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2,071 results · page 7 of 87
Prudhvi Raj Attuluri, George Steven Muvva, Avvari Likitha, Pusapati Sai Krishnam Raju · 5 authors
No abstract is available for this record.
О. І. Baranovskyi
Introduction. The significance and relevance of researching the development of the cryptocurrency market are driven by the digitalization of society, its penetration into all areas of life, including the financial sector, the transformation of its regulation, the need to prevent the cryptocurrency market from operating outside the legal framework, and mitigating the negative consequences of cryptocurrency use. The purpose of the article is to clarify the essence of cryptocurrency, identify its determining factors, and explore the key issues in its functioning. Results. Various approaches to interpreting the concept of "cryptocurrency" have been analyzed. The essence of cryptocurrency, its distinctive features, attractiveness, and associated negative processes have been identified. The author's perspective on the nature of cryptocurrency is presented. The patterns and peculiarities of cryptocurrency market regulation in different countries have been characterized, identified the negative consequences of the absence. The importance of financial monitoring in this sector has been emphasized. Conclusions. Despite the advantages and disadvantages of cryptocurrency implementation, it is essential to establish a well-structured regulatory system, clearly define the regulatory authority, determine the issuance process, usage, application areas, and taxation framework; establish the relationship between cryptocurrency and other financial assets; and ensure state oversight of this sector, including the appropriate development and enhancement of financial monitoring mechanisms.
Alanoud M. Almhlbdi, Norah D. Altowairqi, Areej Alshutayri, Rehab Qarout
Identifying hidden payloads in images has become increasingly critical as steganography continues to challenge traditional security measures. This paper introduces a deep learning framework for both the detection (binary classification) and fine-grained classification (multi-class) of steganographic payloads embedded using Least Significant Bit (LSB) techniques. The proposed system distinguishes between benign images and stego images containing five different payload types: HTML, JavaScript, PowerShell, URLs, and Ethereum-related data. To achieve this, we systematically evaluate various architectures, including a custom Convolutional Neural Network (CNN), hybrid CNN-GRU and CNN-LSTM models, and a Vision Transformer (ViT) at different input resolutions using 5-fold cross-validation. Our experiments reveal a critical finding: image resizing significantly degrades detection performance, as subtle LSB artifacts are often corrupted. While our custom CNN model achieved the highest mean cross-validation accuracy (0.9702), the hybrid CNN-GRU model demonstrated superior generalization on the held-out test set and external dataset, achieving a multi-class accuracy of 0.98 on the testset and 0.97 on the external. This result highlights the advantage of combining the CNN’s spatial feature extraction with the GRU’s ability to model sequential dependencies for robust payload identification on unseen data.
Yizhong Liu, Dongyu Li, Jianwei Liu
No abstract is available for this record.
Mingdi Shen, Tianqi Zhou, Chen Wang, Shijia Hong
No abstract is available for this record.
Willy Quach, LaKyah Tyner, Daniel Wichs
No abstract is available for this record.
Çağlayan Sancaktar, Ahmet Sayar
No abstract is available for this record.
Anubha Jain, Emmanuel S. Pilli
No abstract is available for this record.
S.B. Gurumurthy, Deepa Yogish
No abstract is available for this record.
Souheib Yousfi, Marwa Chaieb
No abstract is available for this record.
Islambek Saymanov, Iouliia Skliarova, Boykuziev Ilkhom, Orif Allanov
No abstract is available for this record.
Chuming Guan, Zeyu Yu, Junlang Zhang, Jiawen Fang · 5 authors
No abstract is available for this record.
Lukman Adewale Ajao, Buhari Ugbede Umar, Henry Ohiani Ohize, Eustace M. Dogo · 6 authors
The prevalence of political interference during election processes remains a significant challenge to the free, fair, and credible conduct of general elections. This election event is crucial as a pillar of democratic governance in any democracy, with the potential for unfitting disturbance and chaos, such as multiple votes, illicit voting, and malicious actors that can be exploited electronically to disrupt voting or affect vote counts. However, this research proposed to develop a secure, smart, verifiable e-voting system (SSVEVS) that can offer an authenticated end-to-end tally voting system, a top-secret ballot election system, and confidence in overall election integrity. The proof of this smart and secure electronic voting system utilizes a 64-bit quad-core ARM Cortex-A76 processor, integrated with multimodal biometric (facial and fingerprint) authentication systems, programmed with a deep-learning image processing (DLIP) algorithm to optimize image detection and recognition. Also, an Ethereum blockchain technology (EBT) with a homomorphic encryption algorithm was implemented on the system to ensure that the original information record is maintained, immutable, tamper-resistant, and transparent throughout the electoral process, and stores the information in a decentralized database application. The system achieved 1,424.501 TPS for 10,000 transactions with a mining time of 7.02 seconds. The biometric (facial and fingerprint) authentication achieved a False Acceptance Rate (FAR) and False Rejection Rate (FRR) of 0.00% respectively. The True Acceptance Rate (TAR) is 100%, with a false image template of 0.04% true identification rate (TPIR).
Akwesi Kusi, Dominic Asoma
Blockchain technology has been envisioned as an emerging facilitator of auditable, transparent, and secure electronic voting (e-voting) systems to overcome issues with traditional and electronic voting systems. However, preserving data integrity, offering voter privacy, and scalability in blockchainbased e-voting systems are persistent issues. In this systematic literature review of peer-reviewed research articles from 2018 to 2025, this paper explores cryptographic schemes, architecture designs for blockchain-based e-voting systems, and solutions for scalability. By taking an PRISMA-congruent structured research methodology approach, nine core studies are reviewed to discuss Zero Knowledge Proofs and blind signature schemes for maintaining privacy conservation, blockchain immutability to maintain integrity, and layer-2 scaling solutions to bypass throughput bottlenecks. Conclusions suggest that although transparency and audita-bility are elevated with applications of blockchain technology, implementation for massive-scale elections remains in its nascent stage and requires development in privacypreservation cryptographic schemes and scalable architecture designs. As a review paper, it compiles an updated summary of the status of the landscape of blockchain-based e-voting systems and highlights existing knowledge gaps and proposes research directions for developing secure, scalable, and privacy-respecting digital elections.
Hanh Tran Thi, Nghi Nguyen Van, Ngoc Le Anh, Hung Dinh Van
No abstract is available for this record.
Augustin Bariant
No abstract is available for this record.
Santosh Reddy Addula, Aitizaz Ali
Most existing research on decentralized IoT applications tends to address specific vulnerabilities, with relatively few techniques dedicated to managing privacy and trust issues. To mitigate these challenges, blockchain-based solutions are increasingly adopted to enhance the reliability and security of IoT networks. In particular, blockchain-based authentication frameworks offer a decentralized approach to storing and verifying device identities, enabling secure and trustless communication among devices and with external systems. However, current blockchain-based IoT systems often suffer from complexity and storage overhead. To address these limitations, we propose a novel solution tailored for large-scale IoT environments using a permissioned blockchain. Our approach incorporates optimized data storage and a lightweight authentication mechanism, offering improved scalability and reduced storage demands. Furthermore, we introduce, for the first time, the integration of homomorphic encryption to secure IoT data at the user end before uploading it to the cloud. The proposed framework is evaluated through comprehensive simulations and compared with existing benchmark models. This research contributes a trust-aware security model that significantly enhances both the privacy and security of IoT services.
G. Prabaharan, E. Bharath, Sakthitharan Subramanian, R Kaviyaraj · 6 authors
No abstract is available for this record.
Federico Barbacovi, Enrique Larraia, Paul Germouty, Wei Zhang
No abstract is available for this record.
P. K. Sinha, Nishant Kumar, Piyush Aggarwal
No abstract is available for this record.
Olalekan Ola Adaramola, Chidozie Odigbo, Lei Chen, Jongyeop Kim · 5 authors
No abstract is available for this record.
J. Zhang, Jinlong Wang
The core of blockchain technology, as a decentralized distributed ledger technology, lies in how to reach consensus without a centralized institution. Consensus algorithm is the cornerstone of blockchain, which determines the security, performance and decentralization degree of blockchain. This paper starts from the basic concept of blockchain consensus algorithms, analyzes the working principle, advantages and disadvantages, and application scenarios of current mainstream consensus algorithms, and discusses the future development trend of consensus algorithms.
Ravani, Leonardo, Kistler, Tobias
Imagine sharing that you know a secret without revealing the secret itself. This is what zero-knowledge proofs (ZKPs) aim to do. In ZKPs there is a prover who claims knowledge of something and a verifier who checks this claim. The goal of this project is to further explore current technologies revolving around ZKPs and understand possible adaptations to an everyday application beyond blockchain use cases. To explore the practical use of ZKPs, this project introduces a web puzzle application that keeps the solutions of individual users private using ZKPs. A user can solve a logic- based puzzle like Binairo or Sudoku and check the validity of their solution by sharing only a ZKP of the solution. That way, the solution never leaves the user’s device. To further strengthen the security, the following two checks are implemented: (1) making sure that the solution matches the original puzzle, and (2) integrating the user’s ID during the generation process. These checks prevent users from reusing a proof to “solve” other puzzles or for the proof to be stolen by another user. To implement this application, different ZKP frameworks are considered. Circom and snarkjs are selected because of their active development, clear documentation and good web development capabilities. The final result is a secure application that demonstrates how ZKPs can be applied in a realistic and practical way. This highlights their broader potential in digital security. In most applications, the impact of ZKPs is intentionally hidden, as good cybersecurity aims to operate in the background. The ZKP-Puzzles application puts the ZKPs in the spotlight and visualizes how ZKPs work.
Amit Agarwal, Carsten Baum, Lennart Braun, Peter Schöll
No abstract is available for this record.