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Menampilkan 1–6 dari 6 artikel
Toward Explainable AI for Cybersecurity: A NIST-Based Knowledge Graph for Transparent Semantic Reasoning
Journal of Information Technology and Computer Science
Vol 2
, No 1
(2026)
Explainable artificial intelligence (XAI) has become a critical requirement in cybersecurity due to the high-stakes nature of security decision-making and the limitations of black-box learning models. This study investigates the construction of an explainable cybersecurity knowledge representation by leveraging standardized terminology from the NIST cybersecurity glossary. The primary problem addressed is the lack of transparent and semantically grounded reasoning mechanisms in existing AI-drive...
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Adaptive DevOps Practices for Enhancing Reliability and Performance of Embedded Computing Platforms in Safety Critical Industrial Applications
Software Engineering in Computing Systems
Vol 1
, No 1
(2026)
This study investigates the adoption of adaptive DevOps practices in embedded systems used in safety-critical industrial applications. Traditional DevOps models, which are primarily designed for cloud-based systems, face significant challenges when applied to embedded platforms due to hardware constraints, real-time performance requirements, and stringent safety standards. The research focuses on developing a tailored DevOps framework that integrates continuous integration/continuous delivery (C...
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Optimizing End to end Machine Learning Pipelines Using Hybrid Edge Cloud Architectures for Real Time Decision making Applications
Big Data Analytics and Data Science
Vol 1
, No 1
(2026)
Real time decision making applications, such as those used in autonomous vehicles, smart cities, and industrial IoT, require fast, scalable, and accurate analytics to ensure timely responses and optimized operations. Traditional cloud-based systems face significant challenges in meeting these requirements due to high latency, limited scalability, and bottlenecks in data processing. This study explores the use of a hybrid Edge Cloud architecture to optimize End to end machine learning (ML) pipeli...
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Executive Decision Support System Implementation Strategies Based on Big Data Analytics to Improve Operational Efficiency and Corporate Governance in Global Digital Enterprises
Integrated System and Management Technology
Vol 1
, No 1
(2026)
This study explores the transformative role of big data-driven Decision Support Systems (DSS) in global digital enterprises, particularly focusing on their impact on operational efficiency and corporate governance. By leveraging big data analytics, DSS offer organizations the tools to process vast amounts of real-time data, enabling executives to make more informed decisions that optimize resources, improve productivity, and reduce operational costs. The research highlights the integration of pr...
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Digital Forensics and Automated Incident Response Framework Leveraging Big Data Analytics and Real Time Network Traffic Profiling in Heterogeneous Cyber Environments
Cyber Security and Network Management
Vol 1
, No 1
(2026)
The increasing complexity and scale of modern cybersecurity threats necessitate the development of advanced systems capable of efficiently detecting, analyzing, and mitigating incidents in real time. This paper proposes an automated framework for digital forensics and incident response that leverages big data analytics and real time network traffic profiling. The framework integrates cutting-edge technologies, including Apache Spark for real time data processing and Hadoop for scalable data stor...
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Information Systems Governance Framework for Supporting Organizational Decision Making in Digital Transformation Initiatives
Information System Analysis, Design and Development
Vol 1
, No 1
(2026)
Digital transformation initiatives have become essential for organizations seeking to remain competitive in today’s rapidly evolving technological landscape. However, many organizations face challenges due to ineffective Information Systems (IS) governance, which hampers strategic decision-making and the successful execution of these initiatives. This study aims to develop an IS governance framework that enhances decision-making quality by aligning IT decisions with organizational goals during d...
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