Matei Sofronie, Andrei Brînzea, Alexandru Bratu, Iulian Aciobăniţei · 5 authors
Verifiable Credentials (VCs) are a core component of decentralized identity systems, enabling individuals to prove claims without centralized intermediaries. However, managing VC revocation across segregated blockchain networks remains a key interoperability challenge. In this paper, we present a bidirectional blockchain bridge that enables the cross-chain verification of VCs between two Ethereum-compatible private blockchain networks: Geth and Besu. The system allows credentials issued and revoked on one chain to be validated from another without duplicating infrastructure or compromising security. Our architecture combines on-chain smart contracts with an off-chain relay, ensuring auditable, low-latency credential checks across chains. Our proposal is validated through an open-source working prototype. It is particularly relevant for domains where independent organizations must validate shared credentials across segregated blockchain infrastructures, including education, healthcare, and governmental identity services.
Multi-agent systems (MAS) have emerged as a critical paradigm for distributed problem-solving in complex environments. However, their deployment in mission-critical applications faces significant challenges regarding trust, security, and adversarial robustness. This paper presents TrustOrch, a novel dynamic trust-aware orchestration framework designed to enhance the resilience of multi-agent collaboration against adversarial attacks. TrustOrch introduces five key innovations: (1) a dynamic trust assessment mechanism that evaluates agent reliability in real-time using multi-dimensional metrics, (2) an adversary-aware orchestration strategy combining reinforcement learning and game theory to detect and mitigate prompt injection attacks, (3) an adaptive collaboration topology that dynamically adjusts agent communication structures based on task complexity and trust levels, (4) explainable decision tracing for complete audit chains, and (5) a layered security architecture leveraging blockchain technology for decentralized trust verification. Our experimental evaluation demonstrates that TrustOrch reduces collision rates by 62%, achieves 91.7% robustness under adversarial attacks, and reduces communication overhead by 39.8% compared to baseline approaches. The framework achieves robust performance under various adversarial scenarios while maintaining transparency and regulatory compliance, making it particularly suitable for deployment in high-risk domains such as finance, healthcare, and autonomous systems.
Trust management systems (TMS) are crucial for managing trust in distributed environments. The rise of decentralized systems and blockchain has sparked interest in credential-based decentralized trust management systems (DTMS). This paper bridges the gap between theory and practice through a systematic review of credential-based DTMS. We analyze existing DTMS solutions through multiple dimensions, including their architectural designs, credential mechanisms, and trust evaluation models. Our survey provides a detailed taxonomy of credential-based DTMS approaches and establishes comprehensive evaluation criteria for assessing DTMS implementations. Through extensive analysis of current systems and implementations, we identify critical challenges and promising research directions in the field. Our examination offers valuable insights for researchers and practitioners working on DTMS, particularly in areas such as access control, reputation systems, and blockchain-based trust frameworks.
Consensus algorithms are essential for blockchain networks to achieve agreement on transaction outcomes. However, mainstream algorithms like Proof of Work (PoW) and Proof of Stake (PoS) exhibit significant limitations in security and efficiency, including high energy consumption, wealth centralization, and a lack of effective node behavior evaluation to guard against internal attacks. To address these issues, this paper proposes an intelligent reputation-based consensus mechanism leveraging a Long Short-Term Memory (LSTM) network. This mechanism analyzes multi-dimensional node attributes (e.g., hostname, country, event sequence, timestamp) to model behavioral patterns using the LSTM, enabling accurate reputation quantification and early detection of malicious intent. Furthermore, we design a dynamic reputation scoring system that calculates a composite reputation score by weighting the LSTM’s predicted score against the node’s historical behavior score. This composite score is directly applied to the dynamic election of authoritative nodes and their role assignment within the consensus process. Simulation results demonstrate that, compared to traditional PoW and PoS mechanisms, our approach significantly reduces the attack success rate of malicious nodes attempting to form monopolies, thereby enhancing the fairness of the consensus process and the overall robustness of the system.
Access control is a security mechanism designed to ensure that only authorized users can access specific resources. Cross-domain access control involves access to resources across different organizations, institutions, or applications. Traditional access control, however, which handles authentication and authorization separately in centralized environments, faces challenges in identity dispersion, privacy leakage, and diversified permission requirements, failing to adapt to cross-domain scenarios. Thus, there is an urgent need for a new access control mechanism that empowers autonomous control over user identity and resources, addressing the demands for privacy-preserving authentication and flexible authorization in cross-domain scenarios.To address cross-domain access control challenges, we propose POLARIS, a unified and extensible architecture that enables policy-based, verifiable and privacy-preserving access control across different domains. POLARIS features a structured commitment mechanism for reliable, fine-grained, policy-based identity disclosure. It further introduces VPPL, a lightweight policy language that supports issuer-bound evaluation of selectively revealed attributes. A dedicated session-level security mechanism ensures binding between authentication and access, enhancing confidentiality and resilience to replay attacks.We implement a working prototype and conduct comprehensive experiments, demonstrating that POLARIS effectively provides scalable, privacy-preserving, and interoperable access control across heterogeneous domains. Our results highlight the practical viability of POLARIS for enabling secure and privacy-preserving access control in decentralized, cross-domain environments.
This study presents a blockchain-backed Role-Based Access Control (RBAC) service for distributed clouds, addressing auditable authorization under multi-region latency and consistency constraints. Although end-to-end costs and tail impacts of permissioned ledgers in RBAC are under-quantified, the present study implements a multi-region deployment with Istanbul Byzantine Fault Tolerance (IBFT), batched commits, and an off-chain cache, with evaluation against centralized and event-sourced baselines, throughput reported in requests per second (RPS), and calibration via Expected Calibration Error (ECE) and Brier Score using multi-seed runs and moving-block bootstrap. At the target load, the candidate achieved 145.0 +/- 4.6 ms 95th percentile (p95) latency and 1008 +/- 13 RPS while meeting the 150.0 ms Service Level Objective at 1000 rps; the 99th percentile (p99) policy-update consistency lag measured 1750.0 +/- 150.0 ms. Connectivity remains the bottleneck. The parts are familiar; the sequencing is not, combining ledger finality with cache-assisted reads and bounded block intervals to narrow the gap to centralized designs under controlled failures. These findings indicate that tamper-evident auditing can be added with modest overhead for enterprise security operators planning multi-region cloud authorization.
Artificial intelligence (AI) agents are increasingly capable of initiating financial transactions on behalf of users or other agents. This evolution introduces a fundamental challenge: verifying both the authenticity of an autonomous agent and the true intent behind its transactions in a decentralized, trustless environment. Traditional payment systems assume human authorization, but autonomous, agent-led payments remove that safeguard. This paper presents a blockchain-based framework that cryptographically authenticates and verifies the intent of every AI-initiated transaction. The proposed system leverages decentralized identity (DID) standards and verifiable credentials to establish agent identities, on-chain intent proofs to record user authorization, and zero-knowledge proofs (ZKPs) to preserve privacy while ensuring policy compliance. Additionally, secure execution environments (TEE-based attestations) guarantee the integrity of agent reasoning and execution. The hybrid on-chain/off-chain architecture provides an immutable audit trail linking user intent to payment outcome. Through qualitative analysis, the framework demonstrates strong resistance to impersonation, unauthorized transactions, and misalignment of intent. This work lays the foundation for secure, auditable, and intent-aware autonomous economic agents, enabling a future of verifiable trust and accountability in AI-driven financial ecosystems.
The security of blockchain systems relies on the honest majority assumption. However, strategic mining threatens this assumption, because selfish miners can gain more block rewards than honest miners by attacks such as withholding blocks. Due to its significant implication, blockchain mining games have been studied in PoW and PoS under various settings using different methods. Nonetheless, this paper argues that the practical limitation of random beacons has not been exploited in strategic mining in PoS blockchains. Current PoS blockchains use random beacons to randomly select validators for each slot. However, the randomness is usually fixed for multiple slots, due to the latency of distributed random beacon protocols. This indicates that validators actually know some information about the election result in the future, which contrasts with the Markov process models in previous analysis. Using this information, this paper presents a close to optimal mining strategy based on an optimal interval scheduling algorithm for each epoch. For proof-of-stake protocols with no propagation delay, we show that a validator with arbitrary proportion of stake can strictly benefit from strategic mining and get significantly higher block rewards than the previous strategies.
As the "agentic web" takes shape-billions of AI agents (often LLM-powered) autonomously transacting and collaborating-trust shifts from human oversight to protocol design. In 2025, several inter-agent protocols crystallized this shift, including Google's Agent-to-Agent (A2A), Agent Payments Protocol (AP2), and Ethereum's ERC-8004 "Trustless Agents," yet their underlying trust assumptions remain under-examined. This paper presents a comparative study of trust models in inter-agent protocol design: Brief (self- or third-party verifiable claims), Claim (self-proclaimed capabilities and identity, e.g. AgentCard), Proof (cryptographic verification, including zero-knowledge proofs and trusted execution environment attestations), Stake (bonded collateral with slashing and insurance), Reputation (crowd feedback and graph-based trust signals), and Constraint (sandboxing and capability bounding). For each, we analyze assumptions, attack surfaces, and design trade-offs, with particular emphasis on LLM-specific fragilities-prompt injection, sycophancy/nudge-susceptibility, hallucination, deception, and misalignment-that render purely reputational or claim-only approaches brittle. Our findings indicate no single mechanism suffices. We argue for trustless-by-default architectures anchored in Proof and Stake to gate high-impact actions, augmented by Brief for identity and discovery and Reputation overlays for flexibility and social signals. We comparatively evaluate A2A, AP2, ERC-8004 and related historical variations in academic research under metrics spanning security, privacy, latency/cost, and social robustness (Sybil/collusion/whitewashing resistance). We conclude with hybrid trust model recommendations that mitigate reputation gaming and misinformed LLM behavior, and we distill actionable design guidelines for safer, interoperable, and scalable agent economies.
The convergence of blockchain and Zero Trust Architecture (ZTA) offers a transformative pathway for enhancing security and resilience in financial infrastructures. Traditional network perimeter models are increasingly inadequate for safeguarding decentralized finance (DeFi), payment systems, and digital asset platforms that operate across distributed environments. This study explores how Zero Trust principles rooted in continuous verification, least privilege access, and micro-segmentation can be effectively integrated into blockchain ecosystems to mitigate identity spoofing, insider threats, and data tampering. By examining hybrid frameworks that combine permissioned blockchains with Zero Trust access controls, the research highlights a paradigm shift toward adaptive, identity-centric security postures in financial networks. The proposed model emphasizes dynamic authentication, real-time monitoring, and cryptographic assurance to ensure trustless yet verifiable interactions among nodes and participants. This integration not only fortifies compliance with emerging regulatory standards but also enhances interoperability and transparency across multi-chain financial systems. The findings suggest that embedding Zero Trust principles within blockchain-oriented infrastructures can create a self-healing, auditable, and future-ready digital finance ecosystem.
Chong Chen, Jiachi Chen, Lingfeng Bao, David F. Lo · 10 authors
Smart contract vulnerabilities, particularly improper Access Control that allows unauthorized execution of restricted functions, have caused billions of dollars in losses. GitHub hosts numerous smart contract repositories containing source code, documentation, and configuration files-these serve as intermediate development artifacts that must be compiled and packaged before deployment. Third-party developers often reference, reuse, or fork code from these repositories during custom development. However, if the referenced code contains vulnerabilities, it can introduce significant security risks. Existing tools for detecting smart contract vulnerabilities are limited in their ability to handle complex repositories, as they typically require the target contract to be compilable to generate an abstract representation for further analysis. This paper presents TRACE, a tool designed to secure non-compilable smart contract repositories against access control vulnerabilities. TRACE employs LLMs to locate sensitive functions involving critical operations (e.g., transfer) within the contract and subsequently completes function snippets into a fully compilable contract. TRACE constructs a function call graph from the abstract syntax tree (AST) of the completed contract. It uses the control flow graph (CFG) of each function as node information. The nodes of the sensitive functions are then analyzed to detect Access Control vulnerabilities. Experimental results demonstrate that TRACE outperforms state-of-the-art tools on an open-sourced CVE dataset, detecting 14 out of 15 CVEs. In addition, it achieves 89.2% precision on 5,000 recent on-chain contracts, far exceeding the best existing tool at 76.9%. On 83 real-world repositories, TRACE achieves 87.0% precision, significantly surpassing DeepSeek-R1's 14.3%.
Fernando Castillo, Eduardo Brito, Sebastian Werner, Pille Pullonen · 5 authors
Service Level Agreement (SLA) monitoring in service-oriented environments suffers from inherent trust conflicts when providers self-report metrics, creating incentives to underreport violations. We introduce a framework for generating verifiable SLA violation claims through trusted hardware monitors and zero-knowledge proofs, establishing cryptographic foundations for genuine trustworthiness in service ecosystems. Our approach starts with machine-readable SLA clauses converted into verifiable predicates and monitored within Trusted Execution Environments. These monitors collect timestamped telemetry, organize measurements into Merkle trees, and produce signed attestations. Zero-knowledge proofs aggregate Service-Level Indicators to evaluate compliance, generating cryptographic proofs verifiable by stakeholders, arbitrators, or insurers in disputes, without accessing underlying data. This ensures three security properties: integrity, authenticity, and validity. Our prototype demonstrates linear scaling up to over 1 million events per hour for measurements with near constant-time proof generation and verification for single violation claims, enabling trustless SLA enforcement through cryptographic guarantees for automated compliance verification in service monitoring.
AbstractAs a key bridge between the real economy and financial capital, supply chain finance generates core data such as transaction documents, logistics information, and financing contracts, whose secure, trustworthy, and controllable management is crucial.Traditional centralized notarization schemes suffer from single points of failure, risks of data tampering, and high trust costs.Although blockchain offers tamper-evident notarization, limited on-chain storage and throughput constrain its direct use in large-scale data scenarios.To address this tension, this paper investigates a secure data notarization and access control algorithm grounded in an on-chain/off-chain hybrid storage architecture and smart contracts.We first construct a layered data management model: high-value, low-volume data hashes (digital fingerprints) and key access-control policies are anchored on-chain to ensure immutability, while complete large-volume raw data are encrypted and stored off-chain (e.g., in IPFS or distributed databases) to ensure scalability.To tackle potential challenges of on-/off-chain consistency and integrity verification under this hybrid architecture, we design an efficient verification mechanism based on cryptographic commitments, ensuring any tampering with off-chain data can be detected quickly and succinctly.Furthermore, to achieve fine-grained privacy protection and compliant use, we propose a smart-contract-based dynamic access control algorithm.By deploying access-control policies as executable code on-chain, the algorithm performs automated logical checks to deliver precise authorization and comprehensive audit logging, ensuring security and transparency throughout data sharing and circulation.Through theoretical security analysis and prototype experiments, the proposed scheme preserves data immutability and traceability while significantly improving the storage efficiency and processing performance of supply chain finance notarization systems, and it enables flexible and secure access control.The results indicate that the coordinated mechanism of on-chain/off-chain hybrid storage and smart contracts offers a feasible technical pathway for building efficient, trustworthy, and secure supply chain finance infrastructure.
Octara Pribadi, Johanes Terang Kita Perangin Angin, Erick Erick
The development of information technology has driven the need for stronger security systems and guaranteed privacy on web-based platforms. Traditional verification methods such as passwords and two-factor authentication are increasingly seen as insufficient in facing the growing complexity of cyber threats. Zero-Knowledge Proof (ZKP) emerges as an alternative solution that enables identity verification without revealing sensitive information. This research aims to implement ZKP technology in web-based systems to enhance user security and privacy. The method involves the implementation of a simple XOR-based ZKP algorithm to prove identity without disclosing personal data, as well as a three-step verification mechanism between the verifier and the prover. Implementation results show that the system can prevent attacks such as man-in-the-middle and replay attacks, while maintaining data confidentiality during the authentication process. This study also identifies challenges in system efficiency and verification process integrity and offers technical solutions to support broader ZKP integration in digital platforms. Thus, the use of ZKP in web-based systems holds great potential to improve user trust and security in the digital era.
Decentralized applications (dApps) in Decentralized Finance (DeFi) face a fundamental tension between regulatory compliance requirements like Know Your Customer (KYC) and maintaining decentralization and privacy. Existing permissioned DeFi solutions often fail to adequately protect private attributes of dApp users and introduce implicit trust assumptions, undermining the blockchain's decentralization. Addressing these limitations, this paper presents a novel synthesis of Self-Sovereign Identity (SSI), Zero-Knowledge Proofs (ZKPs), and Attribute-Based Access Control to enable privacy-preserving on-chain permissioning based on decentralized policy decisions. We provide a comprehensive framework for permissioned dApps that aligns decentralized trust, privacy, and transparency, harmonizing blockchain principles with regulatory compliance. Our framework supports multiple proof types (equality, range, membership, and time-dependent) with efficient proof generation through a commit-and-prove scheme that moves credential authenticity verification outside the ZKP circuit. Experimental evaluation of our KYC-compliant DeFi implementation shows considerable performance improvement for different proof types compared to baseline approaches. We advance the state-of-the-art through a holistic approach, flexible proof mechanisms addressing diverse real-world requirements, and optimized proof generation enabling practical deployment.
Current systems for exchanging medical records struggle with efficiency and privacy issues. While establishing the Electronic Medical Record Exchange Center (EEC) in 2012 was intended to alleviate these issues, its centralized structure has brought about new attack vectors, such as performance bottlenecks, single points of failure, and an absence of patient consent over their data. Methods: This paper describes a novel EMR Gateway system that uses blockchain technology to exchange electronic medical records electronically, overcome the limitations of current centralized systems for sharing EMR, and leverage decentralization to enhance resilience, data privacy, and patient autonomy. Our proposed system is built on two interconnected blockchains: a Decentralized Identity Blockchain (DID-Chain) based on Ethereum for managing user identities via smart contracts, and an Electronic Medical Record Blockchain (EMR-Chain) implemented on Hyperledger Fabric to handle medical record indexes and fine-grained access control. To address the dual requirements of cross-platform data exchange and patient privacy, the system was developed based on the Fast Healthcare Interoperability Resources (FHIR) standard, incorporating stringent de-identification protocols. Our system is built using the FHIR standard. Think of it as a common language that lets different healthcare systems talk to each other without confusion. Plus, we are very serious about patient privacy and remove all personal details from the data to keep it confidential. When we tested its performance, the system handled things well. It can take in about 40 transactions every second and pull out data faster, at around 49 per second. To give you some perspective, this is far more than what the average hospital in Taiwan dealt with back in 2018. This shows our system is very solid and more than ready to handle even bigger workloads in the future.
The rapid co-evolution of Artificial Intelligence (AI) and blockchain technology has exposed a persistent gap between intelligence-the ability to extract insight from data-and trust-the assurance that data, models, and decisions are transparent, verifiable, and tamper-proof.This study introduces the Unified Trust-Intelligence Framework (UTIF), an end-to-end architecture that natively fuses AI and distributed-ledger technologies to deliver auditable, privacy-preserving, and energy-aware intelligent services.A systematic review compliant with PRISMA guidelines (167 peer--reviewed sources, 2018-2024) reveals four critical deficiencies in the current literature: (i) the lack of formal on-chain model certification, (ii) opaque immutability of operational logs, (iii) limited cross-chain and cross-domain interoperability, and (iv) sub--optimal energy footprints.UTIF addresses these gaps through: On-chain algorithmic certification that fingerprints model weights and training metadata via cryptographic hashing.Federated data governance that combines privacy-preserving federated learning with zero-knowledge proofs (ZK-SNARKs) for regulatory compliance (GDPR, EU AI Act).An AI-assisted hybrid PoS-BFT consensus that dynamically tunes fault-tolerance parameters under varying network conditions.A self-verifiable MLOps pipeline deployed on Hyperledger Fabric with Layer-2 rollups, providing continuous integration, delivery, and audit trails.Experimental validation uses two open-access benchmarks-MIMIC-IV (clinical) and ECB-SDW (financial)-executed on a 20-node heterogeneous testbed.UTIF reduces transaction latency by 38 % and operational energy consumption by 27 % compared with Fabric 2.x and PoA baselines, while enhancing adversarial ro-bustness (F1 + 12 %) through on-chain model attestation.A perception survey of 46 domain experts reports a statistically significant boost in trustability (+1.27 0.31 on a 5-point Likert scale, p < 0.01).Stress tests show 98 % valid throughput under Sybil scenarios with 1,000 malicious nodes, maintaining a carbon footprint below 0.25 kg CO e per 1,000 transactions.The findings demonstrate that deep, native convergence of AI and blockchain can simultaneously achieve measurable trust guarantees, competitive performance, and sustainability.The article concludes with regulatory implications, identified limitations (network scale, oracle dependencies), and a research roadmap toward edge-to--cloud, 6G-ready, Web3-compliant intelligent infrastructures.
Healthcare data management in cloud environments faces critical challenges in balancing security, privacy, operational efficiency, and regulatory compliance, as traditional access control mechanisms are inadequate for addressing the complex, multi-tenant, and dynamic nature of modern cloud infrastructures handling sensitive Electronic Health Records (EHRs). This paper introduces a novel hybrid framework that integrates Attribute-Based Access Control (ABAC) with Ethereum blockchain technology to establish a comprehensive multi-layered security architecture for cloud-based healthcare systems, combining advanced cryptographic techniques including double encryption using AES and RSA algorithms, Shamir's Secret Sharing for key management, smart contracts for automated policy enforcement, and multi-party computation protocols to ensure privacy preservation without compromising system performance. Extensive experimental evaluation conducted using 4,412 anonymized clinical records with 12 distinct attributes demonstrates exceptional efficiency with average record insertion time of 1.90 ms, retrieval time of 0.14 ms, blockchain mining time of 0.01 seconds, and hybrid architecture throughput of 562.94 records/second with 1.78 ms latency, significantly outperforming traditional centralized systems (337.17 rec/s, 2.97 ms) and pure blockchain implementations (3.37 rec/s, 296.98 ms). Security assessments reveal 100% operational reliability, 97.3% policy violation detection accuracy, 89% reduction in unauthorized access attempts, and comprehensive regulatory compliance with HIPAA (97%), GDPR (92%), ISO 27001 (94%), and SOC 2 (89%) standards, while maintaining optimized system resource utilization with CPU usage at 35.6%, memory at 48.0%, and network I/O at 34.1%. The framework addresses key limitations of existing approaches by providing seamless integration across multiple cloud layers, eliminating single points of failure, ensuring data immutability through distributed consensus mechanisms, maintaining comprehensive audit trails, and offering practical implications for healthcare organizations seeking secure, scalable, and compliant data sharing mechanisms in cloud-native environments, thereby contributing to the advancement of secure healthcare informatics by bridging the gap between theoretical access control models and practical implementation requirements in distributed cloud infrastructures.
Network Systems, AT&T, United States, Amar Gurajapu, Vardhan Garimella, United States Intellibus
ABSTRACT: Distributed cloud services across multiple providers demand consistent identity verification and policy enforcement. Centralized IAM and policy managers introduce single points of failure, limited auditability, and latency. We propose BC-IdPol, a blockchain-based framework that stores identities and governance policies on a permissioned ledger. Smart contracts enforce registration, authentication, and policy retrieval. Off-chain cloud agents query the chain for runtime decisions. In experiments over a three-cloud prototype (Azure, AWS, GCP) on Hyperledger Fabric, BC- IdPol achieved: 99.9 % tamper-resistance (vs. 0 % baseline) 45 ms median identity lookup latency (vs. 18 ms centralized API) 60 ms median policy fetch time (vs. 20 ms baseline) 1,800 req/sec enforcement throughput (vs. 2,200 req/sec) We detail architecture, smart-contract design, mermaid diagrams, evaluation results, limitations, and future work.
Ensuring the integrity of business processes without disclosing confidential business information is a major challenge in inter-organizational processes. This paper introduces a zero-knowledge proof (ZKP)-based approach for the verifiable execution of business processes while preserving confidentiality. We integrate ZK virtual machines (zkVMs) into business process management engines through a comprehensive system architecture and a prototypical implementation. Our approach supports chained verifiable computations through proof compositions. On the example of product carbon footprinting, we model sequential footprinting activities and demonstrate how organizations can prove and verify the integrity of verifiable processes without exposing sensitive information. We assess different ZKP proving variants within process models for their efficiency in proving and verifying, and discuss the practical integration of ZKPs throughout the Business Process Management (BPM) lifecycle. Our experiment-driven evaluation demonstrates the automation of process verification under given confidentiality constraints.
Rui Han, Bin Yuan, Weizhong Qiang, Deqing Zou · 5 authors
The widespread use of IoT devices in the accommodation and hospitality sectors has created demand for temporary device-permission sharing and transfer. Prior work has largely focused on security issues in device permission sharing, with far less attention devoted to device permission transfer. However, inappropriate access control management during device permission transfer can also lead to violations of the users' expectations of control over their devices. For example, a malicious host retaining or regaining access to a camera after its permission has been transferred to a tenant. In this paper, we present the first systematic study on understanding and enhancing the security of device permission transfer in IoT leasing. To this end, we propose Forseti, a new authorization framework that leverages zero-knowledge proof and a decentralized ledger to ensure that the rights of both hosts and tenants are not violated. Our evaluation demonstrates that Forseti is effective, efficient, scalable, and compatible with existing IoT platforms.
Zero Trust is now the de facto standard to secure cloud-native, distributed, and AI-driven enterprise infrastructures. It's not only crucial to address human identities but also to secure non-human entities such as APIs, software agents, RPA bots, and smart city workloads. As hybrid infrastructures become the new normal and agentic AI systems (e.g., self-driving cars) grow more autonomous, identity remains the most stable and trustworthy security control plane. This document proposes an intent-aware Zero Trust Identity Architecture designed to consolidate governance, authentication, and access control for human and non-human entities. The architecture consists of decentralized identity provisioning, policy-as-code enforcement, real-time telemetry ingestion, trust scoring, and AI-powered intent detection to provide inputs for continuous verification and least privilege enforcement. Compliant with standards such as NIST SP 800-207, NIST SP 800-63, CISA Zero Trust Maturity Model, and DoD's Zero Trust Strategy, the architecture also aligns with industry developments from Microsoft Entra ID, AWS IAM Identity Center, Google BeyondCorp, SPIFFE/SPIRE, and W3C DIDs. The whitepaper explores use cases in healthcare, finance, retail, and industrial IoT spaces that are struggling with unique challenges like OT/IT convergence, multi-user devices, and governance of sensitive data access. High-profile attacks such as SolarWinds, MOVEit, and Log4Shell are broken down to highlight weaknesses in legacy IAM architectures and underscore the need for intent-based security. By intersecting behavior, purpose, and identity, this architecture remakes trust in hybrid, edge, and cloud-native settings with a conclusion of actionable paths of mitigation and a vision for intent-based Zero Trust governance
Escrow trust is a foundational requirement for high-value campaign execution in Web3 marketing marketplaces. When campaign budgets exceed USD 50,000 and settlement is enforced on-chain, the security properties of the escrow contract and its surrounding settlement architecture determine whether the platform can be trusted by enterprise brands. Naive escrow designs — single-key deployment, monolithic contract logic, and implicit state transitions — expose platforms to fund loss through key compromise, smart contract exploit, and fraudulent dispute resolution. This paper presents SESA (Secure Escrow and Settlement Architecture), a formal engineering framework for Web3 campaign escrow that integrates multi-signature approval policies, strict role segregation between campaign management and fund release authority, control-plane and data-plane separation with hardware-backed signing, and explicit finite-state machine governance of all escrow lifecycle transitions including dispute resolution. SESA is grounded in a formal threat model that enumerates eleven attack vectors specific to Web3 escrow systems and maps each to a corresponding architectural control. A formal verification of the escrow state machine using the TLA+ specification language demonstrates the absence of deadlock, fund loss, and unauthorised release under all reachable states. A gas cost analysis of the reference Solidity implementation demonstrates that SESA's security controls add a mean overhead of 23% in gas cost relative to a naive single-key escrow — a trade-off that enterprise buyers consistently accept in exchange for verifiable security assurances. SESA enables campaign budgets that would be commercially unviable under insecure escrow designs to flow safely through the platform, directly expanding the addressable market for high-value brand partnerships.