Blockchain technology has emerged as a transformative model in tourism and hospitality, offering innovative solutions to challenges in transparency, trust, and efficiency. This chapter examines the theoretical foundations and practical applications of blockchain, emphasizing its alignment with frameworks such as social exchange theory, transaction cost economics, and sustainability principles. Key applications include blockchain-based loyalty programs, supply chain management, decentralized booking platforms, and secure payment systems. This chapter also highlights future opportunities, such as decentralized autonomous organizations (DAOs), non-fungible tokens (NFTs), and artificial intelligence (AI) integration, showcasing their potential to redefine the industry. Despite challenges such as scalability and regulatory uncertainties, blockchain offers significant promise for creating a transparent, efficient, and sustainable future in tourism and hospitality. By bridging theoretical constructs with practical insights, this chapter provides a comprehensive guide for researchers and practitioners aiming to harness blockchain’s capabilities.
The rapid proliferation of smart home IoT devices has introduced unprecedented cybersecurity vulnerabilities, necessitating scalable and privacy-preserving intrusion detection systems (IDS). Federated Learning (FL) offers a promising decentralized approach by training models locally without sharing raw data, but it remains susceptible to poisoning attacks and relies on a vulnerable central aggregator. This paper presents a novel blockchain-enhanced FL framework tailored for smart home IDS, integrating multiple consensus mechanisms—Proof-of-Stake (PoS), Practical Byzantine Fault Tolerance (PBFT), and Proof-of-Authority (PoA)—for the first time in this context. Our approach uniquely combines differential privacy (DP) and secure aggregation (SA) within a blockchain-managed workflow to mitigate gradient inversion and membership inference attacks while ensuring tamper-resistant, decentralized trust. Experimental evaluation using the N-BaIoT dataset demonstrates that the proposed system achieves up to 88.3% detection accuracy with manageable latency (~200 ms/round) and formal privacy guarantees ($\varepsilon$=1.0 DP). The framework introduces 52.8% system overhead compared to vanilla FL—a reasonable trade-off for enhanced security and privacy. This work establishes a robust, transparent, and scalable security infrastructure for smart homes, effectively addressing the limitations of both centralized and conventional FL-based IDS.
This paper proposes the Physical Law-Based Security System (PLBSS), a novel distributed ledger paradigm that anchors digital records to irreversible astrophysical events rather than computational assumptions. By deriving absolute timestamps from the past light cones of phenomena such as supernovae or gravitational waves, PLBSS achieves physically irreversible, non-consensus-based data integrity. The system combines probabilistic event anchoring and quantum-based node verification, rendering retroactive tampering physically impossible under known laws of nature.
Perkembangan cryptocurrency, khususnya ethereum telah menarik perhatian banyak kalangan karena volatilitas harga yang tinggi karena dipengaruhi oleh faktor-faktor ekonomi dan sentimen pasar. Penelitian ini bertujuan untuk menganalisis hubungan antara sentimen pengguna twitter dengan fluktuasi harga ethereum menggunakan teknologi Natural Language Processing (NLP) dan Machine Learning (ML). Metode yang digunakan mencakup pengumpulan data tweet tentang ethereum, pra-pemrosesan data, serta analisis sentimen menggunakan algoritma Naïve Bayes. Data harga ethereum diperoleh dari sumber informasi kripto. Hasil analisis menunjukkan bahwa meskipun terdapat fluktuasi antara sentimen positif dan negatif di twitter, korelasi antara sentimen publik dan pergerakan harga ethereum sangat lemah, dengan nilai koefisien korelasi yang rendah
Decentralized Identifiers (DIDs) are increasingly deployed on distributed ledgers, yet systematic cross-platform evidence on their operational behavior remains limited. We present an empirical benchmarking study of three prominent ledger-based DID methods - Ethereum, Hedera, and XRP Ledger - using reference Software Development Kits (SDKs) under a unified experimental setup. We measure latency, transaction cost, and on-chain metadata exposure, normalizing latency by each platform's block or consensus interval and cost by its native value transfer fee. Privacy leakage is quantified using a Metadata-Leakage Score (MLS), an entropy-based measure expressed in bits per operation. Our results reveal distinct architectural trade-offs. Ethereum enables near-instant, off-chain DID creation, but incurs the highest latency and cost for on-chain lifecycle operations. XRPL delivers deterministic and stable latency with fixed, low fees, yet exhibits higher metadata leakage due to more verbose transaction payloads. Hedera achieves the lowest on-chain latency and low fees with minimal metadata leakage, while occasional variance arises from SDK-side processing and confirmation pipelines. Overall, the findings show that ledger architecture and SDK workflows play a major role in shaping DID latency, cost, and metadata exposure, complementing the effects of the underlying consensus mechanism. These results provide evidence-based insights to support informed selection and configuration of DID systems under performance and privacy constraints.
Zero-knowledge proofs (ZKPs) are cryptographic protocols that allow verification of statements without disclosing the underlying information. Among them, PLONK-based ZKPs are particularly notable for offering succinct, non-interactive proofs of knowledge with a universal trusted setup, leading to widespread adoption in blockchain and cryptocurrency applications. Nonetheless, their broader deployment is hindered by long proof-generation times and substantial memory demands. While GPUs can accelerate these computations, their limited memory capacity introduces significant challenges for efficient end-to-end proof generation.
Krzysztof Gogol, Manvir Schneider, Jan Gorzny, Claudio Tessone
We study the feasibility, profitability, and prevalence of sandwich attacks on Ethereum rollups with private mempools. First, we extend a formal model of optimal front- and back-run sizing, relating attack profitability to victim trade volume, liquidity depth, and slippage bounds. We complement it with an execution-feasibility model that quantifies co-inclusion constraints under private mempools. Second, we examine execution constraints in the absence of builder markets: without guaranteed atomic inclusion, attackers must rely on sequencer ordering, redundant submissions, and priority fee placement, which renders sandwiching probabilistic rather than deterministic. Third, using transaction-level data from major rollups, we show that naive heuristics overstate sandwich activity. We find that the majority of flagged patterns are false positives and that the median net return for these attacks is negative. Our results suggest that sandwiching, while endemic and profitable on Ethereum L1, is rare, unprofitable, and largely absent in rollups with private mempools. These findings challenge prevailing assumptions, refine measurement of MEV in L2s, and inform the design of sequencing policies.
Rainer Stütz, Nicholas Stifter, Melitta Dragaschnig, Bernhard Haslhofer · 5 authors
It is well known that reusing cryptocurrency addresses undermines privacy. This also applies if the same addresses are used in different cryptocurrencies. Nevertheless, cross-chain address reuse appears to be a recurring phenomenon, especially in EVM-based designs. Previous works performed either direct address matching, or basic format conversion, to identify such cases. However, seemingly incompatible address formats e.g., in Bitcoin and Ethereum, can also be derived from the same public keys, since they rely on the same cryptographic primitives. In this paper, we therefore focus on the underlying public keys to discover reuse within, as well as across, different cryptocurrency networks, enabling us to also match incompatible address formats. Specifically, we analyze key reuse across Bitcoin, Ethereum, Litecoin, Dogecoin, Zcash and Tron. Our results reveal that cryptographic keys are extensively and actively reused across these networks, negatively impacting both privacy and security of their users. We are hence the first to expose and quantify cross-chain key reuse between UTXO and account-based cryptocurrencies. Moreover, we devise novel clustering methods across these different cryptocurrency networks that do not rely on heuristics and instead link entities by their knowledge of the underlying secret key.
Marcus Smith, Nico Leslie, Gillian Hughes, Rachael Mulheron
Abstract This chapter explores the complex relationship between money, cryptocurrencies, and negotiable instruments in law. It begins by defining money and discussing its legal tender status, highlighting its role as a store of value and its legal character. The chapter then examines cryptocurrencies, focusing on their nature, their status as property, and the legal debates surrounding their classification as money due to the absence of state backing. It distinguishes between pure intangibles and documentary intangibles, such as negotiable instruments. Finally, the chapter addresses the implications of technological advancements like dematerialization, which may redefine the understanding and transfer of documentary intangibles in the future.
Student elections in African universities are frequently marred by violence and fraud, thereby undermining democratic participation. This paper presents the first blockchain-based voting system specifically designed for student elections at Cheikh Anta Diop University (UCAD) in Dakar, Senegal. The proposed hybrid architecture combines the Ethereum blockchain to ensure vote immutability, MySQL for user data management, and IPFS for decentralized document storage. The system integrates multi-layer biometric authentication (facial recognition and WebAuthn), an eight-phase automated smart contract, and PySpark for real-time blockchain data analysis. Implementation results demonstrate 100% voting accuracy with the automatic generation of tamper-proof electoral records. The storage of IPFS hashes on the blockchain guarantees document integrity while optimizing storage costs. This solution effectively addresses the recurring electoral violence at UCAD while establishing a reproducible framework for democratic modernization within African higher education institutions.
The accelerating digitalization of the energy sector is redefining how electricity is generated, traded, and consumed. Among emerging innovations, smart contracts being self-executing programs embedded on blockchains have become pivotal to the development of decentralized energy markets. This article reviews the state of knowledge and practical progress in applying smart contracts to energy systems, with particular attention to their potential in Ukraine’s evolving energy and digital infrastructure. Through a systematic analysis of academic studies, pilot projects, and policy frameworks, the article identifies the main opportunities, challenges, and future trajectories of blockchain-based automation in energy markets. The starting sections introduce the conceptual foundations of smart contracts, highlighting their essential properties of transparency, immutability, and autonomy. These characteristics enable direct peer-to-peer transactions without intermediaries, potentially lowering transaction costs and improving market efficiency. The subsequent analysis focuses on how smart contracts can support decentralized energy trading, renewable integration, and dynamic pricing, using examples from Australia’s Power Ledger, Brooklyn Microgrid in the United States, and Europe’s Enerchain, WePower, and Sunchain initiatives. To complement international evidence, the article discusses Ukraine’s readiness for pilot adoption in microgrid environments, given its digital transformation agenda and renewable energy policies. The study further examines technological, regulatory, and security challenges hindering large- scale deployment. Issues such as interoperability, scalability of consensus algorithms, and the legal enforceability of smart contracts remain critical barriers. Nevertheless, emerging frameworks like regulatory sandboxes and advances in IoT and AI integration offer pathways to overcome them. MATLAB-based simulation examples illustrate the potential for dynamic pricing and automated market balancing. The article concludes with strategic recommendations for policymakers, engineers, and researchers by emphasizing the need for hybrid architectures combining blockchain, artificial intelligence, and energy optimization models. Overall, the article underscores that while smart contracts promise to democratize and decarbonize energy systems, their success ultimately depends on coordinated technical innovation and adaptive governance.
Lukman Ademola Adepoju, Oyetunji Oyewale, Odekunle Bola Odegbemi, Ifeoluwa Abraham Adeagbo · 5 authors
Over 40 years after the identification of human immunodeficiency virus (HIV), Nigeria remain one of the highest burdens of HIV infections in the world, accounting for almost 10% of new infections in sub-Saharan Africa. Despite significant investments and technical supports from different foreign donors including the United States President’s Emergency Plan for AIDS Relief (PEPFAR), the Global Fund, and bilateral partners. The persistent structural, financial, and programmatic gaps continue to hamper the country’s HIV response. This assessment of HIV-related interventions in Nigeria examines what has been achieved, what still need to be done, and how to establish a sustainable and domestically owned HIV care. The review summarizes evidence from peer-reviewed literature (2018–2025) and major institutional reports (UNAIDS, NACA, WHO, PEPFAR) to assess five key domains: coverage and access, funding and sustainability, health system strengthening, monitoring and evaluation, and sociocultural barriers. Evidence shows that while substantial progress has been achieved in testing, antiretroviral therapy (ART) coverage, and community-based care, the HIV response remains heavily donor-dependent, urban-centered, and fragmented across vertical program streams. The review concludes that to achieve long-term epidemic control (EC) and universal health coverage (UHC) in Nigeria’s HIV care and programming with there is a need for domestic financing, health system integration, decentralized service delivery, and data-driven accountability frameworks.
We investigate whether sophisticated deep learning architectures justify their computational cost for short-term cryptocurrency price forecasting. Our study evaluates a 2.1M-parameter (M represents millions (e.g., 2.1M = 2,100,000 parameters), with all RMSE values reported in USD) wavelet-enhanced transformer that decomposes the Fear and Greed Index (FGI) into multiple timescales before integrating these signals with technical indicators. Using Diebold–Mariano tests with HAC-corrected variance, we find that all models—including our wavelet–transformer, ARIMA, XGBoost, LSTM, and vanilla Transformer—fail to significantly outperform the O(1) naive persistence baseline at the 1-day horizon (DM statistic = +19.13, p<0.001, naive preferred). Our model achieves an RMSE of USD 2005 versus USD 1986 for naive (ratio 1.010), requiring 3909× more inference time (2.43 ms vs. 0.0006 ms) for a statistically worse performance. These results provide strong empirical support for the Efficient Market Hypothesis in cryptocurrency markets: even sophisticated multi-scale architectures combining wavelet decomposition, cross-attention, and auxiliary technical indicators cannot extract profitable short-term signals. Through systematic ablation, we identify positional encoding as the only critical architectural component—its removal causes 30% RMSE degradation. Our findings carry important implications, as follows: (1) short-term crypto forecasting faces fundamental predictability limits, (2) architectural complexity provides negative ROI in efficient markets, and (3) rigorous statistical validation reveals that apparent improvements often represent noise rather than signal.
Abstract Lattice-based commitment schemes and their associated zero-knowledge proofs are essential building blocks for advanced lattice-based cryptographic protocols. In particular, proofs of algebraic relations among committed messages are widely used in privacy-preserving protocols such as range proofs. At CRYPTO 2020, Attema et al. proposed practical proofs for valid openings and multiplicative relations among committed values using the BDLOP commitment scheme. In their work, all commitments are generated using the same short randomness. In this paper, we consider a batch setting where commitments are generated using $$\ell$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℓ</mml:mi> </mml:math> independent random vectors and present a batch valid opening proof. Our construction generalizes the approach of Baum et al. by supporting a larger challenge set and removing the requirement for invertible challenge differences. As a result, the proof size scales logarithmically with $$\ell$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℓ</mml:mi> </mml:math> , rather than linearly. Furthermore, we introduce a product proof for committed messages with shared randomness across these $$\ell$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℓ</mml:mi> </mml:math> commitment groups. Compared to the naive approach of applying Attema’s product proof once and repeating the opening proof $$\ell -1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ℓ</mml:mi> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> times, our method achieves significantly better communication efficiency.
Zhuo Wu, Shi Qi, Xinxuan Zhang, Yi Deng · 6 authors
Abstract Recent years have seen the widespread adoption of zkSNARKs constructed over small fields, including but not limited to, the Goldilocks field, small Mersenne prime fields, and tower of binary fields. Their appeal stems primarily from their efficacy in proving computations with small bit widths, which facilitates efficient proving of general computations and offers significant advantages, notably yielding remarkably fast proving efficiency for tasks such as proof of knowledge of hash preimages. Nevertheless, employing these SNARKs to prove algebraic statements (e.g., RSA, ECDSA signature verification) presents efficiency challenges, particularly in critical applications like zk-bridges and zkVMs that require verifying standard cryptographic primitives. To address this problem, we first define a new circuit model: arithmetic circuits with additional exponentiation gates . These gates serve as fundamental building blocks for establishing more intricate algebraic relations. Then we present a Hash-committed Commit-and-Prove (HCP) framework to construct Non-interactive Zero-knowledge (NIZK) proofs for the satisfiability of these circuits. Specifically, when proving knowledge of group exponentiations in discrete logarithm hard groups and RSA groups, compared to verifying complex group exponentiations within SNARK circuits, our approach requires proving only more lightweight computations within the SNARK, such as zk-friendly hash functions (e.g., Poseidon hash function). The number of these lightweight computations depends solely on the security parameter. This differentiation leads to substantial speedups for the prover relative to direct SNARK methods, while maintaining competitive proof size and verification cost.
Secret Sharing Schemes are cryptographic tools for securely distributing a secret among participants, ensuring that only authorized subsets can reconstruct it while unauthorized coalitions cannot, a property known as information-theoretic security. A key challenge in designing such schemes is reducing share size, which impacts efficiency and scalability in distributed systems. This thesis studies this problem in structured access structures. After reviewing threshold schemes and their ideality, it focuses on weighted threshold access structures, analyzing classical constructions and methods, including approximation techniques, to reduce share size. Their relevance is illustrated in Proof-of-Stake blockchain protocols, where influence is proportional to staked resources. Ideal hierarchical access structures are then characterized using matroid theory, Boolean polymatroids, and lattice path matroids, and related to applications in multi-level blockchain networks such as Polkadot.
This essay examines a “becoming-curatorial” of digital artworks that are augmented with blockchain-enabled smart contracts. It argues that embedding executable code in digital objects enables artworks to exhibit quasi-autonomous, self-governing behaviours that can displace the curatorial agency of human intermediaries and redistribute it to computational agents. By analysing projects such as Sarah Friend’s <i>Lifeforms </i>and Harm van den Dorpel’s <i>Mutant Garden Seeder</i>, the essay shows how programmable tokens can inspire (and enforce) non-financial value propositions such as stewardship and care. I situate these works as agential assemblages that involve artists, audiences, markets, and software objects, and which thereby challenge inherited notions of authorship and private ownership. Against the commodity logic often associated with “crypto art,” the essay reads programmability as a curatorial instrument for imagining more-than-human art ecologies, while also making visible the ways in which speculative tendencies can short-circuit such ambitions. Ultimately, these technologies are described as social experiments that interrogate existing value regimes and test recalibrations of agency within the hyper-financialised Web3 landscape.
Nacereddine Sitouah, Francesco Bruschi, Stefano De Cillis
The passing of the eIDAS amendment marks an important milestone for EU countries and changes how they must manage digital credentials for both public services and businesses. Italy has led in adopting eIDAS, first with CIE and SPID identity schemes, and now with the Italian Wallet (IO app) aligned to eIDAS 2.0. Self-Sovereign Identity (SSI) is a decentralized model born from the success of Distributed Ledgers, giving individuals full control over their digital identity. The current eIDAS 2.0 and its implementation acts diverge from SSI principles, rendering the European Digital Identity Wallet (EUDIW) centralized and merely user-centric, prioritizing security and legal protection over true self-sovereignty. This paper proposes an architecture that enables the use of IT Wallet credentials and services in an SSI-compliant environment through Trusted Execution Environments and Zero-Knowledge Proofs.
With the advent of blockchain technology, the number of proposals has boomed. The network traffic imposed by these blockchain proposals increases the cost of hosting nodes. Unfortunately, as of today, we are not aware of any comparative study of the bandwidth consumption of blockchains. In this paper, we propose the first empirical comparison of blockchain bandwidth consumption. To this end, we measure the network traffic of blockchain network nodes of five blockchain protocols: Algorand, Aptos, Avalanche, Redbelly and Solana. We study the variation over time, differentiate the receiving and sending traffic and analyze how this traffic varies with the number of nodes and validators. We conclude that the transport protocol is the main factor impacting the network traffic, segregating node roles helps reduce traffic and different blockchains are differently impacted by the network size.
ABSTRACT The paper examines the relationship between financial technologies (FIN), institutional quality (GOV), fiscal decentralization, and natural resource management in influencing sustainable development and environmental efficiency among OECD economies between 1990 and 2022. The analysis is conducted using advanced panel diagnostic techniques and the Method of Moments Quantile Regression (MMQR) framework. The empirical results indicate that the positive impact of fiscal decentralization and effective systems of governance on the production of green products will be counted, whereas financial technologies and reliance on mineral resources will lead to adverse consequences for sustainability. These outcomes underscore the paradoxical nature of fintech, which, while enhancing financial accessibility, simultaneously reinforces unsustainable practices in the energy and resource sectors. The study emphasizes the need for OECD economies to harmonize their strategies by advancing green finance innovation, strengthening institutional frameworks, and reducing resource dependence. These economies should reorient fintech development toward sustainability goals through targeted regulation, energy‐efficient digital infrastructure, and alignment with low‐carbon transition strategies.
Ni Putu Eka Apriyanthi, Civica Moehaimin Dhewanty, Putu Desiana Wulaning Ayu, I Made Riyan Adi Nugroho · 5 authors
Konteks penelitian ini didasari oleh meningkatnya kerentanan keamanan yang signifikan dalam ekosistem decentralized finance (DeFi) dan blockchain, khususnya terkait dengan aktivitas kecurangan yang semakin kompleks dan berbiaya tinggi. Metode deteksi tradisional tidak lagi memadai untuk menangani volume transaksi yang masif serta karakteristik dataset yang menunjukkan ketidakseimbangan kelas. Oleh karena itu, penelitian ini berfokus pada evaluasi dan perbandingan kinerja tiga algoritma machine learning utama Regresi Logistik, Random Forest, dan XGBoost untuk mengidentifikasi secara akurat aktivitas kecurangan dalam transaksi blockchain. Data yang digunakan adalah dataset transaksi Ethereum dari platform Kaggle. Isu ketidakseimbangan kelas dalam data diatasi melalui implementasi metodologi SMOTE (Synthetic Minority Over-sampling Technique). Kinerja setiap model dinilai secara komprehensif menggunakan metrik presisi, recall, F1-score, dan Area Under the Receiver Operating Characteristic Curve (ROC-AUC) pada data pengujian. Hasil penelitian menunjukkan superioritas XGBoost di antara ketiga algoritma, dengan mencapai akurasi 99,46%, presisi 99,69%, recall 97,86%, dan skor ROC-AUC 99,97% (25). Keunggulan ini diperkuat oleh keberhasilan XGBoost dalam meminimalkan false positives, yakni hanya 1 kejadian. Kinerja yang melampaui model Random Forest dan Regresi Logistik ini mengindikasikan bahwa metodologi gradient boosting sangat efektif dalam mendeteksi pola perilaku kecurangan yang rumit. Secara keseluruhan, temuan studi ini memberikan kontribusi yang substansial terhadap pengembangan kerangka kerja deteksi kecurangan yang otonom dan tangguh.
Abstract. The Bitcoin blockchain is a distributed ledger of transactions maintained by a network of nodes. The protocol assumes that honest nodes control a majority of the network's computing power. Conventional wisdom suggests that a minority group cannot earn revenue disproportionate to its hashing power, implying that the rational strategy is to remain honest. However, Eyal and Sirer (2013) challenged this view by introducing "Selfish Mining," a strategy that enables a minority pool to earn rewards exceeding its share of computing power. This paper replicates the original study using Monte Carlo simulations to verify the threshold at which this attack becomes profitable. The results confirm that a pool controlling more than 1/3 of the network hashrate can theoretically achieve higher returns than honest mining.
This deliverable presents the design and functional validation of a Blockchain Toolkit that supports decentralised identity, privacy-preserving verification, and trust management mechanisms tailored for emerging 6G ecosystems. The toolkit addresses fundamental limitations of centralised trust infrastructures by replacing hierarchical identity and communication models with ledger-anchored, self-sovereign, and cryptographically verifiable components suitable for large-scale, heterogeneous environments.At its core, the toolkit provides a Self-Sovereign Identity (SSI) architecture based on Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), and Anonymous Credentials (ACs), following W3C standards. This identity layer enables secure authentication, selective disclosure, and privacy-preserving verification without dependence on central authorities. Secure messaging and data exchange are supported through DIDComm-based communication patterns and encrypted, DID-bound storage, enabling trusted interactions across administrative and organisational boundaries.The deliverable further consolidates a set of cryptographic building blocks relevant to privacy and trust in 6G systems. These include zero-knowledge proof–based verification patterns, anonymous credential workflows, and privacy-enhancing mechanisms designed to reduce metadata leakage while preserving auditability. Together, these components enable verifiable compliance and trustworthy coordination in adversarial or untrusted environments.To demonstrate applicability, the Blockchain Toolkit is mapped to representative 6G-aligned use cases. These include specialised consensus mechanisms for dynamic spectrum environments, AI-assisted trust management to address data quality and integrity challenges, and NFT-based resource management for network slicing and dynamic spectrum sharing. In these scenarios, blockchain-based tokens and credentials act as programmable trust anchors, while the toolkit’s identity and cryptographic layers enhance privacy, accountability, and resilience against misuse and collusion.Overall, Deliverable 2.4 provides a coherent and standards-aligned toolkit for decentralised trust in 6G ecosystems. By integrating decentralised identity, privacy-preserving cryptographic verification, secure communication, and application-driven blockchain mechanisms, the toolkit supports scalable, privacy-aware, and verifiable interactions among diverse 6G stakeholders, contributing toward trustworthy next-generation wireless infrastructures.