Secure and Explainable AI Systems in Cloud-Based Applications: Bridging Trust and Performance
DOI:
https://doi.org/10.15662/IJEETR.2025.0704014Keywords:
AI Infrastructure, Cloud Computing, SaaS Applications, PaaS Tools, IaaS Resources, AI DeploymentAbstract
The article examines how security and explainability can be integrated in AI systems found in cloud-based applications. With AI also becoming an important concept in different industries, security and transparency of these systems are major concerns that can help in building confidence and boosting performance. The study brings out the dilemma in terms of integrating the necessity of having a strong security system and the need to have explainable AI models especially in cloud infrastructure. Integrating security frameworks with explainability methods will help change cloud-based AI systems to reduce vulnerabilities, maintain the confidentiality of data, and offer users transparent decision-making. This integration is crucial in enhancing user confidence, ethical issues, and performance of the system as highlighted in the article. The major implications of the research findings are that secure and explainable AI models can increase not only trust but also promote the efficiency and reliability of the AI in real settings leading to the broader application of AI technologies in sensitive sectors like healthcare, finance, and autonomous systems.
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