Blockchain Papers

Sonali Kothari, Varsha Iyer, Vardhaman Jain, Ruchir Mathur · 5 authors

No abstract is available for this record.

Uzma Jafar, Mohd Juzaiddin Ab Aziz, Zarina Shukur, Hafiz Adnan Hussain

As electronic voting systems become increasingly prevalent, the urgent need for robust security measures to combat evolving cyber threats has never been more critical. This paper introduces a ground-breaking architectural framework Secure-Tech Triad that synergistically combines Blockchain technology with Machine Learning (ML) algorithms and Internet of Things (IoT) capabilities to enhance the security and efficiency of electronic voting systems. This architectural framework utilizes a modified Proof-of-Stake (PoS) Blockchain algorithm, a Random Forest ML model for real-time anomaly detection, and an MQTT protocol for IoT-based data collection to create a more secure, efficient, and responsive voting environment. Rigorous testing and evaluation show that the integrated framework significantly outperforms existing Blockchain-only solutions in key performance indicators, such as security breach detection rate, system latency, and cost efficiency. This integrated approach is the best-performing model, achieving a 97% security breach detection rate, a 30% reduction in system latency (down to 2.3 seconds), and a 25% decrease in operational costs. These results underscore the combined effectiveness of Blockchain, AI, and IoT in enhancing security, speed, and cost-effectiveness. Specifically, the Random Forest algorithm has been instrumental in achieving an exceptional security breach detection rate, while IoT data collection has played a pivotal role in enabling real-time anomaly detection and proactive threat mitigation.

Junha Kang, Seok-Jun Buu

As the popularity of cryptocurrencies grows, the threat of phishing scams on trading networks is growing. Detecting unusual transactions within the complex structure of these transaction graphs and imbalanced data between Benign and Scams remains a very important task. In this paper, we present Disentangled Prototypical Graph Convolutional Autoencoder, which is optimized for detecting anomalies in cryptocurrency transactions. Our model redefines the approach to analyzing cryptocurrency transactions by treating them as edges and accounts as nodes within a graph neural network enhanced by autoencoders. The DP-GCAE model differentiates itself from existing models by implementing disentangled representation learning within its autoencoder framework. This innovative approach allows for a more nuanced capture of the complex interactions within Ethereum transaction graphs, significantly enhancing the ability of the model to discern subtle patterns often obscured in imbalanced datasets. Building upon this, the autoencoder employs a triplet network to effectively disentangle and reconstruct the graph. Reconstruction is used as input to Graph Convolutional Network to detect unusual patterns through prototyping. In experiments conducted on real Ethereum transaction data, our proposed DP-GCAE model showed remarkable performance improvements. Compared with existing graph convolution methods, the DP-GCAE model achieved a 37.7 percent point increase in F1 score, validating the effectiveness and importance of incorporating disentangled learning approaches in graph anomaly detection. These advances not only improve the F1-score of identifying phishing scams in cryptocurrency networks, but also provide a powerful framework that can be applied to a variety of graph-based anomaly detection tasks.

Shaoyu Li, Shanghao Shi, Yang Xiao, Chaoyu Zhang · 6 authors

No abstract is available for this record.

Dhimas Hafid Kurniawan, Parman Sukarno, Aulia Arif Wardana

No abstract is available for this record.

Xingyu Shang, Meiling Dai, Xiaoou Liu

No abstract is available for this record.

Achilleas Spanos, Ioanna Kantzavelou

No abstract is available for this record.

Kiran K. Garimella, Daniel G. Conway

Abstract Building trust in modern business and in social interactions is a critical need as our networks continue to grow and as we engage deeply with unknown people and companies from various parts of the planet. Zero-Knowledge (ZK) technology is a powerful enabler of this trust. It allows a person to demonstrate they know something, have something, or can do something without revealing the actual information or process. We describe the fundamental concepts of cryptography and ZK, their use and limitations, and discuss how ZK technology can be used from a personal as well as a business perspective.

Hao Sui, Jiale Zhang, Bing Chen, Di Wu · 6 authors

No abstract is available for this record.

Jingjing Yang, Jieli Liu, Dan Lin, Jiajing Wu · 7 authors

With the popularity of Non-Fungible Tokens (NFTs), the high value of NFTs makes them a target for phishing scammers, which harms the security and reliability of the Web3 NFT ecosystem. Despite the significance of this issue, there is a lack of systematic research in the area of emerging NFT phishing scams. To address this gap, we are the first to conduct a case retrospective analysis and empirical measurement study of real-world historical NFT phishing scams on Ethereum. We collect and publicly release the first NFT phishing dataset which includes 1,625 NFT phishing accounts and transaction records as of August 2023. We further categorize the existing scams into four phishing patterns and investigate their distinguishable behaviors. Then, we reveal the modus operandi preferences and economic impacts to characterize NFT phishing scams. We find that NFT phishers stole 67,188 NFTs, with a total direct selling profit of${\$}$20.92 million. We also observe that scammers favor certain categories and collections of NFTs, coupled with signs of gang theft. Furthermore, we design a variety of account features for the classification task of NFT phishers based on empirical conclusions. Experimental results on real-world NFT transaction data demonstrate the effectiveness of these features in detecting NFT phishing accounts, and outperform traditional phishing detection methods with 41% average Precision and 44% average Recall.

Jingjing Yang, Wenjia Yu, Jiajing Wu, Dan Lin · 6 authors

In recent years, phishing scams have emerged as one of the most serious crimes on Ethereum. Existing phishing scam detection methods typically model public transaction records on the blockchain as a graph, and then identify phishing addresses through manual feature extraction or graph learning frameworks. Meanwhile, these methods model transactions within a period as a static network for analysis. Therefore, these methods lack the ability to capture fine-grained time dynamics, and on the other hand, they cannot handle the large-scale and continuously growing transaction data on the Ethereum blockchain, resulting in lower scalability and efficiency. In this paper, we propose a two-dimensional streaming framework 2DynEthNet for Ethereum phishing scam detection. First, we cast the transaction series into 6 slices according to block numbers, treating each as a separate task. In the first dimension, we treat transaction features as edge features instead of node features within one task, allowing each transaction to be streamed in 2DynEthNet, aiming to capture the evolutionary features of the Ethereum transaction network at a fine-grained level in continuous time. In the second dimension, we adopt the strategy of incremental information training between tasks, which utilizes meta-learning to quickly update the model parameters under new slices, thus effectively improving the scalability of the model. Finally, experimental results on large-scale real Ethereum phishing scam datasets show that our 2DynEthNet outperforms the state-of-the-art methods with 28.44% average Recall and achieves the most efficient training speed, proving the effectiveness of both temporal edge representation and meta-learning. In addition, we provide an Ethereum large-scale dynamic graph transaction dataset, ETGraph, which aligns with the data distribution in real transaction scenarios without sampling and filtering unlabeled accounts.

IJSREM Journal

In this comprehensive exploration, our paper delves into the intricate implementation of robust authentication and transaction management within the realm of secure voting systems leveraging blockchain technology. Our innovative project stands as a testament to the commitment to privacy and integrity, safeguarding voter interactions through the adept application of advanced cryptographic techniques—all achieved without reliance on a centralized authority. The multifaceted capabilities of blockchain technology are showcased through the seamless facilitation of secure voting processes and the optimization of transaction transfers, collectively contributing to an ecosystem characterized by enhanced security, transparency, and efficiency. Beyond the immediate applications, our study uncovers profound insights into the transformative potential of blockchain within the voting sector, redefining conventional paradigms by introducing unparalleled security measures and transparency to the intricate dynamics of voter interactions. This research not only underscores the feasibility of blockchain in addressing the unique challenges of voting systems but also offers a roadmap for leveraging its capabilities to create a more secure, accountable, and streamlined electoral ecosystem. The paper thus serves as a pioneering contribution, illuminating the path towards a future where blockchain technologies play a pivotal role in shaping the voting landscape. Index Terms: Internet Computer Blockchain (ICP), Blockchain Voting, Decentralized, Rust, Cryptography, SHA-256 algorithm

Suman Majumder, Sangram Ray, Dipanwita Sadhukhan, Mou Dasgupta · 6 authors

Traditional voting systems mainly comprise of paper polling, electronic ballot system (EVM), mechanical devices, etc., and demand the physical presence of the voters. In the new age of digitization, the electronic voting system has come up with a unique facility to cast votes from any discreet place. However, the e-voting system has to face several challenges regarding security and privacy. To overcome such obstructions, blockchain is introduced in e-voting applications that preserve anonymity, security, and consistency of voter-related information with the help of Merkle tree and hash digest. Hence, any discrepancy can immediately be detected whenever the hash values of the respective block have been modified and consequently, the whole block is discarded. In this research, a novel e-voting scheme is proposed following the decentralized service-oriented architecture of Exonum private blockchain, hybrid consensus algorithm, and Elliptic Curve Diffie-Helmen (ECDH) protocol to agree upon a secure session key among different participants. Moreover, the proposed scheme (ECC-EXONUM-eVOTING) employs a zero-knowledge protocol and is customized to work over idemix technologies with a blind signature scheme. Numerous well-known cryptographic attacks are analyzed formally using the probabilistic random oracle model and informally for validating the security strength of ECC-EXONUM-eVOTING. As a result, it is found that the proposed scheme is well-defended against all potential security concerns. Furthermore, the scheme is simulated using both Automated Validation of Internet Security Protocols and Applications (AVISPA) and Scyther tools to demonstrate the proposed scheme is not prone to any security attacks. Finally, it is concluded that the proposed scheme is well-suited for secure e-voting applications.

Sijo K. Joseph, Priyank Pandey, Manju Khari, Kapil Kumar · 5 authors

Voting is a crucial part of democracy because it gives people the chance to voice their opinions, hold elected officials responsible, encourage diversity in the government, cultivate civic participation, and defend themselves from tyranny. Existing electronic voting (e-voting) systems do in fact suffer a number of important obstacles, with security difficulties and a lack of transparency ranking as two of the most important problems. Given the significance of elections in democracies and the likelihood of fraud or other forms of manipulation in electronic voting procedures, these issues are extremely pressing. Systems used for electronic voting heavily rely on software, which might occasionally have vulnerabilities that hackers can exploit. Any weak point in the system can be used to sway elections or jeopardize its security. To address these issues, a strong, secure electronic voting system (EVS), an open system design, impartial audits, and a dedication to inclusion and accessibility are required. For democratic processes to continue to be trusted and the right to vote to be protected, e-voting system integrity must be ensured. It is necessary to create a new Electronic Voting System (EVS) that can offer greater security, speed, and accuracy than the EVS used in the past. The authors of this research suggested a blockchain-based secure EVS. Immutable, transparent, and secure distributed ledger technology named as blockchain. Blockchain used to implement an E-Voting system that is transparent, tamper-proof, and can guarantee the correctness and integrity of the voting process.

Youshui Lu, Bowen Cai, Xiaojun Tang, Lei Liu · 8 authors

Since the introduction of Bitcoin in 2008, blockchain technology has found widespread applications across various domains. While blockchain offers convenience and immense research value, it also raises privacy and security concerns among users and society at large. Notably, numerous studies have demonstrated the vulnerability of blockchain anonymity. Existing solutions based on bloom filters and SGX(Software Guard Extensions) may safeguard users' access patterns but remain susceptible to novel attacks, including protocol-level and side-channel attacks. To address these issues, we propose a Tree-based Oblivious Random Access Protocol (Tree-ORAP) that not only provides access pattern protection in privacy-preserving blockchain systems but also preserves the original blockchain performance. Furthermore, we design a Tree-ORAP State Version Controller to manage state synchronization across nodes in a multi-client blockchain network. We also analyze the system's security and implement a Tree-ORAP prototype, conducting a series of experiments to demonstrate its efficiency and technical feasibility. In summary, our protocol offers enhanced protection for blockchain systems against a wider range of attacks compared to previous methods, all while maintaining superior security performance and equal or better efficiency.

Qifan Mao, Liangliang Wang, Long Yu, Lidong Han · 6 authors

No abstract is available for this record.

Zijian Bao, Debiao He, Qi Feng, Min Luo · 5 authors

A verifiable timed signature (VTS) scheme allows a signature to be time-locked to a known message for a predetermined duration denoted as$\mathsf {T}$. Verifiability ensures that anyone can verify that the time-lock contains a valid signature without completing the computation. In this paper, we introduce a novel VTS construction method based on the RSA group, designed to maintain a constant level of size. This approach serves as an improvement over the previous linear level size construction method (CCS 2020). First, we construct it by using a commitment to a valid RSA signature. This commitment can only be opened to a regular RSA signature after a sequential computation period. Our scheme utilizes a trapdoor verifiable delay function, RSA signatures, and a specialized zero-knowledge proof to instantiate the proposed scheme. We also conduct proofs in three aspects: correctness, soundness, and security. Furthermore, we identify potential applications for VTS and present a simple Bitcoin voting protocol based on an open vote protocol by utilizing VTS. Experimental results show that our scheme is more efficient compared to the construction of VTS (CCS 2020), reducing the signature size by at least 90.5% and lowering computational costs by at least 77%.

Daniela Pöhn, Michael Grabatin, Wolfgang Hommel

Self-sovereign identity (SSI) is a digital identity management model managed in a decentralized manner. It allows identity owners to manage and store their digital identities in a software wallet, for example, on a smartphone, without relying on centralized providers. This approach tries to enhance the security and privacy of digital identities and, thereby, their owners. With the new eIDAS regulation, elements of SSI, such as the wallet, are being pushed onto the market. However, since the model is relatively new, the security threats are still not fully known. This is shown by a brief security analysis of selected existing SSI wallets. In order to get a picture of the known threats, we systematically analyze and categorize related work in the field of SSI and elements applied by SSI. We then evaluate their application to current SSI systems and identify future work.

Abhishek Kandel, Shivam Dhunotiya, Gufran Ali Siddique, Bharat Bhusan · 5 authors

Most of the countries throughout the world is democratic where voting plays crucial role. Government is formed by people via election. People choose their representatives through the election process. Election should be of a trustworthy process and voting system should be secure, tamper-free, and fraud resistant. It is very difficult to build such a system in large democratic country like India which has population about billion. In this paper, new way of electronic voting using blockchain technology i.e., a system that utilize a decentralized and distributed ledger is suggested. Blockchain technology can make the voting system a simple, secure, and reliable. Moreover, it can save time and money and deal with large amounts of data in real time. The main feature of blockchain technology is that a secure hash algorithm is used to safeguard each block of vote.

Nan Sun, Wei Wang, Yongxin Tong, Kexin Liu

No abstract is available for this record.

Anthony Anyanwu, Samuel Onimisi Dawodu, Adedolapo Omotosho, Odunayo Josephine Akindote · 5 authors

This study examines blockchain applications in the USA's government systems, analyzing its effectiveness in public administration and governance. Blockchain technology, initially introduced as the underlying infrastructure for cryptocurrencies, has garnered substantial attention for its potential to transform various sectors, including government systems. This paper provides a comprehensive review of the applications and impacts of blockchain technology in the United States' governmental landscape. As governments worldwide seek innovative solutions to enhance transparency, efficiency, and security, blockchain emerges as a disruptive force with the capacity to reshape administrative processes. The study elucidates the fundamental principles of blockchain technology, emphasizing its decentralized and tamper-resistant nature. It also explores diverse applications within government systems, ranging from identity management and voting systems to supply chain traceability and public finance. The analysis delves into specific use cases, detailing how blockchain enhances data integrity, reduces fraud, and streamlines bureaucratic processes. Furthermore, the paper assesses the implications of blockchain adoption for government operations, highlighting potential benefits such as cost reduction, increased accountability, and enhanced citizen trust. Challenges and considerations, including scalability, interoperability, and regulatory frameworks, are scrutinized to provide a balanced understanding of the technology's limitations. The review extends to the United States' federal and state-level initiatives, examining pilot projects and ongoing implementations that leverage blockchain in areas such as land registries, healthcare data management, and procurement. Insights into the collaborative efforts between public and private sectors are explored, shedding light on the collaborative frameworks essential for successful blockchain integration. Ethical considerations and privacy concerns are addressed within the context of blockchain applications in government, emphasizing the need for robust safeguards to protect sensitive information while harnessing the transformative potential of the technology. This paper synthesizes the current state of blockchain technology in the United States' government systems, offering a nuanced understanding of its applications and impacts. As blockchain continues to mature and gain traction, this review contributes valuable insights for policymakers, researchers, and practitioners, fostering a deeper appreciation for the transformative potential of blockchain in shaping the future of government operations.

Mingshun Ye, Mingdong Tang, Weili Chen

With the rapid advancement of blockchain technology, cryptocurrencies based on blockchain have become a hot topic. However, various issues accompany this development, with phishing scams emerging as a severe financial crime within the blockchain ecosystem, causing significant economic losses to both blockchain platforms and users. In order to address this threat, this essay proposes a phishing scam account identification model based on Bidirectional Long Short-Term Memory Networks (BiLSTM) named BILAM. The model has been validated on the Ethereum platform and has been proven to be effective.This study proposes a novel approach by using transaction records for the first time to construct a time series, and it leverages the BILAM model to learn latent information. Experimental results demonstrate the effectiveness of this method in constructing transaction time series. Moreover, the BILAM model shows excellent performance, with its predictive accuracy significantly surpassing other models, particularly achieving an AUC index of 92.8%.

Mohammad Hajian Berenjestanaki, Hamid R. Barzegar, Nabil El Ioini, Claus Pahl

The employment of blockchain technology in electronic voting (e-voting) systems is attracting significant attention due to its ability to enhance transparency, security, and integrity in digital voting. This study presents an extensive review of the existing research on e-voting systems that rely on blockchain technology. The study investigates a range of key research concerns, including the benefits, challenges, and impacts of such systems, together with technologies and implementations, and an identification of future directions of research in this domain. We use a hybrid review approach, applying systematic literature review principles to select and categorize scientific papers and reviewing the technology used in these in terms of the above key concerns. In the 252 selected papers, aspects such as security, transparency, and decentralization are frequently emphasized as the main benefits. In contrast, although aspects like privacy, verifiability, efficiency, trustworthiness, and auditability receive significant attention, they are not the primary focus. We observed a relative lack of emphasis on aspects such as accessibility, compatibility, availability, and usability in the reviewed literature. These aspects, although acknowledged, are not as thoroughly discussed as the aforementioned key benefits in the proposed solutions for blockchain-based e-voting systems, whereas the considered studies have proposed well-structured solutions for blockchain-based e-voting systems focusing on how blockchain can strengthen security, transparency, and privacy, in particular, the crucial aspect of scalability needs attention.

Niclas Boehmer, Markus Brill, Alfonso Cevallos, Jonas Gehrlein · 6 authors

We provide the first large-scale data collection of real-world approval-based committee elections. These elections have been conducted on the Polkadot blockchain as part of their Nominated Proof-of-Stake mechanism and contain around one thousand candidates and tens of thousands of (weighted) voters each. We conduct an in-depth study of application-relevant questions, including a quantitative and qualitative analysis of the outcomes returned by different voting rules. Besides considering proportionality measures that are standard in the multiwinner voting literature, we pay particular attention to less-studied measures of overrepresentation, as these are closely related to the security of the Polkadot network. We also analyze how different design decisions such as the committee size affect the examined measures.