Blockchain Papers

Saeed Banaeian Far, Mohammad Reza Chalak Qazani, Azadeh Imani Rad

No abstract is available for this record.

Nelson Lungu, Bibhuti Bhusan Dash, Satyendr Singh, Manoj Ranjan Mishra · 6 authors

Privacy-preserving analytics is indeed a critical enabler for businesses that want to glean insights from sensitive data while protecting individual privacy. Tighter regulation and growing concern over data abuse have, respectively, driven the development of techniques involving zero-knowledge proofs and secure multiparty computation. These systems are set to establish trust boundaries among partner organisations while gently permitting significant information transfers for the decision-making process. The practically verifiable assurance of data secrecy is what makes these protocols particularly attractive in sectors heavily reliant on data analysis, like healthcare, banking, and law enforcement. Such integrated architectures guarantee controlled overhead while delivering high-quality output through cryptographic primitives. Real-life implementations show that it is indeed possible to strike a balance between the efficiency of the system and its security constraints. Enhanced Interoperabillty, along with modularity, will allow more widespread use in diverse ecosystems where insights derived from data drive enterprise innovation alongside robust privacy protections.

Mohammad Arafah, Faisal Aburub, Sabreen Alhariri

The proposed research presents a theoretical investigation into the integration of zero-knowledge proofs (ZKP) within autonomous defense architectures, establishing rigorous mathematical foundations for privacy-preserving security verification in next-generation cybersecurity systems. This study addresses fundamental theoretical challenges in autonomous security verification by developing novel mathematical constructs that enable privacy-preserving proof generation and verification while maintaining formal security guarantees. The research methodology encompasses the development of formal mathematical models for non-interactive zero-knowledge proof systems optimized for autonomous verification environments. These models extend existing theoretical frameworks by introducing novel constructs for proof composition and verification in distributed systems, with particular emphasis on formal security properties including completeness, soundness, and zero-knowledge characteristics.

Fernando Castillo, Jonathan Heiss, Sebastian Werner, Stefan Tai

Blockchain and distributed ledger technologies (DLTs) facilitate decentralized computations across trust boundaries. However, ensuring complex computations with low gas fees and confidentiality remains challenging. Recent advances in Confidential Computing -- leveraging hardware-based Trusted Execution Environments (TEEs) -- and Proof-carrying Data -- employing cryptographic Zero-Knowledge Virtual Machines (zkVMs) -- hold promise for secure, privacy-preserving off-chain and layer-2 computations. On the other side, a homogeneous reliance on a single technology, such as TEEs or zkVMs, is impractical for decentralized environments with heterogeneous computational requirements. This paper introduces the Trusted Compute Unit (TCU), a unifying framework that enables composable and interoperable verifiable computations across heterogeneous technologies. Our approach allows decentralized applications (dApps) to flexibly offload complex computations to TCUs, obtaining proof of correctness. These proofs can be anchored on-chain for automated dApp interactions, while ensuring confidentiality of input data, and integrity of output data. We demonstrate how TCUs can support a prominent blockchain use case, such as federated learning. By enabling secure off-chain interactions without incurring on-chain confirmation delays or gas fees, TCUs significantly improve system performance and scalability. Experimental insights and performance evaluations confirm the feasibility and practicality of this unified approach, advancing the state of the art in verifiable off-chain services for the blockchain ecosystem.

Andrea Flamini

Verifiable credentials (VCs) serve as the digital counterparts to physical credentials, with their security assured through cryptographic methods. The interest on VCs has been renewed by the publication of the European Regulation eIDAS 2.0 that instructs the member states to provide their citizens with a digital wallet (EUDI Wallet) that stores such credentials and that the citizens can use all across the European Union. A great effort has been placed in the definition of common standards that are described in the EUDI Architecture and Reference Framework (ARF), that will be used for the design of the EUDI Wallet. One of the crucial aspects is the identification of the formats and types of VCs supported to be stored in it. The goal of this thesis is twofold: first, to provide a systematic description and analysis of the two VC formats that have been the primary candidates for support by the EUDI Wallet, and second, to propose cryptographic protocols and primitives that facilitate the addition of new features to these credential formats or improve the existing ones. The two VC formats that have been the primary candidates in the development of the EUDI ARF covers (1) the VCs based on hiding commitments that are signed by the issuer using a general purpose digital signature algorithm, and (2) the anonymous credentials generated using the framework of Camenisch and Lysyanskaya, that make use of special digital signature schemes supporting NIZKP that allow one to prove knowledge of a signature created by the issuer. We describe and characterize these formats with a special focus on the cryptographic aspects underlying their design. Then, we introduce a novel cryptographic primitive that can be used to increase the security of the storage of anonymous credentials. We call this primitive multi-holder anonymous credential, and it allows a holder to split an anonymous credential in shares and store them on multiple devices. To present the credential, the holder will need the contribution of a given threshold of the devices. This ensures that as long as an adversary does not compromise enough devices, reaching the threshold, it cannot steal the credential and use it to impersonate the holder. We instantiate a multi-holder anonymous credential that is compatible with the BBS anonymous credential scheme, and we prove its security. Finally, we present a cryptographic commitment scheme whose security is proven in the standard model under assumptions on cryptographic group actions, which are quantum resistant. This commitment scheme, unlike the more efficient commitment based on hashing and salting, supports algorithms and non-interactive zero knowledge proofs to prove predicates about the committed messages, which is an important feature for privacy-preserving applications. To be more specific, when our scheme is used to create VCs, it enables holders to create predicate proofs about the attributes included in their VC, increasing their ability to minimize the disclosure of data.

Beibei Wang, Yang Yi-kun, Wenjie Liu, Lun Xu

Electric vehicles have garnered substantial attention as an environmentally sustainable transportation alternative amid escalating global concerns regarding ecological preservation and energy resource management. While the proliferation of electric vehicles necessitates the development of efficient and secure charging infrastructure, the inherent communication-intensive nature of the charging processes has raised concerns regarding potential privacy vulnerabilities. Our paper introduces a privacy protection scheme specifically designed for electric vehicle charging reservations to address this issue. The primary goal of this scheme is to protect user privacy while maintaining operational efficiency and economic viability for charging providers. Our proposed solution ensures a secure and private environment for charging reservation transactions and subsequent deviation settlements by incorporating advanced technologies, including zero-knowledge proof, a consortium blockchain, and homomorphic encryption. The scheme encrypts charging reservation information and securely transmits it via a consortium blockchain, effectively shielding the sensitive data of all participating parties. Notably, the experimental findings establish the robustness of our scheme in terms of its security and privacy protection, aligning with the stringent demands of electric vehicle charging operations.

Mary C. Lacity, Dan Conway, Kiran Garimella, Erran Carmel

This chapter has two purposes. First, we describe how information system (IS) scholars approach privacy research and summarize major findings. IS scholars are concerned with information privacy and have discovered that individuals have serious information privacy concerns. These concerns, however, do not prevent individuals from disclosing personal identifiable information (PII) to centralized platform providers, a phenomenon called the privacy paradox . We highlight four common explanations for the privacy paradox: privacy calculus, privacy fatigue, trust, and lack of choice. Most IS privacy research, to date, has investigated Web2 applications – which is the foundation for today’s global online economy. With Web2, users rely on centralized platforms for online searching, shopping, banking, data storage, social media, and other services. Second, we introduce scholars to the next frontiers of human privacy with three emerging solutions: decentralization (Web3), multi-party computation (MPC), and zero-knowledge proofs (ZKPs). Web3 applications enhance information privacy compared to Web2 because individuals can access services without disclosing PII to a central authority. The privacy objective is achieved technically through a combination of digital wallets, cryptography, and distributed ledgers (a.k.a. blockchain). Multi-party computation is an innovative approach to calculating information among trusted parties without revealing anyone’s confidential data. It’s a way to answer common questions among trusted parties, such as “Am I paying the same for materials?” and “Does anyone else see suspicious cybersecurity activity on their networks?” Finally, we explain ZKP as a method by which one party can prove to another that they possess a particular identity, item, or piece of knowledge without revealing the specifics of what that identity, item, or knowledge is. Unlike MPC, some types of ZKPs do not require a priori trust; instead, trading partners trust mathematical proofs. Together, Web3, MPC, and ZKPs potentially offer organizations and individuals enhanced online privacy but collectively require more research and field experience.

Go Eun Myeong, Kim Sa Ram

The rise of digital healthcare has intensified concerns over data privacy, particularly in cross-institutional medical data exchanges. This study introduces a blockchain-based protocol leveraging Zero-Knowledge Proofs (ZKP), specifically zk-SNARK, to enable verifiable yet privacy-preserving health data sharing. Built on a permissioned Ethereum blockchain, the protocol ensures that medical data validity can be confirmed without disclosing sensitive content. System implementation involves Python-based zk-circuits, smart contracts in Solidity, and RESTful APIs supporting HL7 FHIR formats for interoperability. Performance evaluations show promising results: proof verification times remained under 100 ms, with average proof sizes below 2 KB, even under complex transaction scenarios. Gas consumption analysis indicates a trade-off—ZKP-enabled transactions consumed approximately 93,000 gas units, compared to 52,800 in baseline cases. Interoperability testing across 10 FHIR-based scenarios resulted in 100% parsing success and an average data integration time of 1.7 seconds. Security assessments under white-box threat models confirmed that sensitive information remains unreconstructable, preserving patient confidentiality. Compared to previous implementations using zk-STARK, this protocol offers a 30% improvement in verification efficiency and a 45% reduction in proof size. The novelty lies in combining lightweight ZKP mechanisms with an interoperability-focused design, tailored for realistic hospital infrastructures. This research delivers a scalable, standards-compliant architecture poised to advance secure digital healthcare ecosystems while complying with regulations like GDPR

Stefanos Chaliasos, Imam Al-Fath, Alastair F. Donaldson

Zero-knowledge proofs (ZKPs) have evolved from a theoretical cryptographic concept into a powerful tool for implementing privacy-preserving and verifiable applications without requiring trust assumptions. Despite significant progress in the field, implementing and using ZKPs via \emph{ZKP circuits} remains challenging, leading to numerous bugs that affect ZKP circuits in practice, and \emph{fuzzing} remains largely unexplored as a method to detect bugs in ZKP circuits. We discuss the unique challenges of applying fuzzing to ZKP circuits, examine the oracle problem and its potential solutions, and propose techniques for input generation and test harness construction. We demonstrate that fuzzing can be effective in this domain by implementing a fuzzer for \texttt{zk-regex}, a cornerstone library in modern ZKP applications. In our case study, we discovered \textit{$10$} new bugs that have been confirmed by the developers.

Yong Chen, Zhaofeng Xin, Bingwang Zhang, Junli Jia

No abstract is available for this record.

Murali Krishna Pasupuleti

Abstract: Algebraic geometry offers a powerful and elegant mathematical framework for the design and analysis of modern cryptographic protocols. This research paper investigates the application of algebraic geometry methods—such as elliptic curves, abelian varieties, and projective algebraic structures—in enhancing the security, efficiency, and scalability of cryptographic systems. By bridging advanced algebraic structures with cryptographic primitives, the study demonstrates how algebraic geometry enables the construction of secure public key protocols, zero-knowledge proofs, and post-quantum resilient schemes. Through theoretical modeling, performance benchmarking, and comparative analysis with classical cryptographic approaches, the paper illustrates the advantages of algebraic geometry in terms of computational hardness assumptions, structural integrity, and potential for innovation in secure communications. The findings contribute to the evolving landscape of cryptography by positioning algebraic geometry as a foundational tool in next-generation cryptographic protocol design. Keywords: algebraic geometry, cryptographic protocols, elliptic curves, public key cryptography, post-quantum cryptography, projective varieties, zero-knowledge proofs, secure communication, mathematical cryptography, abelian varieties

Kun Liu

In the context of global cross-border payments exceeding $150 trillion, traditional mediation architectures, such as SWIFT, face challenges due to high costs, inefficiencies, and fraud risks. However, blockchain technology become an important driver of innovation in cross-border payments with the characteristics of decentralization, real-time and immutable. This paper aims to answer two core questions: Blockchain technology how to improve the efficiency of cross-border payments through smart contracts, cross-chain protocols and other technical features? How to identify and prevent key risks such as private key security and regulatory conflicts? Through the logical framework of "technical basis - efficiency analysis - risk identification - prevention and control strategy", combined with case comparison (such as RippleNet and SWIFT) and quantitative data (such as Stellar network $0.01 / transaction cost). This paper systematically analyzes the role of blockchain in disintermediation, cost compression, and transparency optimization. Besides, the risks of technological vulnerabilities, regulatory fragmentation and market volatility are revealed. Then, this paper proposes a collaborative governance scheme of hybrid architecture, zero-knowledge proof and multilateral regulatory sandbox. Research finding, blockchain technology can reduce cross-border payment time to seconds and reduce costs by more than 90%, but it needs to deal with challenges such as throughput constraints, conflicting regulatory standards and the volatility of digital currencies. It is suggested that future research focus technology optimization, multilateral regulatory collaboration and market ecological integration, provide theoretical and practical support for building an efficient and secure global payment system.

Shunqing Wu, Lifei Wei, Sean M. Wu, Lei Zhang

While blockchain’s immutability ensures data integrity, it also poses significant challenges when dealing with illegal or erroneous data that require modification. The concept of redactable blockchain has emerged, utilizing Chameleon Hash (CH) and subsequent Policy-based Chameleon Hash (PCH) for controlled data editing. However, current redactable blockchain implementations exhibit significant limitations, particularly in their inability to separate data editing from policy modification and their insufficient support for decentralized management of diverse editing operations. To address these issues, this paper initially introduces the concept of Flexible Policy Chameleon Hash (FPCH), which integrates PCH with non-interactive zero-knowledge proofs to enable enhanced policy management flexibility. Moreover, this paper proposes a Redactable Blockchain Framework with Fine-grained Access Control (RBFAC) based on FPCH. The RBFAC framework employs a hybrid cryptographic approach to separate the right of data editing from policy modification. The framework also provides essential functionalities, including editing accountability, key tracking and revocation mechanisms, and policy privacy protection. Finally, experimental evaluations demonstrate that the RBFAC framework maintains acceptable performance overhead while delivering these advanced features. The results indicate that the proposed solution addresses the limitations of existing redactable blockchain systems, offering a more flexible and secure approach to controlled data editing in blockchain environments.

C. Aparna, S. Radha, C. Aarthi, K. M. Karthick Raghunath

ABSTRACT Mobile Ad hoc networks (MANETs) are key for applications in which flexibility and organization are paramount, but the security of such networks entails threats that can exploit the vulnerability of their open architecture, resulting in various attacks. To address such issues, a novel architectural framework is always required. One such framework is introduced, namely, the HoneyFed Secure Architecture (HFSA), which provides the combination of an advanced honey encryption system with federated learning‐based decentralized security to improve the security of MANET. Honey encryption, on the other hand, employs adaptive deception techniques to generate plausible decoy data on decryption failure, employs dynamic key management for tamper resistance, and provides perfect authentication through multi‐factor methods and zero‐knowledge proofs. We found that federated learning offers decentralized model training, where nodes jointly train local models while exchanging progress updates without exposing raw data, enabling 81.4% more detections of emerging threats while preserving data privacy. Using the proposed HFSA approach achieves a 78% protection improvement against attacks and a 71% reduction in unauthorized access. HFSA offers a robust and scalable framework of security that uses continuous learning and adaptation to the vulnerabilities of the MANETs to enhance network resilience.

Maciej Jasiński, Muhammad Yameen Sandhu, Adam Lamęcki, Roberto Gómez‐García · 5 authors

The objective of this article is to demonstrate the applicability of frequency-dependent couplings (FDCs) to the design of self-equalized, generalized Chebyshev microwave bandpass filters (BPFs) in inline coupled-resonator circuit topologies. To this aim, a family of frequency-variant reactive coupling (FVRC) networks with double-zero single-pole (DZSP) characteristics is exploited, where the zeros can be either positioned at the imaginary axis or as a pair of real zeros. Thus, flattened-group-delay sharp-rejection microwave BPFs with in-band equi-ripple-type response and close-to-passband transmission zeros (TZs) can be realized while avoiding more-complex cross-coupling structures. The theoretical foundations of the proposed class of DZSP FVRC networks for the flexible allocation of the two zeros in the complex plane, as well as different circuit variants for their implementation, are presented. Two design examples of self-equalized fifth-order microwave BPFs in lumped-element/transmission-line and 3-D technologies centered at 1.5 and 9.98 GHz, respectively, are also shown, in which different structures for the DZSP FVRC networks are adopted. In both BPF designs, their coupling-matrix-based-synthesis responses obtained from solving an inverse structured nonlinear eigenvalue problem and electromagnetically (EM)-simulated results are provided. Furthermore, for practical validation purposes, a proof-of-concept microstrip prototype of the first BPF design example is built and tested. To the best of the authors’ knowledge, this is the first time that self-equalized, generalized Chebyshev microwave BPFs in inline schemes—i.e., without cross couplings—are experimentally verified.

William J Buchanan

Some of our current public key methods use a trap door to implement digital signature methods. This includes the RSA method, which uses Fermat's little theorem to support the creation and verification of a digital signature. The problem with a back-door is that the actual trap-door method could, in the end, be discovered. With the rise of PQC (Post Quantum Cryptography), we will see a range of methods that will not use trap doors and provide stronger proof of security. In this case, we use hash-based signatures (as used with SPHINCS+) and Fiat Shamir signatures using Zero Knowledge Proofs (as used with Dilithium).

Zhishuo Zhang, Yongjian Liao, Chunjiang Wu, Yating Huang · 6 authors

To provide the encrypted data with public tamperproof and traceability, in this paper, we first explore and discuss that the alone signature attached to the encrypted data is in a low coupling state with the ciphertext which gives rise to signature substitution attack destructing assurance of the encrypted data. Then we propose a new cryptographic primitive called Secret-Embedded Ciphertext Signature of Knowledge (SECTSoK). And then give the general construction of SE-CTSoK in Schnorr identification scheme form over groups. The proposed SE-CTSoK is not only a signature for the ciphertext to make the ciphertext tamper-proof, but also a zero-knowledge argument of the ciphertext random secret to give the proof that the ciphertext secret is embedded in SE-CTSoK for sure without revealing it. Furthermore, we introduce the standardized definition of the Irreconfigurability model for the ciphertext signature to cover any type of the signature substitution attack, and then we give the formalized proof to our proposed SE-CTSoK in Irreconfigurability model which demonstrates that the ciphertext with the corresponding SE-CTSoK can only be correctly traced and confirmed to the ciphertext generator.

Lixin Song, Yu Jie, Jie Zhou

The electronic voting system guarantees the impar-tial, confidential and secure execution of the voting process. However, most existing electronic voting schemes are tailored to specific voting rules and employ particular encryption tools to ensure swift elections under predefined conditions. This often limits their adaptability to accommodate diverse voting modes. Addressing these challenges, the SecureVote scheme proposed in this article incorporates score-based voting rules, supports five different voting rules, thereby catering to a wide range of real-world electronic voting scenarios. The Secure Vote can ensure the privacy and anonymity of the scheme through homomorphic encryption and privacy set intersection technology, and at the same time use non-interactive zero-knowledge proofs to ensure the verifiability of voting, and is better than the scheme with a central trust entity in terms of communication, efficiency and rationality. Finally, we illustrate the nature and efficiency of the scheme through safety proofs and experiments.

Manuel J. C. S. Reis

The rapid expansion of 5G networks and edge computing has amplified security challenges in Internet of Things (IoT) environments, including unauthorized access, data tampering, and DDoS attacks. This paper introduces EdgeChainGuard, a hybrid blockchain-based authentication framework designed to secure 5G-enabled IoT systems through decentralized identity management, smart contract-based access control, and AI-driven anomaly detection. By combining permissioned and permissionless blockchain layers with Layer-2 scaling solutions and adaptive consensus mechanisms, the framework enhances both security and scalability while maintaining computational efficiency. Using synthetic datasets that simulate real-world adversarial behaviour, our evaluation shows an average authentication latency of 172.50 s and a 50% reduction in gas fees compared to traditional Ethereum-based implementations. The results demonstrate that EdgeChainGuard effectively enforces tamper-resistant authentication, reduces unauthorized access, and adapts to dynamic network conditions. Future research will focus on integrating zero-knowledge proofs (ZKPs) for privacy preservation, federated learning for decentralized AI retraining, and lightweight anomaly detection models to enable secure, low-latency authentication in resource-constrained IoT deployments.

Lulu Li, Junyu Wang, Wei Wang, Yi Xu · 7 authors

The collection and application of health care data are crucial for advancing research and improving healthcare. However, privacy and security concerns, particularly with sensitive data, pose significant challenges. Traditional identity-based verification systems, which rely on centralized servers, struggle in medical contexts due to regional data management complexities and the vulnerabilities of centralized models. In this paper, we propose MedZKChain, a privacy-preserving health care device verification system designed to address these challenges. By combining blockchain technology with zero-knowledge proofs, MedZKChain enables decentralized device attribute verification while ensuring data integrity and privacy. The system provides a solution for managing the access of medical records in different regions. MedZKChain leverages decentralized storage to reduce blockchain burden and uses zero-knowledge proofs to allow for secure verification and access authorization without revealing sensitive data. Experimental results demonstrate that, when authorized querying 1,500 patient data records, the proof size in MedZKChain remains less than 100 KB, the proving time is less than 3 seconds, and the verification time is below 0.8 seconds. These results highlight the system efficiency, scalability, and its effectiveness in enabling decentralized, verifiable.

Srishty Sharma, Priyanka Chaudhary, Ananya K Nair, Priyanka Dadhich

Due to their frequent fragmentation and silos, healthcare information systems continue to pose significant challenges in the management of patient data, interoperability, and privacy protection. Current healthcare information exchange mechanisms suffer from critical vulnerabilities such as potential data breaches, inconsistent patient identification, and limited patient control over personal health information. This paper presents a new blockchain-based framework for the Universal Health ID, addressing the systemic limitations of such approaches by providing a decentralized and cryptographically secure access mechanism to patient records. Based on a hybrid architecture that utilizes advanced zero-knowledge proof protocols, designed and implemented a comprehensive system for patient identification and data sharing. The proposed methodology would integrate distributed ledger technology with the sophisticated application of encryption techniques to support end-to-end data integrity, granular access controls, and patient-centric management of information. An empirical analysis revealed that data security metrics improve by 98.7%, and a majority, 92% of health professionals, reported enhanced interoperability, with 85% of the patients exhibiting increased confidence in their data being private. Our findings conclusively prove that blockchain-based universal health ID systems represent a transformative approach to solving modern-day challenges in managing healthcare data, offering scalable, secure, and patient-centric solutions for global health ecosystems.

Harshit Mula, Vedant Shirish Utage, S. Ganesh Kumar, Syed Ismail Abdul Lathif · 5 authors

In a time where professional and social networks are at the forefront of connectivity, the shortcomings of existing platforms come to the fore, particularly for specialist communities in the technical sector. These networks tend to lack in establishing trust, confidentiality, and quality of interaction. This paper proposes an innovative platform that addresses the specific needs of technical experts and enthusiasts via strong verification and decentralized trust systems. Utilizing state-of-the-art technologies such as Large Language Models (LLMs), zero-knowledge proofs (zkSNARKs), and blockchain integration, GeeksGather provides a setting in which users are verified on the basis of actual expertise without sacrificing privacy. By using LLM-created quizzes, privacy-preserving development verification, and implementation with such tools as Scroll blockchain and Guild.xyz, GeeksGather maintains both transparency and user autonomy. The architecture of the system fosters meaningful, secure, and high-quality interaction by means of token-gated groups and encrypted communication channels. This article introduces the design, deployment, and future implications of GeeksGather for professional digital networking to come-raising the bar in trust, decentralization, and data integrity.

Seun Adeoye

The fast digital transformation of healthcare systems has brought electronic health records (EHRs) into wide usage to enhance patient care and provide better data access. The need for better security grows more pungent as cybersecurity and quantum computing threats against traditional cryptographic approaches become more prevalent. This paper develops a Blockchain-Enabled Post-Quantum Cryptographic framework for protecting EHRs. The combination of blockchain technology with PQC safeguards healthcare data through decentralised distribution, unalterable data storage, and complete system transparency, and PQC prevents anticipated quantum computing vulnerabilities. Security and privacy improve in the proposed framework by combining lattice-based cryptography, hash-based signatures, and zero-knowledge proofs. Smart contracts enable the framework to enforce access policies and maintain regulatory compliance through its functionality. A performance analysis of this framework shows it can effectively secure EHRs through efficient and scalable implementation. The research demonstrates that PQC and blockchain offer healthcare organisations a secure protection solution for EHRs that fights evolving cyber threats within trustworthy healthcare systems.

A. Althaf Ali, M. A. Gunavathie, V. Srinivasan, M. Aruna · 6 authors

The integration of smart city applications with healthcare has revolutionized patient monitoring and medical data management. However, ensuring the privacy and security of Electronic Health Records (EHR) remains a critical challenge, especially in IoT-based environments with resource-constrained devices. This paper proposes a novel Blockchain-Enabled Federated Learning (BFL) framework to enhance privacy preservation in EHR processing. The proposed framework leverages zero-knowledge proofs (ZKP) for authentication and homomorphic encryption for secure computation, ensuring robust data security without exposing raw patient data. Federated Learning (FL) enables decentralized model training across IoT devices, reducing privacy risks while maintaining data utility. Additionally, blockchain technology enhances the integrity and transparency of EHR transactions by creating a tamper-proof ledger. The performance of the proposed BFL framework is evaluated based on data utility, model accuracy, execution time, and scalability across varying sizes of EHR datasets. Results demonstrate improved privacy preservation, reduced computational overhead, and enhanced model efficiency, making it a promising approach for secure and privacy-aware IoT-based smart healthcare systems.