Blockchain Papers

A. A. Gerasyov, I. N. Efremova, I. S. Arhipova, R. N. Kamalov

The purpose of research. The actual problem in voting systems is not the prevention of fraud and the failure to ensure the integrity of elections. Therefore, the task of building a system of safe and transparent voting is urgent. The purpose of the research is design and develop an information and computing system based on smart contacts for online voting. Methods. The presented system has the form of a decentralized system that can overcome a number of limitations, such as the likelihood of human error, falsification of voting results and problems with accessibility, using blockchain technology, which provides protection against unauthorized access and transparent record keeping. The use of smart contract technology also ensures that the voting process will be automated, transparent and secure. Thanks to the ability to execute self-executing contracts based on predefined rules, smart contracts can eliminate the need for intermediaries, reduce the likelihood of errors and ensure a high degree of accountability. Results. In order to evaluate the effectiveness of the developed system, testing was carried out, after which a comparative analysis was made with other similar systems. The system can ensure that votes are counted accurately and cannot be manipulated, thereby increasing confidence in the results of the voting process. In addition, the system can potentially reduce the costs associated with traditional voting methods and improve accessibility for voters, since it can be accessed remotely via a web interface. In general, the system will be of interest to various organizations and individuals seeking to conduct safe and transparent voting processes. Conclusion. The use of this software product will provide security and convenience when participating in various online voting, reliable storage of votes and the provision of detailed statistics on the conducted voting.

Dong‐Seong Kim, Syamsul Rizal

Integrating machine learning (ML) into blockchain consensus mechanisms enhances efficiency, scalability, and resilience. This study introduces the PoA 2 algorithm, an ML-enhanced Proof of Authority mechanism that optimizes signer selection for improved transaction processing. Simulations with models including Random Forest, Logistic Regression, SVM, K-Nearest Neighbors, Decision Tree, and Gradient Boosting showed significant gains. Random Forest reduced latency tenfold, achieving nearly 1000 transactions per second, with 93.33% accuracy, 100% precision, 86.67% recall, and a 92.86% F1-score. These results demonstrate ML’s potential to enhance blockchain performance, making hybrid blockchain-ML solutions a promising research direction.

Zi Hau Chin, Vishnu Monn Baskaran, Chee Keong Tan, Ian K. T. Tan · 5 authors

Abstract This study examines the potential of BIP-152’s Compact Block Relay (CBR) to enhance the Bitcoin network. This work explores the block propagation efficiency through dynamic prefilling of transactions. In addition, an enhanced CBR model is proposed to reduce superfluous transaction requests, thus improving the block distribution process. The analysis considers the impact of the dynamically prefilled transactions on Bitcoin network scalability, comparing the advantages and disadvantages of this approach. We also conduct a comparative study of fixed-size and dynamically sized prefilled transactions to highlight the importance of adapting to network demands. Prefilling a fixed number of transactions without considering demand can cause inefficiencies and strain the network with unnecessary bandwidth use. Indiscriminate prefilling exacerbates these issues by inflating data packets unnecessarily, increasing latency and reducing network responsiveness. Our research indicates that the proposed solution can significantly reduce the number of round-trips between network nodes by an average of 29.77% and block reconstruction latency by 39.10% when compared with the CBR.

Vedat Coşkun, Naim Ajlouni, OZDENIZCI Busra

No abstract is available for this record.

Elissa Mollakuqe, Hasan Dağ, Vesna Dimitrova

This research paper explores the CONIKS key management system’s security and efficiency, a system designed to ensure transparency and privacy in cryptographic operations. We conducted a comprehensive analysis of the underlying mathematical principles, focusing on cryptographic hash functions and digital signature schemes, and their implementation in the CONIKS model. Through the use of Merkle trees, we verified the integrity of the system, while zero-knowledge proofs were utilized to ensure the confidentiality of key bindings. We conducted experimental evaluations to measure the performance of cryptographic operations like key generation, signing, and verification with varying key sizes and compared the results against theoretical expectations. Our findings demonstrate that the system performs as predicted by cryptographic theory, with only minor deviations in computational time complexities. The analysis also reveals significant trade-offs between security and efficiency, particularly when larger key sizes are used. These results confirm that the CONIKS system offers a robust framework for secure and efficient key management, highlighting its potential for real-world applications in secure communication systems.

Matteo Loporchio, Anna Bernasconi, Damiano Di Francesco Maesa, Laura Ricci

Decentralized applications, the driving force behind the new Web3 paradigm, require continuous access to blockchain data. Their adoption, however, is hindered by the constantly increasing size of blockchains and the sequential scan nature of their read operations, which introduce a clear inefficiency bottleneck. Also, the growing amount of data recorded on the blockchain makes resource-constrained light nodes dependent on untrusted full nodes for fetching information, with a consequent need for query authentication protocols ensuring result integrity. Motivated by these reasons, in this paper we propose the skip index, an indexing data structure that allows users to quickly retrieve information simultaneously from multiple blocks of a blockchain. Our solution is also designed to be used as an authenticated data structure to guarantee the integrity of query results for light nodes. We discuss the theoretical properties of skip indices, propose efficient algorithms for their construction and querying, and detail their computational complexity. Finally, we assess the effectiveness of our proposal through an experimental evaluation on the Ethereum blockchain. As a reference use case, we focus on the popular CryptoKitties application and simulate a scenario where users seek to retrieve the events generated by the service. Our experimental results suggest that the use of skip indices offers a constant multiplicative speedup, thanks to search times that are at most logarithmic within a chosen search window. This allows to reduce the number of visited blocks by up to two orders of magnitude if compared to the naive sequential approach currently in use. • We propose the skip index, a data structure for efficient blockchain data retrieval. • The skip index provides guarantees about the integrity of query results. • We devise efficient algorithms to construct and query skip indices. • Compared to a sequential scan, skip indices offer a constant multiplicative speedup. • Skip indices experimentally provide a speedup of up to two orders of magnitude.

Ranjith Chodavarapu, Rabimba Karanjai, Xinxin Fan, Weidong Shi · 5 authors

Random numbers play a vital role in many decentralized applications (dApps), such as gaming and decentralized finance (DeFi) applications. Existing random number provision mechanisms can be roughly divided into two categories, on-chain, and off-chain. On-chain approaches usually rely on the blockchain as the major input and all computations are done by blockchain nodes. The major risk for this type of method is that the input itself is susceptible to the adversary's influence. Off-chain approaches, as the name suggested, complete the generation without the involvement of blockchain nodes and share the result directly with a dApp. These mechanisms usually have a strong security assumption and high complexity. To mitigate these limitations and provide a framework that allows a dApp to balance different factors involved in random number generation, we propose a hybrid random number generation solution that leverages IoT devices equipped with trusted execution environment (TEE) as the randomness sources, and then utilizes a set of cryptographic tools to aggregate the multiple sources and obtain the final random number that can be consumed by the dApp. The new approach only needs one honest random source to guarantee the unbiasedness of the final random number and a user can configure the system to tolerate malicious participants who can refuse to respond to avoid unfavored results. We also provide a concrete construction that can further reduce the on-chain computation complexity to lower the cost of the solution in practice. We evaluate the computation and gas costs to demonstrate the effectiveness of the improvement.

Carsten Baum, Jens Berlips, W Q Chen, Ivan Damgård · 20 authors

Oblivious Pseudorandom Functions (OPRFs) allow a client to evaluate a pseudorandom function (PRF) on her secret input based on a key that is held by a server. In the process, the client only learns the PRF output but not the key, while the server neither learns the input nor the output of the client. The arguably most popular OPRF is due to Naor, Pinkas and Reingold (Eurocrypt 2009). It is based on an Oblivious Exponentiation by the server, with passive security under the Decisional Diffie-Hellman assumption. In this work, we strengthen the security guarantees of the NPR OPRF by protecting it against active attacks of the server. We have implemented our solution and report on the performance. Our main result is a new batch OPRF protocol which is secure against maliciously corrupted servers, but is essentially as efficient as the semi-honest solution. More precisely, the computation (and communication) overhead is a multiplicative factor <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>o</mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mn>1</mml:mn> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> as the batch size increases. The obvious solution using zero-knowledge proofs would have a constant factor overhead at best, which can be too expensive for certain deployments. Our protocol relies on a novel version of the DDH problem, which we call the Oblivious Exponentiation Problem (OEP), and we give evidence for its hardness in the Generic Group model. We also present a variant of our maliciously secure protocol that does not rely on the OEP but nevertheless only has overhead <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>o</mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mn>1</mml:mn> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> over the known semi-honest protocol. Moreover, we show that our techniques can also be used to efficiently protect threshold blind BLS signing and threshold ElGamal decryption against malicious attackers.

Zia Ullah, Ghassan Husnain, Muhammad Ismail Mohmand, Mansoor Qadir · 7 authors

Abstract With the rapid expansion of the Internet of Things (IoT), cloud storage has emerged as one of the cornerstones of data management, facilitating ubiquitous access and seamless sharing of information. However, with the involvement of a third party, traditional cloud‐based storage systems are plagued by security and availability concerns, stemming from centralized control and management architectures. A novel blockchain‐IoT model that leverages blockchain technology and decentralized storage mechanisms to address these challenges is presented. The model combines the Ethereum blockchain, interplanetary file system, and attribute‐based encryption to ensure secure and resilient storage and sharing of IoT data. Through an in‐depth exploration of the system architecture and underlying mechanisms, it is demonstrated how the framework decouples storage functionality from resource‐constrained IoT devices, mitigating security risks associated with on‐device storage. In addition, data owners and users can easily exchange data with one another through the use of Ethereum smart contracts, fostering a collaborative environment and providing incentives for data sharing. Moreover, an incentive mechanism powered by the FileCoin cryptocurrency is introduced, which motivates and ensures data sharing transparency and integrity between stakeholders. Furthermore, in the proposed blockchain‐IoT model, the proof‐of‐authority system consensus algorithm has been replaced by a delegated proof‐of‐capacity system, which reduces transaction costs and energy consumption. Using the Rinkby Ethereum official testing network, the proposed model has been demonstrated to be feasible and economical, emphasizing its potential to redefine IoT data management.

M. Gayathri, C. Gomathy

The advancements in telematics and communication technology for automobiles have contributed to the development of Vehicular ad Hoc Networks (VANETs). These networks serve as the foundation for Intelligent Transportation Systems (ITS). Communication across various VANET entities is challenging due to the open communication environment and the highly dynamic nature of VANETs. One of the major challenges in VANETs is ensuring stable and secure transmission. To address these factors, several studies have been conducted. The article discusses a clustering algorithm for VANETs that leverages SCVAN-DPSO to create stable clusters and provide secure communication for mitigating malicious nodes. Additionally, Hyperelliptic Curve Cryptography (HECC) with signcryption in blockchain is proposed. This algorithm is designed to identify and mitigate malicious nodes, ensuring robust and secure communication within the network. To verify vehicles in VANETs, this study also suggests a safe and reliable key management method that generates and stores cryptographic keys using blockchain’s distributed ledger technology. By doing so, the risk of rogue nodes is reduced, and a safe, stable connection between vehicles is guaranteed. This work has been implemented using NS 3.34 simulation with the SUMO real-time traffic mobility simulator, and its performance has been evaluated. The proposed algorithm SCVAN-BKM provides a 99.6 % packet delivery ratio for 20 nodes, 0.4 % packet loss, end-to-end delay of 32.65 ms, throughput of 9.522 Mbps, and a cluster lifetime of 105 s. As the number of nodes increases in the communication zone, stable communication is maintained due to the clustering algorithm used in the proposed approach, as cluster formation supports stability in the high-mobility nature of vehicles, while secure communication is ensured using blockchain technology. The findings demonstrate that our approach is more effective and yields better outcomes than existing systems.

Hua-Yi Lin

Recently, with the popularity of Internet of vehicles (IoV), there is an increasing market demand for integrating blockchain technology and smart contracts in electric vehicles. By utilizing distributed blockchain and smart contract technology, it provides data integrity preservation, traceability, and prevention of forgery. These features can be effectively used in the automated charging system. As a result, IoV can utilize blockchain and smart contract technologies to facilitate seamless payment for charging fees, tolls, parking fees, online shopping and other associated expenses without the need for intermediaries. However, since blockchain and smart contracts operate in an open internet environment, there is a risk of tampering with transaction records. Therefore, enhancing security becomes a crucial concern. The main aim of this study is to emphasize the growing significance of securing transactions and smart contracts in an open transmission environment to prevent potential damage or alteration. In order to achieve the implementation of secure smart contracts within a resource-constrained IoV, this study investigates various cryptographic mechanisms and realizes the elliptic curve cryptosystem (ECC) is widely recognized for providing strong security with shorter key lengths compared to other public key cryptography methods. This makes it ideal for environments with limited resources. Furthermore, in order to enhance the performance of smart contracts, this study proposes a cloud server architecture for parallel storage of smart contracts to improve access speed. Additionally, we introduce an automated trading framework for smart contracts that operates without human intervention. Finally, this study uses ECC to ensure the secure transmission of transaction data among the vehicle, base station, and cloud server, as well as to provide mutual verification of identities across all entities involved in the operation. As a result, this study proposes a secure architecture for blockchain and smart contracts that can autonomously initiate transactions while ensuring secure transmission and protection in the IoV.

Inderpreet Singh, Amandeep Kaur, Parul Agarwal, Sheikh Mohammad Idrees

Abstract Most existing e-government services are centralized and rely heavily on human control. This centralized approach makes the system more susceptible to external attacks and compromises data integrity by rogue insiders. Additionally, relying on individuals to monitor and control workflows introduces errors and corruption risks. In order to guarantee security and transparency, this study proposes an automated and decentralized online voting system that makes use of blockchain technology. Compared to conventional voting techniques, it is more efficient and cost-effective, because it eliminates the need of intermediaries. The primary goal of this research is to use blockchain technology to develop a transparent and safe online voting system. In this paper, a decentralized voting system will be developed utilizing ethereum blockchain and smart contracts to ensure the voting process’s integrity. The system can be evaluated with simulated voting data to reflect real-world scenarios, focusing on security, scalability, and user-friendliness. The study also explores potential future enhancements, such as incorporating biometric authentication to further improve accessibility and security. The insights provided will be valuable to policymakers, researchers, and practitioners involved in the development, implementation, and regulation of blockchain-based voting systems.

Francesco Zola, Jon Elduayen, Igor Pallin, Raúl Orduna-Urrutia

Abstract Despite being backed by blockchain technology that promises security, immutability, and full transparency, some cryptocurrencies such as Bitcoin have been used as enablers for many licit and illicit activities such as money laundering, terrorism financing, and ransomware payments. In this scenario, the analysis of the transactions, as well as the entities that have generated them, became a crucial step for law enforcement officer (LEO) investigations. However, the (pseudo) anonymity of the network, the lack of regulatory authority, the employment of anonymizer mechanisms, the evolution of entities’ behavior, and the emergence of new dynamics are just five of the main elements that make this task challenging. At the same time, the huge amount of information to be analyzed can result in a waste of time and resources, slowing the investigations. For this reason, in this work, we present Kriptosare, a tool able to classify entity behaviors belonging to Bitcoin, Bitcoin Cash, and Litecoin. On the one hand, the tool makes use of state-of-the-art machine learning techniques to reduce anonymity in the considered cryptocurrencies. This model extracts behaviors from interactions and dynamics of different known entities involved in the transactions and then predicts the behaviors of new unseen entities. On the other hand, Kriptosare includes a crypto simulator able to create and control a private Bitcoin, Bitcoin Cash, or Litecoin network. This unit allows the simulation of crypto transactions in a controlled way for evaluating hypotheses and/or enriching the input data. The presented tool can be used by LEOs to search and highlight the most important red flag indicators that could suggest criminal behavior, and to support their analysis by optimizing their investigation resources.

Mohammad AlKhanafseh, Ola Surakhi

As digital crime continues to rise, the preservation of digital evidence has become a critical phase in digital forensic investigations. This phase focuses on securing and maintaining the integrity of evidence for legal proceedings. Existing solutions for evidence preservation, such as centralized storage systems and cloud frameworks, present challenges related to security and collaboration. In this paper, we propose a novel framework that addresses these challenges in the preservation phase of forensics. Our framework employs a combination of advanced technologies, including the following: (1) Segmenting evidence into smaller components for improved security and manageability, (2) Utilizing steganography for covert evidence preservation, and (3) Implementing blockchain to ensure the integrity and immutability of evidence. Additionally, we incorporate Long Short-Term Memory (LSTM) networks to enhance steganography in the evidence preservation process. This approach aims to provide a secure, scalable, and reliable solution for preserving digital evidence, contributing to the effectiveness of digital forensic investigations. An experiment using linguistic steganography showed that the LSTM autoencoder effectively generates coherent text from bit streams, with low perplexity and high accuracy. Our solution outperforms existing methods across multiple datasets, providing a secure and scalable approach for digital evidence preservation.

Ziyi Su, Shiwei Wang, Hongliu Cai, Jiaxuan Huang · 7 authors

Current authentication schemes based on zero-knowledge proof (ZKP) still face issues such as high computation costs, low efficiency, and security assurance difficulty. Therefore, we propose a secure and efficient authentication scheme (SEAS) for large-scale IoT devices based on ZKP. In the initialization phase, the trusted authority creates prerequisites for device traceability and system security. Then, we propose a new registration method to ensure device anonymity. In the identity tracing and revocation phase, we revoke the real identity of abnormal devices by decrypting and updating group public keys, avoiding their access and reducing revocation costs. In the authentication phase, we check the arithmetic relationship between blind certificates, proofs, and other random data. We propose a new anonymous batch authentication method to effectively reduce computation costs, enhance authentication efficiency, and guarantee device authentication security. Security analysis and experimental results show that an SEAS can ensure security and effectively reduce verification time and energy costs. Its security and performance exceed existing schemes.

Patricia Callejo, Ignacio Fernández, Marcelo Bagnulo

Abstract Non-Fungible Tokens (NFTs) are becoming increasingly popular as a way to represent and own digital property. However, the usage of NFTs also prompts questions about privacy. In this work, we show that it is possible to use NFTs to retrieve enough information to fingerprint users. By doing so, we can uniquely associate users with blockchain accounts. This would allow linking several blockchain accounts to the same user. This work focuses on the vulnerabilities presented by some popular NFT marketplaces. Since NFTs may have HTML files embedded, they allow the use of fingerprinting techniques if not handled carefully. Finally, we provide recommendations and countermeasures for the different actors in this ecosystem to avoid these kinds of tracking methods and, in doing so, safeguard user privacy.

Shamsa Kanwal, Saba Inam, Zara Nawaz, Fahima Hajjej · 6 authors

IoT enables the emergence and implementation of smart devices to address real-world problems and challenges. Today we are surrounded by various smart devices, such as smart phones, smart homes, smart cars, smart televisions, and smartwatches that assist us in making our lives easier and smoother. IoT is a conglomeration of multiple technologies at various layers to impart the best of ubiquitous and pervasive computing to deliver several benefits in a variety of application sectors such as medicine, agriculture, and industry. In an IoT setting, blockchain technology is used for addressing security challenges and eradicating third-party participation. Utilizing public networks for storing or transmitting health care images poses risks of eavesdropping, data breaches, and unauthorized access. Before uploading medical data to the decentralized network, encryption is required to prevent unauthorized access. The aim of this study is to integrate technologies to ensure transactions are conducted safely and securely. We proposed an IoT-Blockchain system based on chaos encryption scheme using Tinkerbell mapping to ensure medical data integrity and authenticity. The suggested approach is examined to assess performance parameters such as, key space analysis, key sensitivity analysis, Information Entropy (IE), histogram, correlation of adjacent pixels, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index (SSIM). These findings demonstrated that the suggested method is extremely efficient in avoiding security breaches and guaranteeing information integrity.

Damiano Di Francesco Maesa, Laura Ricci, Luca Santarella, Yitbarek Yimame

Centralised cryptocurrency exchanges are often a mandatory first point of entry for most blockchain users. This means that such services have to compete for user attention, often by boosting their attractiveness through questionable behaviours. One of such practices is wash trading, i.e. injecting fake trades to artificially boost the service statistics to portray an unreal users engagement. To protect inexperienced users from dishonest services it is then paramount to develop a set of techniques to identify fraudulent behaviours. This is why, in this paper, we propose a set of automated, yet intuitive analysis that may hint at possible misbehaviour. The goal of these techniques is to be intuitive enough to be understandable by inexperienced users. To this aim we present our experimental results on the real world data of two exchanges, one considered honest and the other suspicious. The outcome is encouraging, as it reveals how dishonest behaviour can be macroscopically detectable, even by the considered intuitive tests.

Maoyi Xie, Ming Hu, Ziqiao Kong, Cen Zhang · 10 authors

Although Decentralized Finance (DeFi) applications facilitate tamper-proof transactions among multiple anonymous users, since attackers can access the smart contract bytecode directly, vulnerabilities in the transaction mechanism, contract code, or third-party components can be easily exploited to manipulate token prices, leading to financial losses. Since price manipulation often relies on specific states and complex trading sequences, existing detection tools have limitations in addressing this problem. In addition, to swiftly identify the root cause of an attack and implement targeted defense and remediation measures, auditors typically prioritize understanding the methodology behind the attack, emphasizing 'how' it occurred rather than simply confirming its existence. To address these problems, this paper presents a novel automatic price manipulation detection and analysis framework, named DeFort, which contains a price manipulation behavior model to guide on-chain detection, multiple price monitoring strategies to detect pools with abnormal token prices, and various profit calculation mechanisms to confirm attacks. Based on behavioral models, DeFort can automatically locate transactions and functions that cause abnormal price fluctuations and identify attackers and victims. Experimental results demonstrate that DeFort can outperform state-of-the-art price manipulation detection methods. Furthermore, after monitoring 441 real-world projects for two months, DeFort successfully detected five price manipulation attacks.

Minfeng Qi, Qin Wang, Zhipeng Wang, Manvir Schneider · 8 authors

In this article, we present the first Systematization of Knowledge (SoK) on constructing Layer Two (L2) solutions for Bitcoin. We carefully examine a representative subset of ongoing Bitcoin L2 solutions (40 out of 335 extensively investigated cases) and provide a concise yet impactful identification of six classic design patterns through two approaches (i.e., modifying transactions and creating proofs). Notably, we are the first to incorporate the inscription technology (emerged in mid-2023), along with a series of related innovations. We further establish a reference framework that serves as a baseline criterion ideally suited for evaluating the security aspects of Bitcoin L2 solutions, and which can also be extended to broader L2 applications. We apply this framework to evaluate each of the projects we investigated. We find that the inscription-based approaches introduce new functionality (i.e., programability) to Bitcoin systems, whereas existing proof-based solutions primarily address scalability challenges. Our security analysis reveals new attack vectors targeting data/state (availability, verification), assets (withdrawal, recovery), and users (disputes, censorship).

Tong Liu, Si-Nga Lai, Xiaochen Yuan, Yue Liu · 5 authors

This article proposes a new digital watermarking mechanism based on the Ethereum blockchain, Smart Contract, and Interplanetary File System (IPFS), with an enhanced Fast Walsh Hadamard Transform (FWHT) algorithm for watermark embedding and extraction. The proposed scheme aims to address the limitations of existing digital watermarking techniques, such as dependence on third-party platforms, by leveraging the decentralization feature of blockchain. The Smart Contract is used to manage the transaction between the parties involved in the watermarking process, while IPFS is used to store the watermark data. The enhanced FWHT algorithm is used to embed the watermark into the host image without affecting its visual quality. The results show that the proposed scheme outperforms the state-of-the-art algorithms in terms of both imperceptibility and robustness. Additionally, it demonstrates that our scheme can effectively resist various attacks. Therefore, our scheme can be a promising solution for image copyright protection, authentication applications, and image trading.

Muhammad Razali, Azrul Amri Jamal, Syed Abdullah Fadzli, Muhammad D. Zakaria · 6 authors

The act of voting is an inherent and essential entitlement that is universally granted to all individuals. Electronic voting, commonly known as e-voting, is a voting method that utilises electronic equipment to facilitate and manage the process of casting and tallying votes. Electronic voting systems are employed to expedite the process of tallying ballots. Furthermore, it will reduce the amount of money needed to pay for counting staff while also reducing human error. The implementation of remote voting would greatly benefit individuals residing at a considerable distance from their designated polling location, as it would afford them the convenience of casting their vote at any given time and from any geographical area. The utilisation of blockchain technology presents novel opportunities for the creation and advancement of innovative digital services. The implementation of Blockchain-Enabled e-Voting has promise in mitigating instances of election fraud and enhancing voter accessibility. The voting process involved the utilisation of electronic devices, such as computers or smartphones, by those who met the criteria for voter eligibility. This method ensured that the voting process maintained the principle of anonymity. The significance of electronic credibility services has seen substantial development, becoming as a crucial element inside the contemporary information era. This project seeks to implement the objective of constructing an electronic voting system utilising blockchain technology. The two-level architecture ensures secure voting without relying on current (non-blockchain) technologies for redundancy. The blockchain-based voting project is made up of two components that work together to make the whole thing operate. One will be the admin, who will be in charge of creating elections, as well as adding candidates to the smart contract elections. The other type of user is the voter, who can vote for their preferred candidate and have their vote recorded on the blockchain to make it tamper-proof.

Sonitema Laia, Ari Moesriami Barmawi

Election systems often face severe challenges regarding security and trust. Threats such as vote falsification and lack of transparency in vote counting have shaken the integrity of elections in various countries. The use of blockchain technology in e-voting has been proposed as an attractive solution to overcome this problem. Several studies use blockchain for the security of electronic voting systems. The existing methods are not resistant against impersonation attacks and man-in-the-middle attacks. This research proposes a new scheme to strengthen a blockchain-based e-voting system. The blockchain used in the proposed method is Ethereum. The proposed scheme uses the modified framework and The Goldreich-Goldwasser-Halevi (GGH) signature scheme. Digital signatures generated using Goldreich-Goldwasser-Halevi (GGH) can strengthen the identity of the message sender so that enemies cannot imitate someone. In this research, the Voter's public key and anonymous ID are used by the Voter to maintain the Voter's anonymity. Based on the experimental results, it can be concluded that the proposed scheme is stronger than the previous scheme because the probability of success in impersonating the sender with the proposed scheme using an impersonation attack and man-in-the-middle attack is small.

Samuel Hand, Alexander Koch, Pascal Lafourcade, Daiki Miyahara · 5 authors

Abstract A zero-knowledge proof (ZKP) allows a prover to prove to a verifier that it knows some secret, such as a solution to a difficult puzzle, without revealing any information about it. In recent years, ZKP protocols using only a deck of playing cards for solutions to various pencil puzzles have been proposed. The previous work of Lafourcade et al. deals with a famous puzzle called Slitherlink. Their proposed protocol can verify that a solution forms a single loop without revealing anything about the solution, except this fact. Their protocol guarantees that the solution satisfies the single-loop condition, by interactively constructing a solution starting from a state that holds a simple single loop, and proceeding via steps that preserve the invariant of encoding a single loop, until the proper solution is reached. A drawback of their protocol is that it requires additional verifications to guarantee a single loop. In this study, we propose a more efficient ZKP protocol for such a puzzle with fewer additional verifications. For this, we employ the previous work of Robert et al., which addressed the connectivity property in a puzzle. That is, we verify that a solution is connected but not split, to be a single loop. Applying our proposal, we construct a card-based ZKP protocol for Moon-or-Sun, which has its specific rule of alternating pattern in addition to the single-loop condition.