The demand for privacy-preserving machine learning has led to the rise of Federated Learning (FL), where multiple clients collaboratively train a model without sharing raw data. Despite its privacy benefits, FL is vulnerable to Byzantine failures, where malicious or faulty participants inject corrupted updates, threatening model integrity. To address this, a range of Byzantine-resilient aggregation techniques have been proposed, including statistical filters (e.g., Trimmed Mean, Krum), trust-based weighting, cryptographic protocols, and hybrid strategies. This paper presents a systematic literature review (SLR) of these defenses, evaluating their robustness, scalability, and suitability for real-world applications. Challenges such as non-IID data, adaptive attacks, and trade-offs between security and efficiency are critically examined. In addition, we explore emerging trends such as domain-specific defenses, energy-aware FL, quantum-resilient methods, and federated zero-knowledge proofs. A novel classification of hybrid approaches and a standardized benchmarking framework are proposed to guide future research. This review aims to support the development of resilient, efficient and scalable decentralized learning systems in adversarial environments.
As democratic processes increasingly transition to digital environments, safeguarding voter privacy and maintaining electoral integrity have become paramount. This study investigates the application of Zero-Knowledge Proofs (ZKPs) as a cryptographic framework for developing secure and private electronic voting systems. A comparative performance evaluation was conducted between ZKP-based voting protocols and traditional systems, focusing on key metrics such as validation time, privacy leakage index, and memory usage. Quantitative data analysis, supported by statistical methods including mean comparisons and standard deviation assessments, highlights the superiority of ZKP-based systems in minimizing information leakage while maintaining verifiability. Although ZKP protocols introduce higher memory consumption, the trade-off results in substantially enhanced voter anonymity and reduced validation latency. The findings suggest that ZKPs provide a scalable and efficient solution to the dual challenge of transparency and privacy in digital voting infrastructures. This research contributes to the growing body of work on cryptographic voting technologies and underscores the importance of balancing security with performance in the design of future e-voting systems. Keywords: Zero-Knowledge Proofs, E-voting, Cryptography, Privacy, Secure Voting Systems, Digital Democracy, Voter Anonymity, Cryptographic Protocols, Electoral Integrity, Privacy-Preserving Computation
True democracy, strong trust of people in the government and legal transfer of power in the country are possible only when elections are held honestly and correctly. Modern information technologies contribute to innovative restructuring of electoral processes, ensuring optimization of the voting process, minimizing human errors, increasing accessibility for voters. At the same time, the introduction of digital technologies creates significant problems with information security, in particular, possible changes in voting results, manipulation, threats to integrity, availability, confidentiality and anonymity. One of the effective solutions for ensuring information security in electronic voting (e-voting) is blockchain technology. This study is devoted to the problem of developing a website for electronic voting using blockchain technology. Based on the study of scientific literature, the essence, principles, advantages and disadvantages of this technology are revealed. A comparative analysis of the best practices for implementing blockchain technology in the e-voting process is presented. As an example, the process of developing a website for electronic voting using blockchain technology is described: functional requirements for this system are established, the architecture of the software application is described, and a use case diagram is modeled. TypeScript was used as the main programming language for the backend development, Nest.js as a framework, PostgreSQL for data management, and Web3.js for implementing the backend functionality. The frontend was implemented using the TypeScript programming language, the React framework, and Tailwind CSS for interface design. The developed electronic voting platform demonstrates high flexibility and can be implemented for various electoral procedures. Its functionality covers both elections of officials (for example, the rector of the university) and local votes (for example, the election of the head of an academic group), as well as referendums to evaluate the activities of structural units. The data identified during the study can enrich educational materials for students of the 12th Information Technology branch.
Open access
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
In today's world, e-government services are critical for assisting citizens with their daily activities such as visa applications, tax submission, emergency security assistance, and electronic tendering. By combining blockchain and IoT technologies, e-government services can be made far more secure and efficient. Existing e-government applications suffered from a number of limitations, including a lack of privacy and security, increased job processing time, a lack of coordination among various parties, and a lack of services. More specifically, they did not conduct simultaneous investigations into citizen service, employee service, and business service while comparing performance. To conquer these issues, this article proposes a decentralized blockchain-based secure and privacy-preserving smart e-government system that considers the interactions between informers, government, smart contracts, MetaMask-based public and private wallets, Ethereum, and the Interplanetary File System. We investigated the time and cost delays associated with employee, business, and citizen services in the proposed blockchain-based e-government system. This paper provides appropriate security measures for mitigating malware attacks, DDoS attacks, and Sybil attacks. Our simulation results show that the proposed blockchain-based e-government system can reduce the completion time of existing works by at least 33%. Received: 2 November 2024 | Revised: 6 February 2025 | Accepted: 23 May 2025 Conflicts of Interest The author declares that they have no conflicts of interest to this work. Data Availability Statement The data that support this work are available upon reasonable request to the corresponding author. Author Contribution Statement Nahid Imtiaz: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Visualization. Mahfuzulhoq Chowdhury: Conceptualization, Methodology, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration.
The article presents a comprehensive analysis of the transition from traditional centralized digital identity models to an innovative decentralized paradigm based on block-chain technologies and zero-knowledge proofs (ZKP). It highlights the fundamental problems of existing systems that rely on centralized registries, passwords, and social logins. Such approaches create significant vulnerabilities, including risks of data breaches, mass surveillance, and manipulation, as centralized intermediaries act as sole controllers of personal information, depriving users of control over their data. In response to these challenges, the article discusses the concept of Decentralized Identity (DID). This model enables individuals to own, store, and control their digital credentials independently, without involving intermediaries. The key technological components of this ecosystem include Verifiable Credentials (VC), Digital ID Wallets, and Decentralized Identifiers (DID), which are typically stored on a block-chain to ensure immutability and security. A triadic trust model involving the Issuer, Holder, and Verifier is described, allowing data verification without direct contact with the issuing organization. Special attention is given to the concept of Self-Sovereign Identity (SSI) as a specific philosophy within DID that emphasizes user autonomy, data minimization, and privacy by design. Unlike the broader DID concept, in the SSI model, the user makes the final decision regarding the disclosure of their data. A central technology ensuring privacy in decentralized systems is zero-knowledge proofs (ZKP). ZKP allow the validation of the truthfulness of a statement without revealing the underlying information. The article provides a detailed analysis of the benefits of using ZKP in the context of DID, including selective attribute disclosure (e.g., proving legal age without revealing the date of birth), minimizing the amount of shared data, preventing correlation and user activity tracking, as well as creating reputation systems that preserve anonymity. Practical application scenarios such as private electronic voting and confidential medical data protection are examined. The paper also addresses standardization, which is key to ensuring compatibility and widespread adoption of DID solutions. Leading initiatives such as W3C Verifiable Credentials, the Decentralized Identity Foundation (DIF), and projects like Hyperledger Indy and Aries are mentioned. Examples of advanced implementations already in use are provided: Polygon’s zkKYC for private verification in DeFi, the Sismo protocol for creating anonymous reputation badges in Web3, and Evernym’s SSI platform based on Hyperledger Indy. In conclusion, it is emphasized that the combination of DID and ZKP forms a new paradigm for digital identity management focused on security and user autonomy. Despite challenges related to usability complexity, key loss risk, and legal uncertainty, the technology is actively evolving and moving from conceptual to practical application, which may eventually become the foundation for a global sovereign digital identity.
An increasing number of DeFi protocols are gaining popularity, facilitating transactions among multiple anonymous users. State Manipulation is one of the notorious attacks in DeFi smart contracts, with price variable being the most commonly exploited state variable-attackers manipulate token prices to gain illicit profits. In this paper, we propose PriceSleuth, a novel method that leverages the Large Language Model (LLM) and static analysis to detect Price Manipulation (PM) attacks proactively. PriceSleuth firstly identifies core logic function related to price calculation in DeFi contracts. Then it guides LLM to locate the price calculation code statements. Secondly, PriceSleuth performs backward dependency analysis of price variables, instructing LLM in detecting potential price manipulation. Finally, PriceSleuth utilizes propagation analysis of price variables to assist LLM in detecting whether these variables are maliciously exploited. We presented preliminary experimental results to substantiate the effectiveness of PriceSleuth . And we outline future research directions for PriceSleuth.
The rise of Industry 5.0 focuses on merging advanced intelligence, automation, and human-centered teamwork in industrial settings. However, keeping interconnected IoT networks secure is still a challenging problem. This paper proposes a new security framework that combines Blockchain, Federated Transfer Learning, and zero trust network (ZTN) principles to improve IoT security in Industry 5.0. Blockchain is a decentralized ledger that ensures secure data sharing and protects model updates. Federated Transfer Learning allows model training across distributed IoT devices to keep data private. The ZTN approach enforces strict access rules, assuming that no entity is trusted by default. The proposed framework offers a scalable and resilient solution to protect next-generation industrial IoT networks, using Blockchain for data security, transfer learning for adaptability, and ZTN for strict access control. The ZTN architecture strengthens security by checking every access request and keeping the IoT system safe. The experimental results show good performance of the proposed method, with better accuracy, precision, recall, and F1 scores. The model achieved an accuracy of 0.85, 0.88, and 0.87 for learning rates of 0.01, 0.001, and 0.0001, respectively, at 100 epochs. The precision values reached 0.84, 0.87, and 0.86, while the recall scores were 0.82, 0.86, and 0.85, respectively. The F1-scores were recorded at 0.83, 0.86, and 0.85, which confirms the robustness of our model.
Cryptocurrency networks operate on decentralized systems that require efficient performance monitoring for transparency, security, and real-time insights. The establishment of a frontend-only, lightweight dashboard for displaying network metrics linked to popular digital currencies is addressed in this research paper. It collects live data from public APIs and visualizes key performance indicators such as token prices, transaction volume, and ownership distribution using open-source tools like Chart.js. The design emphasizes responsiveness, usability, and data accessibility, targeting users interested in monitoring trends and network health without backend dependencies. This dashboard simplifies data interpretation for end- users and promotes real-time decision-making.
Abstract: Ensuring free and fair elections is the foundation of democratic nations, but conventional voting systems are still susceptible to manipulation, fraud, and inefficiencies. With the advancement of digital infrastructure, electronic voting (evoting) has become a reality, but usually at the expense of transparency and security because of centralized control. Blockchain technology, and specifically Ethereum with its smart contract feature, provides a chance to transform voting systems through decentralization, immutability, and end-to-end verifiability. This suggests a next-generation e-voting system on the Ethereum blockchain with secure voter authentication, transparent vote casting, and smart contract-based automated result counting. Experimental results confirm the system's fraud resistance, scalability for medium-sized elections, and capability to present realtime, tamper-proof election results.
Software defined networking (SDN) increasingly integrates multiple controllers from diverse vendors to enhance network scalability, flexibility, and reliability. However, such heterogeneous deployments pose significant security threats, especially at the east-west interface which is connecting these controllers. Existing solutions are inadequate for ensuring robust protection across multi-vendor SDN environments as most of them are meant to a specific type of attacks, use centralized solution, or designed for homogeneous SDN environments. This study proposes a blockchain-based security framework to address existing security gaps within heterogeneous SDN environments. The framework establishes a decentralized, robust, and interoperable security layer for distributed SDN controllers. By utilizing the Ethereum blockchain with customized smart contract-based checks, the proposed approach enables mutual authentication among controllers, secures data exchange, and controls network access. The framework effectively mitigates common SDN threats such as distributed denial-of-service (DDoS), man-in-the-middle (MitM), false data injection, and unauthorized access. Experimental results highlight the practicality of the solution, achieving a stable throughput of approximately 20 transactions per second with an average authentication latency of 28-40 ms. These results demonstrate that the proposed framework not only enhances inter-controller communication security but also maintains the network performance, making it a reliable and scalable solution for real-world SDN deployments.
A novel electronic voting system (EVS) was developed by integrating blockchain technology and advanced facial recognition to enhance electoral security, transparency, and accessibility.The system integrates a public, permissionless blockchain-specifically the Ethereum platform-to ensure end-to-end transparency and immutability throughout the voting lifecycle.To reinforce identity verification while preserving voter privacy, a facial recognition technology based on the ArcFace algorithm was employed.This biometric approach enables secure, contactless voter authentication, mitigating risks associated with identity fraud and multiple voting attempts.The confluence of blockchain technology and facial recognition in a unified architecture was shown to improve system robustness against tampering, data breaches, and unauthorized access.The proposed system was designed within a rigorous research framework, and its technical implementation was critically assessed in terms of security performance, scalability, user accessibility, and system latency.Furthermore, potential ethical implications and privacy considerations were addressed through the use of decentralized identity management and encrypted biometric data storage.The integration strategy not only enhances the verifiability and auditability of election outcomes but also promotes greater inclusivity by enabling remote participation without compromising system integrity.This study contributes to the evolving field of electronic voting by demonstrating how advanced biometric verification and distributed ledger technologies can be synchronously leveraged to support democratic processes.The findings are expected to inform future deployments of secure, accessible, and transparent electoral platforms, offering practical insights for governments, policymakers, and technology developers aiming to modernize electoral systems in a post-digital era.
Electronic voting (e-voting) has emerged as a transformative technology in the modern digital era. Many countries across the world are using e-voting systems in different types of elections, from political to non-political. One of the primary goals of e-voting is ensuring both verifiability and privacy simultaneously, which we refer to as security. Verifiability is a security feature that guarantees voters can confirm their vote is reflected in the final election result, while privacy guarantees that no one is able to link a vote to the voter who cast it. Verifiability needs to hold only for the duration of the election, whereas privacy needs to extend beyond the election period, even decades after the election. This property, known as everlasting privacy in the literature, ensures that even computationally unbounded adversaries cannot compromise voter privacy, securing elections against future advances in computing, including quantum computing. Researchers have proposed a wide variety of protocols to achieve this ambitious goal in secure e-voting, however, these protocols differ significantly, making the analysis and state-of-the-art complicated. In this thesis, we first address this fragmentation by systematically analyzing all existing e-voting protocols designed to ensure everlasting privacy. We map out the relationships and dependencies among these protocols, evaluate their security and efficiency under realistic assumptions, and identify unresolved challenges in the field. Our work provides a foundational reference for researchers aiming to design secure e-voting systems with everlasting privacy, paving the way for privacypreserving elections in the post-quantum era. Building on these insights, we propose a novel e-voting system that integrates the best practices from prior research while addressing their limitations. Leveraging the Hyperion scheme as a foundation, we develop an enhanced protocol that not only guarantees everlasting privacy but also introduces everlasting receipt-freeness and coercion mitigation. Unlike existing systems like Selene and Hyperion, which rely on computational assumptions for privacy, our protocol offers privacy even against adversaries with unlimited computational power. In secure electronic voting systems with everlasting privacy, the focus is on futureproofing privacy, while sometimes election verifiability relies on the computational soundness of zero-knowledge proofs (ZKP), which are vulnerable to quantum adversaries. Therefore, a key technical challenge is designing e-voting systems with efficient post-quantum cryptographic primitives to secure both privacy and verifiability against quantum attacks. In this thesis, we advance the state of post-quantum ZKPs by focusing on the ZKPs proposed by Jain et al., which are based on the conservative Learning Parity with Noise (LPN) assumption. We optimize the efficiency of these ZKPs, achieve formal security verification using EasyCrypt, and uncover flaws in existing implementations, demonstrating their vulnerability to malicious provers. Additionally, we construct the first code-based ZKP of shuffle, enabling a verifiable and privacy-preserving e-voting protocol with mixing-based tallying. Our e-voting system ensures both verifiability and vote privacy through the computational difficulty of decoding random linear codes, marking it as the first verifiable code-based e-voting system.
Electronic voting systems have long been proposed as a means of modernizing democratic participation by improving accessibility, reducing administrative costs, and accelerating electoral processes. Nevertheless, existing electronic voting architectures frequently rely upon centralized infrastructures that introduce significant challenges concerning transparency, security, auditability, and public trust. Blockchain technology has emerged as a promising alternative capable of addressing many of these limitations through decentralization, immutability, and distributed consensus. Despite considerable research activity, many proposed blockchain voting solutions remain conceptual, while relatively few studies present fully implemented and experimentally evaluated frameworks integrating multiple complementary security mechanisms.This study presents the design, implementation, and evaluation of a secure blockchain-based electronic voting framework built upon Hyperledger Fabric 2.4. The proposed architecture integrates smart contracts, distributed consensus mechanisms, AES-256 cryptographic vote protection, a conceptual zero-knowledge proof layer, and Merkle-tree-based integrity verification within a permissioned blockchain environment. A functional prototype was implemented in Go chaincode and deployed within a simulated regional election scenario representing the four prefectures of Crete, Greece.The study adopts a Design Science Research methodology and evaluates the proposed framework through a series of functional, security, and scalability experiments. The evaluation examined voter eligibility enforcement, duplicate vote prevention, ballot confidentiality, ledger integrity, auditability, and resistance against five distinct attack scenarios, including unauthorized ballot modification, ballot injection, and timestamp manipulation.The findings demonstrate that the proposed framework successfully preserves voter anonymity, prevents duplicate voting, detects unauthorized modifications in all tested scenarios, and enables transparent and independently verifiable election outcomes. While the results confirm the suitability of permissioned blockchain architectures for secure digital elections, several challenges remain, particularly regarding scalability, endpoint security, legal compliance, and large-scale deployment.Overall, this study contributes both a practical implementation and an empirical evaluation of a blockchain-enabled electoral infrastructure, providing insights into the future development of secure digital democratic systems.
A democratic election is a crucial act in each nation, as it determines the country's future for a specific term. Some of the older voting methods, such as Ballot Paper and EVM (Electronic Voting Machine), have disadvantages such as lack of transparency, poor voter turnout, vote rigging, and many others. Using Blockchain technology and Smart Contracts, it is simple to circumvent the flaws of the Ballot system and EVM. Electronic Voting Powered by Blockchain and Smart Contracts outperforms these antiquated voting methods by delivering secure results in less time and at a lower cost. With E-Voting utilizing Blockchain, prices can be lowered, the necessity for Polling stations and the consumption of resources such as EVMs and Ballot Papers may be decreased, and security can be improved by offering End-to-End Encryption and authenticity. This blockchain-powered e-voting can readily acquire trust due to the transaction's transparency, immutability, and difficulty of modification once hosted, as a result of smart contracts. Using OTP Verification and face verification, the suggested solution is a MERN-based web application with a multitude of upgraded authentication and permission techniques. To improve security, this voting data is saved as a transaction in a Blockchain-based distributed ledger using smart contracts.
Abstract: In modern democracies, secure and transparent voting mechanisms are critical for ensuring public trust and electoral integrity. Traditional voting systems often face challenges such as tampering, identity fraud, and lack of transparency. This paper proposes a Blockchain-Based Voting System designed to address these issues by integrating advanced technologies including Zero-Knowledge Proofs (ZKP), InterPlanetary File System (IPFS), and the Polygon Proof-of-Stake (PoS) blockchain. The system incorporates Aadhaar-based identity verification with OTP authentication to ensure that only eligible citizens can vote, while preserving voter anonymity through the implementation of ZKP. All sensitive data, including votes and candidate information, are recorded on the decentralized Polygon network, ensuring immutability and transparency. IPFS is employed for storing large files such as candidate profiles and voting records in a secure and distributed manner. Smart contracts automate the core election functions such as vote casting, validation, and result declaration, thereby minimizing the risk of human error and manipulation. A modular user interface is provided for both voters and election administrators, facilitating real-time monitoring, seamless authentication, and secure participation. By leveraging blockchain’s trustless architecture and privacypreserving cryptographic protocols, the proposed system aims to modernize the electoral process, enhance voter confidence, and strengthen democratic institutions in the digital age.The architecture ensures end-to-end verifiability, making each vote independently auditable without compromising confidentiality. This integration of privacy, security, and scalability offers a robust foundation for next-generation electoral systems.
Abstract—The integrity and transparency of voting systems are fundamental to the democratic process; however, traditional voting mechanisms often encounter issues such as fraud, manipulation, limited transparency, and centralized control. To address these challenges, this research proposes a decentralized voting system utilizing blockchain technology. The system leverages the Ethereum blockchain, smart contracts developed in Solidity, and a React.js-based frontend integrated with Web3.js and MetaMask to ensure secure voter authentication, transparent vote casting, and immutable vote recording. Voter and candidate registrations are managed through decentralized smart contracts, and all transactions are permanently stored on the blockchain, providing public verifiability while preserving voter anonymity. Development and testing were conducted in a simulated environment using Ganache and the Truffle Suite, allowing for extensive validation of system functionalities. Experimental results demonstrate enhanced security, real-time result computation, prevention of double voting, and elimination of any single point of failure. This decentralized architecture significantly improves trust, transparency, and security in electoral processes, offering a scalable and reliable model for the future of electronic voting systems. Index Terms— Blockchain, Decentralized Voting, Ethereum, Smart Contracts, Solidity, Web3.js, MetaMask, Ganache, Truffle Framework, E-voting Systems.
5G is the most recent technology standard for cellular networks, and one of its key elements is the Radio Access Networks (RAN), which furthers the enabling of the 5G basic capabilities: enhanced Mobile Broadband (eMBB), Massive Machine-Type Communication (mMTC), and Ultra-Reliable, Low-Latency Communication (URLLC). To meet the capabilities required by 5G use cases, 5G is distributed, virtualized, and architecturally more complex than previous generations. These capabilities bring benefits but introduce risks and security challenges that must be addressed through controls designed to support and secure 5G services across any operator cloud. Therefore, this paper focuses on studying and evaluating security mechanisms used in RANs. Special attention is given to Distributed Ledger Technologies (DLTs) since they are one of the most studied topics regarding security enhancement. DLTs could bring advantages for improving network security through encryption to protect the information and automate verification and execution of transactions. For this reason, we carried out a systematic review, extracting and analyzing data from 39 papers from 2010 to 2023. Our main results list RAN-related susceptible security dimensions, vulnerabilities, and possible attacks and threats. We also show how DLTs can enhance RANs and present other considered mechanisms to increase RAN security. • The evolution of mobile communication based on openness, softwarization, and virtualization inserts new vulnerabilities into networks. • The increasing number of connected devices, especially IoT ones, is a security attention point in mobile networks. • Various security mechanisms, including Distributed ledger technologies (DLT), may enhance RAN security once these technologies can increase system resilience. • Other security approaches may also address RAN security issues.
Online social platforms for digital communication necessitate an in-depth understanding of their evolving dynamics, especially after the renewal requests brought about by new paradigms, such as Web3. The dynamics within online social networks (OSNs) are influenced by numerous factors, encompassing user behavior, content generation, platform features, and technological advancements, with triadic closure standing out as a prominent and influential element. In this study, we focus on the temporal aspects of triadic closure and its role in the evolution of OSNs, especially after the advent of the Web3 paradigm. By analyzing networks with timestamped links from diverse platforms based on different architectures, including communication, Web3-based, and trade networks, we developed a comprehensive analytical pipeline to support the study of triadic closure patterns. This pipeline includes an algorithm for the census of time-ordered triads, a vector-based model for representing growing networks (growth triadic profile), the identification of triadic closure rules (TERs), and the evaluation of the speed of the formation of closed triads. Our findings reveal significant variations in the impact of triadic closure across different OSNs, marked by diverse growth triadic profiles and varying formation speeds of closed triads as well as diversity in the predictability of evolutionary patterns based on triads. This study not only enhances the comprehension of triadic closure in the temporal evolution of OSNs but also provides valuable insights to be taken into account for the design and administration of online social platforms.
M. K. Ghosh, Swapnil Srivastava, Apoorva Upadhyaya, Raju Halder · 5 authors
Phishing scams on Ethereum have expanded with the surge of the platform, posing substantial challenges due to the sheer similarity in user behaviours and sparse temporal instances. Current methods often fail to tackle these concerns and overlook the temporal sequence of transactions, resulting in suboptimal performance. In this paper, we aim to address these gaps by focusing on the alignment of two aspects: (1) User-specific local temporal behavior, and (2) Divergences from global activity patterns of the network. Hence, we introduce CATALOG (CApturing joint TemporAl dependencies from LOcal and Global user behaviour), a novel representation learning model that jointly captures the local and global user behviours and their correlations by leveraging a dual cross-attention mechanism paired with a bi-directional Masked Language Modelling (MLM) transformer. Our proposed model simultaneously learns from local behavioral shifts, global market trends, and contextually enriched embeddings, effectively distinguishing phishing from non-phishing users while addressing existing research gaps. Extensive experiments on real-world Ethereum transaction data show that our framework improves phishing detection by 7-8% in the F1-Score along with demonstrating the generalization to Ethereum versions 1.0 and 2.0.
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.
Open access
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Abstract: This paper describes a project-specific electronic voting (e-voting) system that integrates blockchain technology with face recognition for robust voter authentication. The goal is to design a decentralized platform in which every vote is recorded immutably on an Ethereum-based blockchain, while face recognition ensures that only a uniquely verified individual can cast a ballot. We detail the system architecture, methodology, and implementation steps, and we compare our approach to other blockchain-based e-voting systems worldwide, including Voatz, Follow My Vote, Zug e-Voting, and Moscow Blockchain Voting. Finally, we reference the open-source repository on which our project is based, demonstrating its real-world applicability and transparency.
This study explores the application of Quadratic Voting (QV) and its generalization to improve decentralization and effectiveness in blockchain governance systems. The conducted research identified three main types of quadratic (square root) voting. Two of them pertain to voting with a split stake, and one involves voting without splitting. In split stakes, Type 1 QV applies the square root to the total stake before distributing it among preferences, while Type 2 QV distributes the stake first and then applies the square root. In unsplit stakes (Type 3 QV), the square root of the total stake is allocated entirely to each preference. The presented formal proofs confirm that Types 2 and 3 QV, along with generalized models, enhance decentralization as measured by the Gini and Nakamoto coefficients. A pivotal discovery is the existence of a threshold stakeholder whose relative voting ratio increases under QV compared to linear voting, while smaller stakeholders also gain influence. The generalized QV model allows flexible adjustment of this threshold, enabling tailored decentralization levels. Maintaining fairness, QV ensures that stakeholders with higher stakes retain a proportionally greater voting ratio while redistributing influence to prevent excessive concentration. It is shown that to preserve fairness and robustness, QV must be implemented alongside privacy-preserving cryptographic voting protocols, as voters casting their ballots last could otherwise manipulate outcomes. The generalized QV model, proposed in this paper, enables algorithmic parametrization to achieve desired levels of decentralization for specific use cases. This flexibility makes it applicable across diverse domains, including user interaction with cryptocurrency platforms, facilitating community events and educational initiatives, and supporting charitable activities through decentralized decision-making.
Francesco Zola, Jon Ander Medina, A. Venturi, Raúl Orduna-Urrutia
Cryptocurrency users increasingly rely on obfuscation techniques such as mixers, swappers, and decentralised or no-KYC exchanges to protect their anonymity. However, at the same time, these services are exploited by criminals to conceal and launder illicit funds. Among obfuscation services, mixers remain one of the most challenging entities to tackle. This is because their owners are often unwilling to cooperate with Law Enforcement Agencies, and technically, they operate as 'black boxes'. To better understand their functionalities, this paper proposes an approach to analyse the operations of mixers by examining their address-transaction graphs and identifying topological similarities to uncover common patterns that can define the mixer's modus operandi. The approach utilises community detection algorithms to extract dense topological structures and clustering algorithms to group similar communities. The analysis is further enriched by incorporating data from external sources related to known Exchanges, in order to understand their role in mixer operations. The approach is applied to dissect the Blender.io mixer activities within the Bitcoin blockchain, revealing: i) consistent structural patterns across address-transaction graphs; ii) that Exchanges play a key role, following a well-established pattern, which raises several concerns about their AML/KYC policies. This paper represents an initial step toward dissecting and understanding the complex nature of mixer operations in cryptocurrency networks and extracting their modus operandi.