https://publikasi.dinus.ac.id/jcta <div style="border: 3px #086338 Dashed; padding: 10px; background-color: #ffffff; text-align: left;"> <ol> <li><strong>Journal Title </strong>: Journal of Computing Theories and Applications</li> <li><strong>Online ISSN </strong>: <a href="https://portal.issn.org/resource/ISSN/3024-9104">3024-9104</a> </li> <li><strong>Frequency </strong>: Quarterly (February, May, August, and November) </li> <li><strong>DOI Prefix</strong>: 10.62411/jcta</li> <li><strong>Publisher </strong>: Universitas Dian Nuswantoro</li> </ol> </div> <div id="focusAndScope"> <p><strong data-start="133" data-end="190">Journal of Computing Theories and Applications (JCTA)</strong> is a peer-reviewed international journal that covers all aspects of foundations, theories, and practical applications in computer science. All accepted articles are published online, assigned a <strong data-start="527" data-end="547">DOI via Crossref</strong>, and made <strong data-start="558" data-end="593" data-is-only-node="">freely accessible (Open Access)</strong>. The journal follows a <strong>rapid peer-review</strong> process, with the first decision typically provided within two to four weeks. JCTA welcomes original research papers in, but not limited to:</p> <p>Artificial Intelligence<br />Big Data<br />Bioinformatics<br />Biometrics<br />Cloud Computing<br />Computer Graphics<br />Computer Vision<br />Cryptography<br />Data Mining<br />Fuzzy Systems<br />Game Technology<br />Image Processing<br />Information Security<br />Internet of Things<br />Intelligent Systems<br />Machine Learning<br />Mobile Computing<br />Multimedia Technology<br />Natural Language Processing<br />Network Security<br />Pattern Recognition<br />Quantum Informatics<br />Signal Processing<br />Soft Computing<br />Speech Processing</p> <p><br />Special emphasis is given to recent trends related to cutting-edge research within the domain.</p> </div> <div id="peerReviewProcess"> </div> <div id="sponsors"> <p> </p> </div> Universitas Dian Nuswantoro en-US Journal of Computing Theories and Applications 3024-9104 https://publikasi.dinus.ac.id/jcta/article/view/15508 <p>The proliferation of cloud infrastructures has intensified concerns regarding data security, integrity, identity and access management, and user privacy. Despite recent advances, existing solutions often lack comprehensive integration of privacy-preserving mechanisms, dynamic trust management, and cross-provider interoperability. This study proposes an AI-enabled, zero-trust, blockchain-fused identity management framework for secure, privacy-preserving multi-cloud environments. The framework integrates homomorphic encryption with differential privacy for aggregate-level protection and secure multi-party computation for collaborative data processing. The proposed system was validated in a simulated multi-cloud environment using CloudSim, Ethereum blockchain, and AWS EC2. Experimental results indicate homomorphic encryption latency of approximately 450ms per operation and statistically significant security improvements (t(128) = 12.47, p &lt; 0.001), privacy (t(95) = 8.93, p &lt; 0.001), and throughput (t(156) = 15.21, p &lt; 0.001). The framework achieved differential privacy with ε = 0.1 while retaining 99.2% data utility, and demonstrated a 34% improvement in processing speed over conventional differential privacy approaches. In addition, the implementation was observed to be 2.3× faster than BGV-based configurations, with 45% lower memory consumption than CKKS and a 67% reduction in ciphertext size relative to baseline implementations. From an operational perspective, the framework shows a 23% reduction in security management costs, a 31% improvement in resource utilization efficiency, and an 18% decrease in compliance audit expenses. The model further indicates a 27% reduction in total cost of ownership (TCO) compared with multi-vendor security solutions, a projected return on investment (ROI) within 14 months, and an 89% reduction in security incident response costs under the evaluated conditions.</p> Tabitha Chukwudi Aghaunor Eferhire Valentine Ugbotu Emeke Ugboh Paul Avwerosuoghene Onoma Frances Uchechukwu Emordi Arnold Adimabua Ojugo Victor Ochuko Geteloma Rebecca Okeoghene Idama Peace Oguguo Ezzeh Copyright (c) 2026 Tabitha Chukwudi Aghaunor, Eferhire Valentine Ugbotu, Emeke Ugboh, Paul Avwerosuoghene Onoma, Frances Uchechukwu Emordi, Arnold Adimabua Ojugo, Victor Ochuko Geteloma, Rebecca Okeoghene Idama, Peace Oguguo Ezzeh https://creativecommons.org/licenses/by/4.0 2026-02-24 2026-02-24 3 4 428 442 10.62411/jcta.15508