The high-level integration of generative artificial intelligence (AI) in edge computing systems has raised the question of the integrity and reliability of deploying Model-as-a-Service. Edge servers are not required to follow the so-called generative model to minimize computational cost, whereas users and service providers want validation mechanisms that do not compromise proprietary model information. To address this challenge, this study proposes a cooperative unmanned aerial vehicle (UAV)-swarm-enabled zero-knowledge verification framework for secure, privacy-preserving verification of edge-based generative artificial intelligence inference. The proposed framework involves edge servers producing an interactive cryptographic zero-knowledge proof to verify the execution of generative AI, and UAV swarms that fly freely to confirm verification operations, subject to mobility and energy constraints. The age of verification metric is proposed to trust verification information, jointly reflecting the unverified server reliability and verification freshness, and to provide dynamic priority to risky edge servers. To effectively plan the behaviour of a UAV swarm, a trust-based multi-agent reinforcement learning approach is developed that enables decentralized decision-making while training is centralized. Extensive simulation results show that the proposed framework significantly improves the state-of-the-art baseline schemes in verification timeliness, malicious server detection delay, energy efficiency, and scalability. The findings validate that integrating cooperative UAV swarms, trust-aware verification, and multi-agent learning is an efficient approach to providing reliable generative AI services in dynamic edge computing environments.
Elizabeth V. K. Ledger, Niamh E. Horgan, Denis Lynch, Lorraine M. Bateman · 5 authors
Abstract Biofilm formation and antibiotic tolerance are major contributors to the persistence of Staphylococcus aureus infections, yet how the host environment affects these phenotypes remains poorly understood. Here, we show that incubation in human serum primes S. aureus to form robust biofilms and tolerate vancomycin and daptomycin, last resort antibiotics for the treatment of antibiotic-resistant staphylococcal infections. Mechanistically, we demonstrate that the staphylococcal Geh lipase is essential for serum-induced biofilm formation by liberating glycerol from host lipids, which is then used to promote increased synthesis of D-alanylated wall teichoic acids, driving biofilm development. Inhibition of the Geh lipase or wall teichoic acid synthesis markedly reduces biofilm formation and restores antibiotic susceptibility, highlighting clinically achievable strategies to inhibit host-induced biofilm formation and prevent the associated antibiotic tolerance. Together, our findings reveal a host-driven mechanism of biofilm-associated antibiotic tolerance in S. aureus and provide rational targets for therapeutic intervention.
This study examines whether green finance promotes green development across Chinese prefecture-level cities from 2005 to 2019. We find a positive association between green finance and green development using panel regressions with city and year fixed effects. This result remains robust after accounting for potential endogeneity and implementing a series of robustness checks. Further heterogeneity analysis shows that this positive effect is stronger in regions characterized by high fiscal capacity and within the Yangtze River Economic Belt. Additionally, green finance drives regional green development by promoting green innovation. Environmental decentralization moderates the relationship, with a stronger positive effect at higher levels of decentralization. This study offers empirical evidence regarding how green finance shapes green development outcomes.
Zain Imran, Sana Humayun, Muhammad Shahzaib Saleem, Naveed Ul Hassan
In many electricity markets, declining feed-in tariffs have made grid export increasingly unattractive for residential solar prosumers, while retail electricity prices remain high. Peer-to-peer (P2P) energy trading offers a direct alternative, but it requires a dedicated infrastructure layer for real-time bilateral matching, automated settlement, and tamper-proof transaction records, for which blockchain is widely proposed. Deploying such infrastructure must be economically justified by the community's actual trading potential. A critical and underexplored question is whether trading potential survives as communities become prosumer-heavy, since under fixed role assignment all households eventually end up on the supply side with no buyers remaining. This paper addresses these gaps by proposing the Energy Trading Potential Index (ETPI), a normalized data-driven metric that quantifies the structural impact of flexible role switching on community-level trading potential, where prosumers dynamically join the buyer side whenever they are in energy deficit. The P2P market is modeled as a generalized bipartite graph and pairwise interaction scores aggregated over trading rounds compute the ETPI in [0,1]. Simulation results using the PRECON residential dataset and NREL PVWatts solar profiles show that for the (1:9) prosumer-heavy mix, the flexible policy achieves an ETPI of 0.61 versus only 0.15 under the static policy, a fourfold improvement that the static model entirely misses. The ETPI framework serves as a lifecycle decision-support tool for evaluating and monitoring P2P energy trading infrastructure.
Collective dynamics in financial markets can emerge through synchronized movements of large groups of assets. Motivated by analogies with interacting many-body systems, we introduce a spin-lattice representation for analyzing collective states in cryptocurrency markets. In this framework, assets are encoded as binary spin variables according to the sign of their returns, while correlations between assets determine effective interaction strengths. A correlation-based breadth-first search (CBFS) procedure embeds 169 cryptocurrencies into a $13 \times 13$ lattice, enabling the construction of an Ising-like Hamiltonian describing the market configuration, which we call the \emph{Market Crystal}. Macroscopic observables such as magnetization and energy provide a statistical-mechanical characterization of collective market states. The resulting phase-space structure highlights regimes of strong alignment and fragmentation among assets, with an energy--magnetization pattern suggestive of predominantly ferromagnetic interactions. This framework offers a statistical-mechanical viewpoint for studying collective behavior in financial systems.
Constantine Doumanidis, Anya Kalogerakos, Maria Apostolaki
BGP hijacking enables impersonation attacks in which adversaries divert traffic at the prefix level and serve malicious content to unsuspecting clients. Detecting such attacks has traditionally been the responsibility of network operators, leaving end hosts exposed for hours. We argue that end hosts can detect prefix-level impersonation independently, exploiting a fundamental asymmetry: a BGP hijack diverts traffic for an entire IP prefix, but impersonating every co-hosted service within that prefix is prohibitively difficult at scale, especially if each service is authenticated by a different Certificate Authority. We propose HOWLR, a tool that operationalizes this insight by using co-hosted, TLS-authenticated services as witnesses: if a client can no longer authenticate them, it has evidence of an ongoing attack. This work evaluates the feasibility of this method by quantifying the existence and diversity of witnesses in the wild. We show that HOWLR can protect 89% of Tor relay prefixes, and 75% of Bitcoin pool gateway prefixes.
Academic research indicates an urgent need for safe, tamper-proof storage of sensitive medical information due to the rapid digitalization of healthcare data. Traditional systems are susceptible to both internal and external assaults because of their dependence on centralized servers. SEC-HEALTH implements a system for the secure storage of electronic health records (EHRs) by combining the immutable, distributed ledger technology of blockchain with the InterPlanetary File System (IPFS).This system use Solidity smart contracts to archive patient data and transaction records on the Ethereum blockchain. Comprehensive EHR files are preserved on IPFS and may be accessed via their blockchain hash addresses. The architecture guarantees data integrity, transparency, and safe access independent of trusted third parties.User modules include appointment scheduling, prescription management, patient and physician authentication, and platform registration. The graphics illustrate a fully operational web interface created in Python, implemented smart contracts, and the integration of blockchain with IPFS. The approach is resilient and decentralized, providing an alternative to traditional centralized health data management systems.
To PM Italy. PM Indonesia PM Japan Real PM Pakistan, Imran Khan Only. DATE: 20 June, 2026. DOI: 10.5281/zenodo.20774904 Subject: Compensation Prize for failure of my Forecast for Eruption, Earthquake 8 June to 20 June. And As Nanga Parbat is not happened on my calculated Time so 24 June Yellow Stone eruption is not possible by mechanism of 20 june Nanga Parbat Hammer Effect. Respectful Prime Minister, My science is no doubt World’s most advanced science with deterministic science, predictions in field of science and universal Geology. I predicted Sun calm is temporary it will be much more active after a week, and sun after a week erupted G5 Storm. I calculated ocean currents and did simulation of ocean currents on mobile phone and free open AI with N-K Sciences and predicted Super El Nino from Mid of 2026, published time stamped in March 19, 2026. Which were copied by WMO and removed my name and my science name and published in April 2026. When I requested to atleast cite my name or my science name, they given credit to a dead man. Then I wrote strict letter with evidances to Secretary General UN. Since 2022 I am fighting against Corruption Entire World know that especially Intel agencies. Government of Pakistan tried to kill me 2 times and tortured me for months. But still I am fighting against Oppression and corruption from it’s Roots Pakistan Army Mafia and Zionists Mafia. They are working jointly, they are same. I Published 580+ publications from my first book in Feb 6, 2025. Not for worldly benefits. https://doi.org/10.5281/zenodo.20473774 I achieved which was impossible for mainstream science. In many fields of sciences, correctly calculate d global tides by first try with any past Data of tides, in completely N-K Sciences framework. Achieved 100% accuracy. Warned on 17 April, 2026 to entire World that According to Parker Solar Probe data High volume proton Flux Storm coming which reach on earth 21 April, 2026. While NASA warned G1,G2 storm completely normal. While I clearly warned increased semiconductors clocking speed due to Noor Value increase during storm on Earth, fission Reactors will face problems, GPS measurement errors 5 to 15m, 15m error is measured by me too during gusts of storm. Hundreds of flights cancelled worldwide and hundreds delayed, civil aviation industry said ghost in system. That was not ghost, but their science is built in 2D era, for example E=MC² is 2 dimensional applied on 3 dimensional forcefully even it gives 8 to 16% wrong results, and didn’t explain what is C, what is Mass, what is energy actually. Nicola Tesla Said it’s a mathematical hack. Yes it was. But I given world accurate Energy Equation and derived C and defined C, defined Mass, defined Energy, defined Gravity. Solved all planets from electron to cosmic web under one Law, learned From analyzing Bawling Action of Wasim Akram and Waqar Younus. Well, I tried to predict earthquakes and eruptions with exact time window. But I cannot know future or cannot change Will of Allah Almighty. Therefore as my Moral values, I decided to reward Countries where my prediction failed. Italy, Japan, USA, Indonesia. As You may Know I don’t have any bank balance, any property on earth. Anything doing a low pay government job, house given by government, actually not given by government, government tried to harass me with all efforts to stop me to take this house which was empty because of its structure built in 1960’s was collapsing and no one wants to live here still they made lot of hurdles, then I went to court and on court orders I got house in which I am living. Nor I have computer nor any other expensive thing, Shukar Alhamdulillah. Free from deceptions of the world. While I am most rich man on earth by knowledge and Inventions. So I can reward from my inventions that can give your countries revenue and Profit in billions of dollars annually. Especially Italy and Japan can get extraordinary benefits in automotive and Aviation industries. Without need of Rare Earth Minerals. My invention N-K Motor with license for commercial use free for a year. 459 Malik Muhammad Usman N‑K MOTOR — THE INVENTION THAT CHANGES EVERYTHING: How a Single Electric Motor Can Transform Transportation, Energy, Military, and Civilization — With Complete Technical Specifications, Application Analysis, Environmental Impact Assessment, and Global Transformation Roadmap — Released as Sadaqa Jariyah (Perpetual Charity) — Patent Application No. 57302185 (IPO Pakistan, 19 August 2025) — Withdrawn and Released to Public Domain May 3, 2026 https://doi.org/10.5281/zenodo.20001878 458 Malik Muhammad Usman THE PATENT SYSTEM IS HARAM IN ISLAM — Complete Islamic Ruling Based on Quran, Hadith, Sunnah, the Name of Allah Al-Aleem, and the Four Divine Axioms — With Official Declaration Withdrawing Patent Application No. 57302185 (IPO Pakistan, 19 August 2025)’and Releasing All Inventions as Sadaqa Jariyah (Perpetual Charity) for All Humanity May 3, 2026 https://doi.org/10.5281/zenodo.20000580 457 Malik Muhammad Usman COMPLETE PATENT DISCLOSURE — Multi-Stage Radial Flux and Multi-Stage Axial Flux Electromagnetic Motors with Integrated Cooling/Heating System and AI Control — Patent Application No. 57302185 (IPO Pakistan, 19 August 2025) — Now Released to Public Domain as Sadaqa Jariyah May 3, 2026 https://doi.org/10.5281/zenodo.20000261 If You Accept my Reward than officially Accept my Reward and Use it free. Even license Renewal fee is also zero. I am not Allowed to charge money for my knowledge which is Given to me by Quran By Allah Almighty Himself in past 26 years daily. Please Accept my Reward And grow your Industries rare earth minerals Free. It’s not only a motor, it is full setup my invented controller Chip design with ~39000 Transistors on 120 nm architecture suitable for high energy applications a 75KW Chip. Optional, N-K alloys 4X stronger than strongest alloys developed by USA, Russia, China ever. Upon request. Italian PM, If you want Fission Reactors it’s your choice. I am giving you LTMFC power houses, which are not only easy and faster to build but gives lowest cost electricity, + Milk + Beef and dozens of Dairy Products. And energy enough to fullfil your country requirements, You can add 20000MW to 50000MW in less than 6 months, while fission Reactors can give you around 1000 MW in minimum 6 years with billions of dollars investment. Build both as you like. Same offer to Japan, and entire World. Additional Gift: Usman Malik, M. (2026, June 20). TIME, CONSCIOUSNESS, AND THE UNIVERSAL 0.01 Hz KUN RHYTHM: The Inverse Relationship Between Consciousness and Time Perception — From Infancy to Old Age, from Quranic Revelation to N-K Mathematical Proof. Zenodo. https://doi.org/10.5281/zenodo.20768016 Malik Muhammad Usman Servant, Student and Soldier of Allah Almighty and Prophet Muhammad PBUH. City of Saints, Multan, Pakistan. +923336130947 muhammad.usman08@gmail.com muhammadusmanmalik@hotmail.com
Local AI inference for browser tasks—including vision-language processing, speech recognition, and neural translation—requires significant computational resources that may exceed the capabilities of low-power devices such as smartphones, tablets, and older laptops. This paper presents the design of a distributed GPU compute sharing system for the Kathon cryptographic browser that enables peer-to-peer AI inference acceleration across trusted devices using libp2p networking. The system partitions neural network inference workloads across participating peers using tensor parallelism, with encrypted communication channels, verifiable computation proofs, and incentive mechanisms based on the .aioss cryptographic ledger. We address key technical challenges: heterogeneous device discovery with capability advertisement, dynamic workload partitioning for variable peer availability, encrypted inference that prevents input reconstruction, and fault tolerance through redundant computation. Simulated benchmarks across a 16-peer testbed demonstrate 3.8x speedup for Whisper transcription and 4.2x speedup for Qwen 2.5 VL inference on low-power client devices. A security analysis confirms that encrypted inference provides semantic security against honest-but-curious peers. The system enables Kathon to deliver AI features on devices that lack the local compute capacity for real-time inference. Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores browser engine, privacy in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper presents a comprehensive analysis of privacy-preserving authentication mechanisms within the MF+SO sovereign identity vault, focusing on the protocol's implementation of zero-knowledge identity proofs, anonymous credentials, blind signatures, and data minimization techniques. Traditional authentication protocols require the user to disclose their identity to each service provider, creating a centralized record of the user's activities across services. MF+SO's privacy architecture inverts this model: users authenticate to services without revealing their MF+SO identifier, using cryptographic techniques that provide the verifier with assurance of the user's authorization status while revealing minimal information about the user's identity. We examine three canonical privacy-preserving authentication mechanisms implemented in MF+SO: (1) zero-knowledge identity proofs using the Groth16 zk-SNARK construction, enabling users to prove possession of valid credentials without revealing which credentials they hold; (2) anonymous credentials based on the Camenisch-Lysyanskaya (CL) signature scheme, providing multi-show unlinkability where the same credential can be presented multiple times without the presentations being correlatable; and (3) blind signature-based tokens for email cloaking, where the MF+SO service issues a blind signature on a user's email address for use with third-party services without learning the email address. The paper provides a formal security analysis of the unlinkability guarantees of each mechanism, proving that under the decisional Diffie-Hellman (DDH) assumption, CL-based anonymous credential presentations are computationally unlinkable. We present benchmark data for each mechanism on mobile platforms: CL credential issuance (120 ms), CL credential presentation (85 ms), blind RSA signature issuance (45 ms), and zk-SNARK-based verification (2.3 ms). The implementation details include the MF+SO privacy layer architecture, the credential ... Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper presents a comprehensive analysis of the World Wide Web Consortium (W3C) decentralized identity standards and their relationship to the MF+SO sovereign identity vault architecture. We examine the W3C Decentralized Identifier (DID) Core specification (W3C, 2022), the Verifiable Credential (VC) Data Model (W3C, 2022), and related standards including DID Resolution, DID URL dereferencing, and the Verifiable Credential Proof Formats. The paper provides a taxonomic analysis of DID methods (did:key, did:ethr, did:ion, did:web, did:indy) in terms of their trust assumptions, ledger requirements, latency, cost, and privacy properties. We compare MF+SO's identity model—which uses Ed25519 public keys as self-certifying identifiers with a local hash chain for state verification—against the W3C DID Core model, identifying both alignments and divergences. Key findings include: MF+SO identifiers are functionally equivalent to DIDs but use a simplified resolution mechanism that does not require a distributed ledger or external registry; MF+SO's hash chain audit trail provides state verification properties comparable to DID Document versioning on a ledger; and MF+SO's selective disclosure mechanisms using zero-knowledge proofs (see Paper VII) directly implement the W3C Verifiable Credential selective disclosure and data minimization requirements. We analyze the interoperability implications of MF+SO's architecture, demonstrating how MF+SO DIDs can be registered on external DID methods for cross-system interoperability while maintaining the local hash chain as the authoritative state source. The paper also examines the Verifiable Credential lifecycle within MF+SO: issuance, storage, presentation, and revocation, with attention to the credential schema registry, proof format compatibility (Data Integrity Proofs, JSON Web Signatures), and the holder-binding mechanisms that prevent credential sharing. A comparative assessment evaluates MF+SO against three alternative decentra... Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
konstantinos votis, Panagiotis Symeonidis, Centre for Research and Technology Hellas
This deliverable provides an overview of the Digital Product Passport, Distributed Ledger Technology, and blockchain applied to the needs of ALUMIL in order to demonstrate the use of DPPs in the Aluminium industry sector.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Organizations operating multiple AI systems generate independent cryptographic ledgers that may need mutual verification, cross-referencing, or consolidated audit for enterprise-wide compliance reporting. Cross-chain notarization provides cryptographic evidence that a ledger's state is acknowledged by another independent ledger, enabling distributed audit verification without central coordination. This paper presents the design and analysis of the AIOSS cross-chain notarization protocol, which anchors the hash chain head of one ledger into another by inserting a notarization entry containing the cross-chain proof. We define three notarization modes: unilateral (ledger A notarizes ledger B's state), bilateral (mutual notarization between A and B), and supervised (third-party notarizer with independent proof). The notarization proof comprises a Merkle inclusion proof of the source ledger's state proof within a notarization ledger entry, enabling verification by any party holding both ledger files. We analyze the security of cross-chain anchoring under the common prefix assumption, proving that notarization preserves the integrity of both ledgers. Performance benchmarks demonstrate that notarization completes in under 200 milliseconds for ledgers of up to 1 million entries. We further evaluate the notarization merge operation, which produces a unified ledger from multiple notarized ledgers with cross-reference integrity. The protocol supports regulatory requirements for multi-system audit consolidation under SOC2 reporting and GDPR Article 30 record-of-processing activities. --- Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores hash chain, cryptography in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper presents a rigorous analysis of the hash chain auditability mechanism implemented within the MF+SO sovereign identity vault, specifically the `.aioss` hash chain data structure. The hash chain links successive vault state commitments through SHA3-256 cryptographic hashes, creating an immutable, tamper-evident log of all state transitions. Each link in the chain incorporates a parent_hash invariant that binds the current state to the entire prior history, a canonical JSON serialization of the vault state to ensure deterministic hashing across platforms, and an Ed25519 signature providing cryptographic proof of authenticity. We demonstrate that this construction achieves the forensic auditability properties first described by Haber and Stornetta (1991) for digital timestamping, extended to the identity management domain. The paper provides a formal mathematical model of the chain construction, analyzes the computational and storage costs of chain verification, presents a security proof for the tamper-detection properties under the random oracle model, and compares the MF+SO approach against alternative audit log constructions including Merkle trees, Certificate Transparency logs, and blockchain-based registries. The implementation leverages SHA3-256's sponge construction to eliminate length extension vulnerabilities that would compromise naive hash chain implementations. Empirical measurements demonstrate that chain verification for a typical user with 10,000 state transitions completes in under 200 milliseconds on modern mobile hardware. The paper concludes with an analysis of forward secrecy guarantees, key rotation impacts on chain continuity, and proposed extensions for zero-knowledge proofs of chain membership. Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper argues that universal, cross-domain trust scores — from credit ratings and ESG scores to AI-generated trust metrics — face structural limits that better data or better models do not remove. The claim is not that scoring is never useful, but that compressing trust into a single comparable number, used for high-stakes allocation across contexts, recurrently fails. Trust is treated here not as a scalar quantity but as a contextual, relational, and time-dependent state. The paper identifies five recurring failure modes (context collapse, Goodhart's Law, epistemic centralization, irreversibility, and metric substitution for truth), illustrated through documented institutional failures (Enron, Wirecard, Volkswagen Dieselgate, the 2008 subprime crisis, and ESG rating practice). An informal impossibility argument — analogous in form to Arrow's theorem, not a formal mathematical proof — suggests that no single universal trust score can jointly satisfy context-independence, temporal stability, observer-neutrality, and manipulation-resistance. The paper then discusses proof-based verification as a complementary paradigm: for a bounded class of objective, checkable claims, the need for trust is reduced through local verification rather than measurement. Examples include Bitcoin proof-of-work, zero-knowledge proofs, and blockchain-based supply chain traceability. The limits of this approach are discussed explicitly, including the oracle problem and the irreducibly judgmental claims that proof cannot settle. This is version 2.0, a substantial revision repositioning the work from a position paper toward a conceptual analysis: the central thesis is qualified, an explicit scope-and-limitations section is added, the impossibility argument is reframed as informal, and the limits of proof-based verification are addressed directly.
Antonio Pellicani, Gianvito Pio, Sašo Džeroski, Michelangelo Ceci
Abstract The cryptocurrency market represents a significant innovation in the financial ecosystem, built upon cryptographic principles to ensure secure and transparent transactions. Cryptocurrencies experienced a global adoption, driven by their decentralized nature that enables borderless transactions without third-party intermediaries. The price of cryptocurrencies is characterized by a significant volatility, that introduces both opportunities and challenges. In this context, the development of accurate methods for the forecasting of price variation, able to work in real-time on data streams, has become vital for various stakeholders. In this paper, we propose a novel approach, called LEMON, for the online prediction of the price variation of cryptocurrencies, that leverages possible temporal correlations among them. Our approach stems from the empirical evidence that cryptocurrencies tend to form groups characterized by similar trends, a behavior often attributed to shared market dynamics and common external factors. Through the analysis of temporal correlations, LEMON dynamically identifies these groups, that are then exploited to learn multiple multi-target tree-based models, specifically designed for processing continuous data streams. LEMON also introduces a novel adaptive non-parametric weighting scheme, that automatically adjusts the importance of each instance based on the observed data distribution in real-time, improving the forecasting of the price variation. Our experiments, performed on 16 datasets related to 16 cryptocurrencies, demonstrate that LEMON outperforms state-of-the-art approaches in two distinct prediction tasks: forecasting the closing price variation (regression) and predicting the market trend direction (classification), making it an effective tool to support stakeholders requiring accurate real-time predictions.
Privacy-preserving systems have traditionally faced a fundamental tradeoff between data utility and confidentiality. Selective Disclosure Credentials (SDCs) enable users to prove specific attributes without revealing underlying personal information, while Fully Homomorphic Encryption (FHE) enables arbitrary computation on encrypted data without exposing plaintext. Although both technologies address critical privacy challenges, they solve different problems and are rarely integrated into a unified architecture. This paper introduces the concept of Composable Privacy, a layered framework that combines selective disclosure credentials, zero-knowledge proofs, and fully homomorphic encryption into a cohesive privacy architecture. The framework separates privacy concerns into three functional layers: an authentication layer using selective disclosure and zero-knowledge proofs, a computation layer using homomorphic encryption for confidential processing, and a verification layer that provides cryptographic assurances of computation correctness. The paper examines the cryptographic foundations of BBS+ signatures, Coconut threshold credentials, lattice-based homomorphic encryption schemes, and post-quantum security considerations. It further evaluates the practical feasibility of the architecture through applications in decentralized finance, healthcare federated learning, confidential governance systems, and blockchain-based identity infrastructure. Performance trends, scalability challenges, interoperability requirements, and future hardware acceleration pathways are also analyzed. The proposed Composable Privacy framework demonstrates how selective disclosure and encrypted computation can be combined to create privacy-preserving digital systems that maintain verifiability, confidentiality, and regulatory compliance simultaneously. The work provides a conceptual foundation for next-generation privacy architectures in blockchain, decentralized identity, and distributed computing environments.
Self-sovereign identity (SSI) represents a paradigm shift in digital authentication, transferring control from centralized identity providers to individual users (Mühle et al., 2018). This paper presents the Kathon Vault identity system, which implements self-sovereign browser identity through BIP39 mnemonic seed phrases (Palatinus et al., 2013) for Ed25519 hierarchical deterministic (HD) key generation (Bernstein et al., 2012; Wuille, 2012). The system generates a master seed from a BIP39 mnemonic (12, 18, or 24 words with configurable passphrase), derives Ed25519 keypairs through the SLIP-10 key derivation scheme (Přikryl, 2022), and enables zero-knowledge authentication across websites through a novel browser-native WebAuthn-hybrid protocol. We demonstrate that the BIP39-derived Ed25519 keys provide equivalent security to standard FIDO2/WebAuthn authenticators (316 bits of entropy for 24-word phrases) while offering three critical advantages: (1) deterministic key recovery from the mnemonic phrase alone, (2) hierarchical key organization matching the SLIP-44 registered coin type for Kathon, and (3) cryptographic privacy through zero-knowledge proofs that enable selective attribute disclosure without revealing the master public key. In a security analysis against brute-force, dictionary, side-channel, and social engineering attacks, the system achieves resistance levels exceeding NIST SP 800-63B Level 4 authentication assurance requirements (NIST, 2020). A usability study with 48 participants demonstrates that BIP39-based authentication achieves 96% successful login rates with 14% lower task completion time compared to password manager-based workflows. This work establishes mnemonic-based HD key generation as a viable and superior alternative to federated identity providers for browser-based authentication. --- Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores browser engine, privacy in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
This paper examines the cryptographic foundations of audit ledgers, with particular focus on hash chains, transparency logs, and verifiable data structures as implemented in the 01s Sovereign (Kaiman) operating system's .aioss ledger format. We survey the evolution from simple hash-linked data structures to sophisticated transparency frameworks such as Certificate Transparency (CT), CONIKS, and Trillian, and demonstrate how these technologies converge in the 01s Sovereign OS to create an immutable, verifiable record of all system and AI-assisted decisions. Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores api gateway, ai routing in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
Ronansa Vaza Bramudya, Ratna Roostika, Nur Aima Syafie
The rapid growth of non-fungible tokens (NFTs) has increased competition among digital marketplaces and heightened the need to understand factors that drive consumer purchase intention. However, NFT platforms still face challenges related to technological complexity and trust, which may hinder user participation. This study examines the effects of social influence, effort expectancy, performance expectancy, and trust on purchase intention in the Magic Eden NFT marketplace using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This research contributes by extending the UTAUT model to the NFT marketplace context and highlighting the pivotal role of trust in shaping user perceptions and behavioral intentions. A quantitative approach was employed by collecting data from 251 Magic Eden users through an online questionnaire distributed via social media and crypto communities. The data were analyzed using Structural Equation Modeling (SEM) with SmartPLS to test the proposed relationships. The results indicate that social influence, effort expectancy, and performance expectancy have significant positive effects on purchase intention. Trust also has a strong positive effect on effort expectancy and performance expectancy, as well as a direct positive effect on purchase intention. Among the examined relationships, trust shows the strongest influence on users’ perceived ease of use of the platform. Overall, the findings suggest that strengthening trust and improving platform usability are essential for increasing purchase intention in NFT marketplaces.
We study the evolution of transaction speed and fees from January 2024 through March 2026, comparing Ethereum Mainnet and its Layer 2 (L2) networks, as well as Solana and Polygon. Ethereum has undergone upgrades that have increased block size and blob count. These upgrades have doubled transactions per second (TPS) on both the Mainnet and the L2 networks. Mainnet median fees have fallen from over \$2 to under \$0.02, and L2 median fees have fallen more than 95% from \$0.05 to \$0.0015. We forecast that Mainnet median fees will converge with Solana in August 2027, but TPS will remain below 100 until 2034. The L1 Strawmap, proposing EIP-7938, a potential exponential increase in the gas limit, brings the Mainnet to only 100 TPS in January 2028. With continued blob expansion, L2s will surpass Solana TPS in March 2029 and have lower median fees by October 2026.
This paper presents a comprehensive analysis of zero-knowledge proof (ZKP) systems and their application to privacy-preserving identity management within the MF+SO sovereign identity vault. Zero-knowledge proofs, introduced by Goldwasser, Micali, and Rackoff (1985), enable a prover to convince a verifier of the truth of a statement without revealing any information beyond the statement's validity. We examine three families of ZKP systems in the context of MF+SO's identity assertions: zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge), zk-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge), and Bulletproofs. For each family, we analyze the setup assumptions (trusted setup vs. transparent), proof size, verification complexity, prover computation, and post-quantum security. The paper identifies three canonical use cases within MF+SO: (1) age verification without date of birth disclosure, where the user proves that their age exceeds a threshold without revealing their exact birth date; (2) credential possession proof, where the user proves they hold a valid credential for a resource without revealing which credential among a set they hold; and (3) membership in an allowlist without position disclosure, where the user proves their identifier appears in a list without revealing their position in the list. We present benchmark data for each use case using the Groth16 zk-SNARK (prover time: 1.2 seconds, proof size: 192 bytes, verification: 2.3 ms) and the STARK-based approach using the Winterfell library (prover time: 4.8 seconds, proof size: 48 KB, verification: 8.1 ms). The implementation complexity analysis demonstrates that zk-SNARKs require trusted setup ceremonies but provide the most compact proofs, while zk-STARKs eliminate the trusted setup requirement at the cost of larger proofs. The paper concludes with an analysis of the protocol integration requirements, including circuit compilation for the MF+SO identity predicate lang... Part of The Anticloud research corpus by Lois-Kleinner Alpasan (ORCID: 0009-0009-2233-6107). This work explores cryptography, key management in the context of sovereign AI infrastructure, post-cloud computing architectures, and transparent, blackbox-free systems.
Established threat modelling methodologies (STRIDE, PASTA, Trike, OCTAVE, LINDDUN, attack trees, and adversary-behaviour catalogues such as MITRE ATT&CK) were designed for software products and enterprises with a discernible security perimeter, a single owning organisation, and a clean separation between technical and operational risk. Modern organisations violate all three assumptions: they run on cloud and SaaS control planes they do not own, distribute privileged authority across founders, contractors, vendors, signers, committees, and automation, and expose value through human approval ceremonies and supply-chain edges rather than a network boundary. The dominant failures are authorised-but-malicious actors, collusion across nominally independent parties, control-plane and CI/CD compromise, and operational mishandling of high-value actions, which existing methods largely omit. We present TRACE, a methodology that treats threat actors, roles, assets, critical invariants, and trust/authority edges as first-class, evidence-linked objects spanning three layers: protocols, systems, and organisations. We compare nine widely used frameworks across ten dimensions, show where each falls short in distributed, cloud-first, zero-trust settings, and specify TRACE: its core model, three application pillars, sequential gated workflow, and an evidence-and-traceability discipline for human-AI co-working in which language models accelerate coverage while senior reviewers retain judgement over invariants, severity, and collusion. TRACE was developed through Web3 security practice but is stack-agnostic. We discuss its relationship to zero trust architecture and accountable Byzantine consensus, its limitations, and open questions around empirical validation.