Blockchain Papers

Akhila Reddy Yadulla, Bhargavi Konda, Vinay Kumar Kasula

Blockchain technology, originally associated with digital currencies, possesses key features such as decentralization, anonymity, robustness, and resistance to tampering, making it an ideal platform for building covert communication channels. This chapter begins by introducing the concept of network covert channels, discussing their definition, historical development, and the architecture of blockchain technology with an exploration of traditional network covert channels. It then highlights the advantages of blockchain-based covert communication channels over conventional methods. The chapter classifies blockchain network covert channels based on several key components. It provides a detailed analysis of the advantages and disadvantages of these channels in terms of covert nature, transmission efficiency, and communication costs. Finally, the chapter addresses existing challenges and limitations within blockchain network covert channels and offers insights into future research directions to improve their efficiency, security, and scalability in the context of secure communication.

Yichen Tan, Yuyang Cheng, Lu Ding, Yong Zhao

Account-based blockchain anonymous systems use non-interactive zero-knowledge proof schemes to protect user privacy but suffer from limited functionality and vulnerability to security attacks. This paper addresses these issues by proposing an optimized scheme that improves multi-signature authentication and enhances system security. We designed and implemented the first multi-signature authentication mechanism for account-based blockchain anonymous systems, supporting secure zero-knowledge operations such as deposits, withdrawals, transfers, and payments. Additionally, we enhanced security by upgrading the zk-SNARK proof scheme to SE-SNARK, significantly increasing the system’s resistance to attacks. Experimental results show that our approach improves security, flexibility, and overall system practicality without compromising efficiency.

T. Vairam, M Srijeimathy, S. Sarathambekai

Public elections are one of the bases upon which a democracy is built in many countries. Blockchain, an evolving and groundbreaking technology can be used to implement the elections. The online voting system along with trust among the voters drastically increases the number of voters participating in the election, in turn defining a true democracy. One of the most promising methods that are available to implement the election using Blockchain is Proof of Work. It is a necessary part of adding new blocks to the blockchain but consumes many computing resources. This is the precise time to move the application from Proof of Work(PoW) to other consensus algorithms that are available. This paper intends to compare the performance of the consensus algorithms based on the Voting system. The application is first built using Ethereum which uses PoW as the consensus algorithm. Then the voting system is built using the hyperledger sawtooth framework which offers PoET and pBFT. To compare the performance of both systems, metrics like throughput and latency are planned to be considered.

Yin Lei, Zhuo Chen, Xiangbo Yuan, Jiahang Sun · 8 authors

Purpose This study aims to propose blockchain-based covert data transmission schemes for modern decentralized applications, addressing the challenges of secure covert communication in resource-constrained environments. The research seeks to enhance the covertness and efficiency of communications in Web3.0 environments, where transparency and decentralized architectures dominate. Design/methodology/approach Two blockchain-based lightweight covert data transmission schemes are proposed. The first scheme involves sharing private keys, while the second scheme avoids sharing private keys to prevent the potential loss of digital currency. Both schemes are designed to be implemented on lightweight devices. The solutions were tested on Raspberry Pi and the Ethereum Testnet to assess their feasibility. Findings The results demonstrate that both schemes improve covertness and efficiency for Web3.0-compatible devices. The second scheme, which avoids sharing private keys, effectively addresses the risk of blockchain private key leakage while maintaining low resource consumption. These findings provide evidence that the proposed solutions are suitable for lightweight devices and offer enhanced security without compromising performance. Originality/value This research offers a novel approach to covert data transmission in Web3.0 environments by leveraging blockchain technology. It provides valuable insights into secure communication methods, contributing to the development of efficient and secure data transmission mechanisms for decentralized applications. The study’s findings highlight areas for future research and practical applications in blockchain-based Web3.0 security.

Authors unavailable

Traditional electronic voting systems face sig-nificant challenges, including susceptibility to tam-pering, lack of transparency, and vulnerabilities in voter authentication.To address these issues, this paper proposes a decentralized e-voting archi-tecture that integrates Aadhaar-based identity val-idation, biometric authentication (fingerprint and facial recognition), and Ethereum blockchain tech-nology for secure and immutable vote recording [1].The system leverages multi-factor authentica-tion to ensure only eligible voters can participate, while blockchain's distributed ledger guarantees tamper-proof storage and real-time auditability of votes.Experimental evaluations demonstrate that the proposed framework achieves a throughput of over 10,000 transactions per second with 99.99% uptime, making it scalable for large-scale elections.By eliminating centralized points of failure and enabling remote voting, this approach signif-icantly enhances electoral integrity, accessibility, and public trust.Future work will explore inte-gration with postquantum cryptography to further strengthen long-term security.

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.

Amit Lathigara, Sunil Soni, Nirav Bhatt, Paresh Tanna · 5 authors

The exponential growth of cryptocurrency transactions has simultaneously increased the complexity and frequency of fraudulent activities. This research presents a novel approach to cryptocurrency transaction fraud detection utilizing Convolutional Neural Networks (CNN), a state-of-the-art deep learning technique. The study leverages a comprehensive dataset of cryptocurrency transactions, employing advanced feature engineering and preprocessing techniques to enhance model performance. Our proposed CNN model demonstrates significant potential in identifying fraudulent transactions with high accuracy and reliability. Key findings reveal the model achieved significant training and validation accuracy, indicating robust generalization capabilities. The performance metrics were validated through detailed loss curve analysis, which demonstrated minimal overfitting and effective learning dynamics. The proposed methodology contributes to the emerging field of blockchain security by offering a sophisticated machine learning framework for real-time fraud detection. Experimental results highlight the CNN model's effectiveness in distinguishing between legitimate and fraudulent cryptocurrency transactions, presenting a promising solution for financial institutions and cryptocurrency platforms.

Satya Subrahmanyam

The rapid growth of digital systems has revolutionized modern life but also introduced critical vulnerabilities in data integrity and security. Blockchain technology, as a distributed ledger system, offers transformative solutions by ensuring trust, transparency, and tamper-resistance in data management. This chapter explores blockchain's theoretical foundations, practical applications, and associated challenges. Key attributes such as decentralization, immutability, and cryptographic security are examined, alongside real-world applications in sectors like healthcare, finance, and cybersecurity. The discussion addresses scalability, energy consumption, and regulatory hurdles, while highlighting innovations like quantum-resistant cryptography and blockchain-AI convergence. Through theoretical insights, case studies, and actionable recommendations, this chapter underscores blockchain's potential to fortify data systems, paving the way for a secure digital future.

Dhruv Kumar Maurya, J Naveen Ananda Kumar, Gaurav Agarwal, Navdeep Singh

An E-voting framework utilizing decentralized technology can establish a secure and transparent environment for elections, where voters can confidently cast their ballots knowing that their votes are final and untampered with. Blockchain's decentralized structure ensures that votes are recorded accurately, preventing interference from external actors. In a protected Evoting framework, each vote becomes part of an immutable, distributed ledger, allowing for peer-to-peer validation of transactions. This ensures that each voice counts as the only, unchanging record. The results can be reported immediately as soon as the voting process is completed. Voting is a critical process carried out in democratic societies, usually through secret voting documents or other similar methods. However, traditional voting systems are often plagued by problems such as voting manipulation, low turnout and logistics challenge. To solve these problems, we propose implementation of decentralized voting platforms that offer advanced security, efficiency and confidence in the election process

Xinxin Fan, Veronika Kuchta, Francesco Sica, Lei Xu

No abstract is available for this record.

Suresh Babu Erukala, Dimitar Tokmakov, Anoosha Perumalla, Rajesh Kaluri · 7 authors

The Internet of Things (IoT) is a disruptive technology that underpins Industry 5.0 by integrating various service technologies to enable intelligent connectivity among smart objects. These technologies enhance the convergence of Information Technology (IT), Operational Technology (OT), Core Technology (CT), and Data Technology (DT) networks, improving automation and decision-making capabilities. While cloud computing has become a mainstream technology across multiple domains, it struggles to efficiently manage the massive volume of OT data generated by IoT devices due to high latency, data transfer costs, limited resilience, and insufficient context awareness. Fog computing has emerged as a viable solution, extending cloud capabilities to the edge through a distributed peer-to-peer (P2P) network, enabling decentralized data processing and management. However, IoT networks still face critical challenges, including connectivity, heterogeneity, scalability, interoperability, security, and real-time decision-making constraints. Security is a key challenge in IoT implementations, including secure data communication, IoT edge and fog device identity, end-to-end authentication, and secure storage. This paper presents an efficient blockchain-based framework that creates a secure end-to-end communication cooperative flow IoT network. The framework utilizes a hybrid blockchain network that collaborates to offer a collaborative flow of end-to-end secure communication from end devices to cloud storage. The fog servers will maintain a private blockchain as a next-generation public key infrastructure to identify and authenticate the IoT's edge devices. The consortium blockchain will be maintained in the cloud and integrated with the permission blockchain system. This system ensures secure cloud storage, authorization, efficient key exchange, and remote protection (encryption) of all sensitive information. To improve the synchronization and block generation, reduce overhead, and ensure scalable IoT network operation, we proposed the threshold signature-based Proof of Stake and Validation (PoSV) consensus. Additionally, lightweight authentication protects resource-constrained IoT nodes using an aggregate signature, ensuring security and performance in real-time scenarios. The proposed system is implemented, and its performance is evaluated using key metrics such as cryptographic processing overhead, consensus efficiency, block acceptance time, and transaction delay. The findings show that threshold signature-based Proof of Stake and Validation (PoSV) consensus, reduces the computational burden of individual signature verification, which results in an optimized transaction latency of 80-150 ms, compared to the previous 100-200 ms without Non-PoSV. Additionally, aggregating multiple signatures from different authentication events reduces signing time by 1.98 ms compared to the individual signature time of 2.72 ms and the overhead of verifying multiple individual transactions is 2.87 ms is significantly reduced to1.46 ms along with authentication delay ranges between 95-180 ms. Hence, the proposed framework improves over existing approaches regarding linear computing complexity, increased cryptographic methods, and a more efficient consensus process.

Goshgar Ismayilov

In this work, we address the evolutionary computation in programmable cryptography on blockchain technologies for the first time in the literature. For that, we propose a novel privacy-preserving and decentralized protocol ([email protected]) where the evolutionary computation model is public while the user inputs/outputs (i.e. the current and next populations) are private. The protocol relies on the transitions between the public-domain (i.e. contract-domain) and the private-domain (i.e. evolutionary-domain) to be secure. We perform an experimental study using two popular benchmark problems to measure the blockchain gas consumption, zero-knowledge proof generation/verification times and zero-knowledge proof size.

Hao Yu, Guijuan Wang, Anming Dong, Yubing Han · 6 authors

With the growth of the Internet of Things (IoT), millions of users, devices, and applications compose a complex and heterogeneous network, which increases the complexity of digital identity management. Traditional centralized digital identity management systems (DIMS) confront single points of failure and privacy leakages. The emergence of blockchain technology presents an opportunity for DIMS to handle the single point of failure problem associated with centralized architectures. However, the transparency inherent in blockchain technology still exposes DIMS to privacy leakages. In this paper, we propose the privacy-protected IoT DIMS (PPID), a novel blockchain-based distributed identity system to protect the privacy of on-chain identity data. The PPID achieves the unlinkability of identity-credential-verification. Specifically, the PPID adopts the Zero Knowledge Proof (ZKP) algorithm and Shamir secret sharing (SSS) to safeguard privacy security, resist replay attacks, and ensure data integrity. Finally, we evaluate the performance of ZKP computation in PPID, as well as the transaction fees of smart contract on the Ethereum blockchain.

Abdullah Aljumah

The rapid proliferation of mobile IoT devices with inadequate security measures has elevated security to a critical concern. Researchers have proposed various systems for vulnerability detection based on conventional frameworks. However, these approaches often face challenges such as high computational costs, limited storage capacity, and slow response times. To ensure robust protection against cyberattacks, modern security solutions must continuously monitor and analyze historical data across the entire IoT network. This paper introduces a distributed security framework for IoT networks, leveraging software-defined networking (SDN), blockchain, and edge computing to efficiently detect and mitigate IoT-based attacks. In the proposed framework, SDN facilitates network-wide data monitoring and analysis, enabling effective attack detection. Blockchain technology ensures decentralized and tamper-resistant attack identification, addressing potential vulnerabilities. Meanwhile, the edge computing paradigm enables real-time attack detection at the network edge, ensuring timely alerts. An experimental evaluation of the proposed framework demonstrates its superiority over traditional approaches in terms of detection accuracy (98.7%), false positive rate (1.2%) and response time (101.1 ms), highlighting its effectiveness in securing IoT networks.

Kode Lakshmi Durga Sindhujasri, Kaduputla Manogna, Sutrayeth Hari Yuktha Nanda, Baligiri Thandava Krishna · 5 authors

Abstract: Elections play a fundamental role in any democratic system, and ensuring their integrity is of utmost importance. Traditional voting methods, such as paper ballots and Electronic Voting Machines (EVMs), suffer from various limitations, including security vulnerabilities, vote tampering, low voter turnout, delays in result processing, and a lack of transparency. Digital voting solutions offer convenience but raise concerns regarding data security and susceptibility to cyber threats. Blockchain technology presents a promising solution to these challenges by providing a decentralized, transparent, and tamperproof framework for conducting elections. As a distributed ledger system, blockchain records transactions in an immutable and verifiable manner, ensuring the integrity of votes. Key features such as decentralization, cryptographic security, transparency, and anonymity make blockchain a robust choice for secure e-voting. In this paper, we propose and implement a blockchainbased e-voting system using Ethereum smart contracts and Web3.js. Our system enforces single-use voting credentials, preventing duplicate votes, and leverages gas fees to mitigate fraudulent voting attempts. Additionally, we develop a web-based application that demonstrates the practical implementation of blockchain voting, discussing its advantages, challenges, and limitations in real-world scenarios

Xingyu Liang, Sen Wang, Ling Xiong, Zhicai Liu · 5 authors

No abstract is available for this record.

Atsuki Koyama, Kentaroh Toyoda, Manato Fujimoto, Thi Hong Tran

The rapid advancement of deepfake technology poses serious risks, including financial fraud and political misinformation, demanding robust methods for verifying image content authenticity. While the C2PA standard and zero-knowledgeproof-based methods provide an image content authenticity proving mechanism, the existing solutions struggle to efficiently support privacy-preserving edits and iterative modifications. To address these challenges, we propose zk-REAL (Zero-Knowledge-Based Protocol for Repeated Image Edit Authenticity Proof with Lattice Hashing), a framework that leverages a lightweight lattice-based hashing scheme within a zero-knowledge proof system. Our approach significantly reduces computational overhead, enabling faster proof generation and smaller proof size even for high-resolution images. Additionally, the updatability of our hashing method supports iterative edits, such as mosaicking or partial modifications, by minimizing redundant computations. Finally, to ensure compatibility with the C2PA ecosystem and conventional signature verifications, we integrate SHA-256 outside of the zero-knowledge circuit. Our evaluation shows up to a 29% reduction in computational costs for proof generation, showcasing the potential of zk-REAL in practical content authenticity verification scenarios.

Polaki Sujatha, A Soujanya, E. J. Priyadharsini, S. Thenappan · 6 authors

This study introduces a secure voting system enhancing voter authentication, data integrity by integrating blockchain technology with an AI-driven biometric scheme, palmprint. The proposed method ensures that fraudulent voting is eliminated and allows trust within the election process in applications of e-governance because of the use of distributed ledger technology and reliable biometric verification. The system leverages the use of smart contracts to enable safe and secure transactions. It makes use of a CNN that has been trained on the PolyU Palmprint Database to check and authenticate palm prints. Simulation results show that the AI model presents phenomenal performance with 99.85% authentication accuracy and 35.42 transaction/sec blockchain free of data integrity issues. The system is also assured of an error-free user experience, excellent scalability, and lower latency. The proposed framework presents an excellent solution towards addressing the apprehensions regarding security and efficacy about the digital voting system that promotes safe and translucent e-governance.

Prajwal Prakash Dalvi, Jayant Mehare, Amol Zade, Amit Gaikwad

Blockchain technology is becoming a great innovation at today's date due to its transparency, security and reliability. With the advancement in every aspect of life blockchain with its decentralized and distributed ledger system aims to provide immutability in digital transaction across the globe with the help of block structure joined together that stored the data in the form of hash. The data stored in block is next to immutable as if tried to change in a single block the hash of every block in the chain will change which makes it easy to identify. Due to its security and transparency the study describes its use in the e-voting system revolutionizing voting system with more security and transparency reducing logistic problem, solving storage issues, solves the problem of using extra man power in the large democracy like India.

Stefan Dziembowski, Shahriar Ebrahimi, Parisa Hassanizadeh

Ensuring the authenticity and credibility of daily media on internet is an ongoing problem. Meanwhile, genuinely captured images often require refinements before publication. Zero-knowledge proofs (ZKPs) offer a solution by verifying edited image without disclosing the original source. However, ZKPs typically come with high costs, particularly in terms of prover complexity and proof size. This paper presents VIMz, a framework for efficiently proving the authenticity of high-resolution images using folding-based zkSNARKs; a type of proving system that minimizes computational overhead by recursively folding multiple evaluations of the same constraints into a compact proof. As a complete proof system, VIMz proves the integrity of both the original and edited images, as well as the correctness of the transformation without revealing intermediate images within a chain of edits--only the final result is disclosed. Moreover, VIMz maintains the anonymity of the original signer and all subsequent editors while proving the authenticity of the final image. We also compare VIMz with the system model in Coalition for Content Provenance and Authenticity (C2PA) from different perspectives and show that VIMz offers higher level of security guarantee by eliminating the need to trust the editing environment. Experimental results show that VIMz performs efficiently in both prover and verifier sides. It can prove the transformations on 8K (33MP,i.e., 100MB) images with up to 13%~25% faster than the competition, while reaching to a peak memory of only 10 GB. Moreover, VIMz has a verification time of under 1 second and achieves succinct proofs of less than 11 KB for all resolutions, which is more than 90% improvement compared to the competition. VIMz's low memory complexity allows for proving multiple transformations in parallel to achieve a 3.5x additional speedup on average.

Mohsen Minaei, Pedro Moreno-Sánchez, Zhiyong Fang, Srinivasan Raghuraman · 8 authors

We propose Data Tumbling Layer (DTL), a cryptographic scheme for non-interactive data tumbling. The core concept is to enable users to commit to specific data and subsequently re-use to the encrypted version of these data across different applications while removing the link to the previous data commit action. We define the following security and privacy notions for DTL: (i) no one-more redemption: a malicious user cannot redeem and use the same data more than the number of times they have committed the data; (ii) theft prevention: a malicious user cannot use data that has not been committed by them; (iii) non-slanderabilty: a malicious user cannot prevent an honest user from using their previously committed data; and (iv) unlinkability: a malicious user cannot link tainted data from an honest user to the corresponding data after it has been tumbled. To showcase the practicality of DTL, we use DTL to realize applications for (a) unlinkable fixed-amount payments; (b) unlinkable and confidential payments for variable amounts; (c) unlinkable weighted voting protocol. Finally, we implemented and evaluated all the proposed applications. For the unlinkable and confidential payment application, a user can initiate such a transaction in less than $1.5$s on a personal laptop. In terms of on-chain verification, the gas cost is less than $1.8$ million.

Juan Diego Morillo Reina, T. J. Mateo Sanguino

Log files are essential assets for IT engineers engaged in the security of server and computer systems. They provide crucial information for identifying malicious events, conducting cybersecurity incident analyses, performing audits, system maintenance, and ensuring compliance with security regulations. Nevertheless, there is still the possibility of deliberate data manipulation by own personnel, especially with regard to system access and configuration changes, where error tracking or debugging traces are vital. To address tampering of log files, this work proposes a solution to ensure data integrity, immutability, and non-repudiation through different blockchain-based public registry systems. This approach offers an additional layer of security through a decentralized, tamper-resistant ledger. To this end, this manuscript aims to provide a solid guideline for creating secure log storage systems. For this purpose, methodologies and experiments using two different blockchains are presented to demonstrate their effectiveness in various contexts, such as transactions with and without metadata. The findings suggest that Solana’s response times make it well suited for environments with moderately critical records requiring certification. In contrast, Cardano shows higher response times, thus making it suitable for less frequent events with metadata that requires legitimacy.

Madhuri S. Arade, Nitin Pise

Abstract Privacy is one of the major security concerns. The zero-knowledge proof enables the transmission of data from the sender to the receiver without disclosing the actual content of the data. The proposed work uses the ZK-STARK (Zero-Knowledge Scalable Transparent ARgument of Knowledge) Algorithm for transaction privacy in the organic jaggery supply chain. The paper emphasizes a detailed mathematical model, involving two key participants: the prover (food processor) and the verifier (distributor). The prover calculates the polynomial for the problem, its composition polynomial, and provides its Merkle proof to the verifier. The verifier conducts queries to confirm and validate the accuracy of the information. Using the fast reed-solomon interactive oracle proofs protocol, the proof is validated. It measures performance as proof generation and verification time, proof size, and throughput. Plans involve increasing the domain size of this algorithm, varying the polynomial interpolation, and evaluating its performance measures by integrating it into Blockchain.