Jurnal Ilmiah Computer Science

Transforming Cybersecurity Practices: A Comprehensive Approach to Protecting Digital Banking Assets

2025-09-10T22:29:51+07:00

The rapid evolution of digital banking has introduced unprecedented security challenges, necessitating a proactive and comprehensive cybersecurity framework. This paper explores advanced strategies for safeguarding digital banking assets, integrating cutting-edge technologies such as artificial intelligence (AI), blockchain, and zero-trust architectures. By analyzing emerging threats, regulatory requirements, and best practices, this study presents a holistic approach to strengthening financial cybersecurity resilience. The findings emphasize the need for a dynamic, multi-layered security model that adapts to evolving cyber threats while ensuring compliance and user trust.

A Comparative Study of Encryption-Based Access Control Schemes in Ethereum, Hyperledger Fabric, and Corda

2025-09-10T22:29:52+07:00

Blockchain technology has emerged as a transformative solution for decentralized and immutable data storage, offering transparency and security across various industries. However, ensuring authorized data access remains a critical challenge in blockchain systems. Encryption-based access control mechanisms are pivotal in mitigating unauthorized access, yet their implementation varies significantly across different blockchain platforms. This study provides a comprehensive comparison of encryption-based access control schemes in three prominent blockchain platforms: Ethereum, Hyperledger Fabric, and Corda. The analysis focuses on their strengths, weaknesses, and suitability for various use cases, evaluating security, scalability, and usability. The findings reveal distinct trade-offs among the platforms, highlighting the need for tailored solutions based on specific application requirements. Future research directions, including hybrid access control models and post-quantum cryptography, are also discussed.

Design and Implementation of a Smart Contract-Based Consent Management Model for Secure Personal Data Sharing

2025-09-10T22:29:52+07:00

Emerging data-sharing paradigms demand robust mechanisms to ensure user consent is dynamically managed while preserving data sovereignty. This paper proposes a blockchain-driven consent management model that leverages smart contracts, offline storage, and a JavaScript/JSON front end to empower data owners in healthcare, finance, and identity management. The framework decentralizes consent logging, automates access enforcement, and integrates GDPR-compliant "right to revoke" functionalities, addressing critical gaps in existing systems such as offline accessibility, cross-industry interoperability, and regulatory compliance. A mixed-methods approach—combining a systematic literature review (SLR) of 150 studies (2018–2023) and three case studies—validates the model's efficacy. Performance benchmarks reveal sub-second consent updates, 99.98% audit accuracy, and 40% reduced breach risks compared to centralized systems. The hybrid architecture employs a two-tiered design, with an on-chain layer for immutable consent logging and an offline layer for local data storage, ensuring enforceability even during network outages. The front end, built using React.js and Ethers.js, provides a user-friendly interface for non-technical users to define and manage consent terms. Security protocols, including FIDO2 authentication and AES-256-GCM encryption, ensure robust protection against unauthorized access. Challenges include gas cost volatility in public blockchains and latency in multi-chain consent synchronization. The study contributes a novel hybrid architecture, open-source front-end tools, and a regulatory alignment roadmap for decentralized consent ecosystems. Case studies in healthcare, finance, and identity management demonstrate the model's practical applicability, with unauthorized access reduced by 40% and user satisfaction scores exceeding 4.7/5. Future work will explore AI-driven consent drafting, interoperability standards, and quantum-resistant cryptography to further enhance the model's scalability and security. This research advances the state of the art in blockchain-based consent management, offering a scalable, secure, and user-centric solution for data sovereignty in the digital age.

Blockchain Technology in AI-Driven Cybersecurity: Strengthening Trust in Financial and Digital Security Systems

2025-09-10T22:29:52+07:00

Blockchain technology has revolutionized the banking and finance sector by introducing a decentralized, secure, and transparent framework for financial transactions. This paper provides a comprehensive review of the role of blockchain in transforming trust mechanisms within financial institutions, focusing on its applications in payments, smart contracts, identity management, and regulatory compliance. A mixed-methods approach was employed, integrating a systematic literature review with case study analysis to evaluate the effectiveness of blockchain-based security solutions. The results indicate that blockchain significantly enhances transaction security, reduces fraud, and improves operational efficiency, with AI-powered fraud detection achieving a 92% accuracy rate and biometric authentication strengthening access control. Despite these advantages, challenges such as scalability, regulatory compliance, and integration with existing financial infrastructures remain key barriers to adoption. The study concludes that blockchain, in conjunction with AI-driven cybersecurity measures, presents a robust solution for enhancing trust and security in digital finance. However, continuous regulatory advancements and industry-wide collaboration are necessary to ensure its sustainable implementation.

A Federated Architecture for Enhancing Security and Scalability in IoT-Cloud Integrated Systems

2025-09-10T22:29:52+07:00

The exponential growth of the Internet of Things (IoT) and its integration with cloud computing has introduced significant challenges related to security, scalability, and data privacy. This paper proposes a novel federated architecture that leverages federated learning and distributed security mechanisms to enhance the resilience and scalability of IoT-cloud integrated systems. By decentralizing data processing and security enforcement, the architecture mitigates common attack vectors such as centralized point-of-failure, data leakage, and unauthorized access. The proposed system is designed with modular security components including lightweight encryption, dynamic trust management, and blockchain-inspired audit trails. A performance evaluation conducted through simulated environments and real-world IoT testbeds demonstrates improved latency, resource efficiency, and defense against cyber threats when compared to conventional centralized systems. This research contributes to the advancement of secure and scalable IoT-cloud infrastructures and offers a viable path for industrial and smart city deployments.