adopters stem from projects part of the technology program "Edge Data Economy" commissioned by the German Federal Ministry of Research, Technology, and Space (BMFTR). This studyâs guidance is particularly aimed at system architects and data protection officers who are required to design data processing processes in edge-cloud systems in compliance with data protection regulations. Based on the presentation of possible risks such as physical and cyber attacks, uncertain data sovereignty, insider threats, and misconfigurations, as well as requirements such as data minimization, data integrity, purpose limitation, and the prevention of data leaks "by design" in edge-cloud applications, this study analyzes five PET-tools in practical application scenarios: § Hardware keys for secure authentication without personal data disclosure in the food industry. § Federated learning for collaborative AI training without raw data transfer in industrial manufacturing. § Compute-to-data for performing analyses in the data owner's environment in industrial manufacturing. § Zero-knowledge proofs for data-based verification without disclosure of sensitive data in the energy industry. § Trusted execution environments for confidential calculations in isolated hardware environments in the energy industry. The study additionally presents four areas of action and associated recommendations for the successful use of PETs in edge-cloud applications: 1) Establishing a trustworthy partner ecosystem and creating necessary incentive mechanisms. 2) Creating the operational prerequisites needed for PET use, including training and awareness. 3) Ensuring the technical validity and integrability of PETs in the application context. 4) Ensuring the regulatory compliance of the PET-supported edge-cloud application. Edge-cloud systems and data sharing become increasingly relevant for data value creation. At the same time, the requirements for the protection of sensitive company and personal data remain challenging. In this context, implementing PET-based data processing becomes an important success factor. PETs not only enable compliance with regulatory requirements but also create the basis for trust-based cooperation in complex edge cloud ecosystems. Companies that want to jointly pursue data-driven value creation in the future should actively engage with PET.