Yongxin Zhang, Jiacheng Yang, Hong Lei, Zijian Bao · 7 authors
A verifiable random function (VRF) is a pseudorandom function that enables source verification. By providing a public verification key and accompanying proof with the output, all parties can verify the correctness of the output without interaction. VRF has gained widespread adoption in blockchain applications, including Algorand, Ouroboros, and ChainLink. This article introduces SM2VRF, the first VRF based on the Chinese standard SM2 cryptographic algorithm, and extends it to a batch construction called SM2VRF-B for efficient verification of multiple sources. We showcase the applicability of SM2VRF in an electronic random committee election scenario, where the blockchain is utilized for storing candidate parameters and votes. By employing the Hamming distance, our scheme eliminates the risk of election failure. We provide a security proof for the proposed scheme, followed by an evaluation of the performance of both SM2VRF and SM2VRF-B. We implement our committee election scheme with Ethereum to assess the feasibility and efficiency.
Addressing the shortcomings of traditional voting systems, such as fraud, lack of transparency, and inefficiency, this paper proposes a decentralized voting model based on the Polygon blockchain. The model leverages the inherent characteristics of blockchain, including anti-tampering, transparency, and security, to establish a secure and trustworthy voting mechanism. By utilizing smart contract, the model automates voting, enforces rules, records ballots in real-time, and prevents double voting, thereby significantly reduces human errors and election fraud. It also ensures privacy, eliminates coercion, and realizes on-chain tallying using the Paillier homomorphic encryption. The model is analyzed in terms of security and deployed on Polygon, a sidechain of Ethereum. Comparisons with other schemes demonstrate that this model is also optimized for reducing gas cost.
The rapid adoption of Internet of Things (IoT) devices in smart homes has led to growing security vulnerabilities, primarily due to the limitations of traditional, static access control mechanisms. This paper presents a novel, dynamic access control policy that leverages the immutable and transparent nature of Blockchain technology, specifically Ethereum, along with machine learning algorithms to enhance security measures. By integrating machine learning algorithms like Support Vector Machines (SVM) and Neural Networks, the proposed system can adapt and respond to changing behavioural patterns and potential threats in real time. Additionally, a caching mechanism implemented on the Ethereum Blockchain is introduced to optimize system performance and reduce latency. Experimental results demonstrate significant improvements in access control security, system efficiency, and adaptability. The findings of this paper not only contribute to the advancement of secure access control policies for IoT smart homes but pave the way for future research in integrating Blockchain and machine learning for robust and scalable IoT security solutions.
The advent of Blockchain and its subsequent application in creating Bitcoin has changed the world of finance. The peer-to-peer Blockchain networks, lack a third-party intermediary authority to regulate the transactions, making it vulnerable to various forms of stings. One of the most proliferate uses of crypto transactions is for the ransom payment made by victims of ransomware attacks. Owing to the varied nature of the ransomware attacks, coupled with the decentralized nature of Blockchain, tracking and guarding against such attacks is still a challenge. One way to prevent ransomware attackers from easily benefitting from such crypto transactions is to identify them and avert any payment to those attackers. In this paper, the impact of three ensemble classification algorithms – Random Forest, XGBoost and Balanced Bagging are studied to correctly classify ransomware payments from existing Bitcoin transaction data, to identify the attackers’ addresses and possibly suspend them from taking part in any transactions. The outcomes of the three algorithms are compared with each other based on various indicators. From the experimental results, it could be concluded that Balanced Bagging Classifier demonstrated better performance with an accuracy of 98.41%.
Apurva K. Vangujar, Buvana Ganesh, Alia Umrani, Paolo Palmieri
This article presents a novel e-voting scheme that combines Group Identity-based Identification (GIBI) with Homomorphic Encryption (HE) based on the discrete logarithmic assumption. The proposed scheme uses the Schnorr-like GIBI scheme for voter identification and authorization using zero-knowledge proofs to ensure the anonymity and eligibility of voters. The voter$\textsf {v}_{i,j}$is granted the authorization to cast a valid vote for a single candidate$\textsf {C}_{k}$. The use of distributed ElGamal provides fairness while the use of partial shares for decryption enables individual and universal verifiability without the need for a central authority. The proposed scheme is secure under various scenarios and robust in the random oracle model. The GIBI-HE scheme offers a promising solution for e-voting, providing a sustainable and accessible environment for voters while supporting the unreusability of votes and protecting the privacy of voters.
This research examines the feasibility of implementing blockchain-based electronic voting systems in Morocco to enhance electoral transparency and integrity. The study employs a methodology that combines Distributed Permission Ledger Technology (DPLT) and the Solana blockchain, resulting in a multilayered system. The main findings highlight the effectiveness of blockchain technology in mitigating electoral fraud and manipulation when implemented with precision, underscoring the importance of meticulous design and execution. These findings contribute significantly to discussions surrounding the modernization of electoral processes in the digital age and support the hypothesis that blockchain can address vulnerabilities in traditional voting methods. Moreover, the study marks a significant step toward modernizing elections, preserving democratic principles, and reinforcing the role of technology in addressing persistent electoral challenges, ultimately enhancing accessibility, security, and transparency in elections and strengthening democracy in the digital era.
Pseudorandom Correlation Functions (PCFs) allow two parties, given correlated evaluation keys, to locally generate arbitrarily many pseudorandom correlated strings, e.g. Oblivious Transfer (OT) correlations, which can then be used by the two parties to jointly run secure computation protocols. In this work, we provide a novel and simple approach for constructing PCFs for OT correlation, by relying on constrained pseudorandom functions for a class of constraints containing a weak pseudorandom function (wPRF). We then show that tweaking the Naor-Reingold pseudorandom function and relying on low-complexity pseudorandom functions allow us to instantiate our paradigm. We further extend our ideas to obtain efficient public-key PCFs, which allow the distribution of correlated keys between parties to be non-interactive: each party can generate a pair of public/secret keys, and any pair of parties can locally derive their correlated evaluation key by combining their secret key with the other party’s public key. In addition to these theoretical contributions, we detail various optimizations and provide concrete instantiations of our paradigm relying on the Boneh-Ishai-Passelègue-Sahai-Wu wPRF and the Goldreich-Applebaum-Raykov wPRF. Putting everything together, we obtain public-key PCFs with a throughput of 15k–40k OT/s, which is of a similar order of magnitude to the state-of-the-art interactive PCFs and about 4 orders of magnitude faster than state-of-the art public-key PCFs. As a side result, we also show that public-key PCFs can serve as a building block to construct reusable designated-verifier non-interactive zero-knowledge proofs (DV-NIZK) for NP. Combined with our instantiations, this yields simple and efficient reusable DV-NIZKs for NP in pairing-free groups.
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.
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.
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.
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
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.
Open access
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
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.
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.
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.
Open access
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
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.
Yuping Yan, George Shao, Dennis Song, Mason Song · 5 authors
Blockchain transactions have gained widespread adoption across various industries, largely attributable to their unparalleled transparency and robust security features. Nevertheless, this technique introduces various privacy concerns, including pseudonymity, Sybil attacks, and potential susceptibilities to quantum computing, to name a few. In response to these challenges, innovative privacy-enhancing solutions like zero-knowledge proofs, homomorphic encryption, and stealth addresses (SA) have been developed. Among the various schemes, SA stands out as it prevents the association of a blockchain transaction's output with the recipient's public address, thereby ensuring transactional anonymity. However, the basic SA schemes have exhibited vulnerabilities to key leakage and quantum computing attacks. To address these shortcomings, we present a pioneering solution - Homomorphic Encryption-based Dual-Key Stealth Address Protocol (HE-DKSAP), which can be further extended to Fully HE-DKSAP (FHE-DKSAP). By leveraging the power of homomorphic encryption, HE-DKSAP introduces a novel approach to safeguarding transaction privacy and preventing potential quantum computing attacks. This paper delves into the core principles of HE-DKSAP, highlighting its capacity to enhance privacy, scalability, and security in programmable blockchains. Through a comprehensive exploration of its design architecture, security analysis, and practical implementations, this work establishes a privacy-preserving, practical, and efficient stealth address protocol via additively homomorphic encryption.