About the Journal

Journal of Applied Big Data Analytics and Security (JABDAS) is a peer-reviewed academic journal dedicated to the dissemination of high-quality research on applied big data analytics, data science, and secure data-driven systems. The journal focuses on practical and methodological contributions that advance the design, implementation, evaluation, and governance of analytics solutions in real-world contexts.

JABDAS publishes original research articles, review papers, and technical studies covering topics such as big data analytics pipelines, machine learning and artificial intelligence applications, data engineering frameworks, analytics evaluation methodologies, and decision-support systems. Particular emphasis is placed on security, privacy, and trust issues in analytics environments, including secure data processing, privacy-preserving analytics, and cybersecurity challenges in data-intensive platforms.

The journal welcomes interdisciplinary research where computational analytics and security considerations play a central role, with applications in education, business, industry, healthcare, and societal systems. JABDAS aims to provide a rigorous scholarly platform for researchers, practitioners, and educators seeking to bridge theory and practice in big data analytics and security.