Responsible Intelligence in Cloud-Native Software Engineering: Ethical AI and NLP Framework for Secure Software-Defined Networks
DOI:
https://doi.org/10.15662/IJARCST.2021.0405004Keywords:
Responsible Artificial Intelligence (AI), Cloud-Native Software Engineering, Software-Defined Networks (SDN), Natural Language Processing (NLP), Ethical Computing, Explainable AI (XAI), Cognitive Cloud Framework, Secure Orchestration, Trust-Aware APIs, AI GovernanceAbstract
The convergence of Ethical Artificial Intelligence (AI), Natural Language Processing (NLP), and cloud-native software engineering is redefining the foundation of secure and intelligent network infrastructures. This paper proposes a Responsible Intelligence Framework for Software-Defined Networks (SDNs) that integrates ethical AI principles and NLP-driven automation to enhance decision transparency, trust, and resilience in cloud-native ecosystems. The framework introduces an explainable AI layer embedded within SDN controllers, enabling semantic understanding of network policies, intent-based orchestration, and dynamic anomaly detection through NLP-assisted rule interpretation. Ethical intelligence modules govern AI decision-making, ensuring compliance with fairness, accountability, and privacy-preserving standards throughout the software lifecycle. The study highlights a multi-tier cloud-native architecture where containerized microservices communicate via trust-aware APIs, monitored by cognitive agents capable of ethical self-adaptation. Experimental simulations demonstrate significant improvements in security compliance, fault recovery time, and explainability of AI-based network operations. The proposed approach establishes a foundation for responsible, interpretable, and secure AI integration in next-generation cloud-native software systems.
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