AI-Enhanced Intrusion Detection Systems for Retail Cloud Networks: A Comparative Analysis
Abstract
Retail businesses using cloud-based services are increasingly vulnerable to cyber threats, requiring robust Intrusion Detection Systems (IDS) for proactive threat management. This paper provides a comparative analysis of AI-enhanced IDS models, including Supervised ML, Deep Learning, and Federated Learning, in detecting cyberattacks on retail cloud networks. We benchmark the performance of these models against traditional IDS using accuracy, false-positive rates, and real-time detection speed. Our results highlight the advantages of AI-driven IDS in identifying sophisticated attack patterns, securing customer transactions, and preventing data breaches in cloud-based retail environments.
References
Reddy, R. (2022). Innovations in Agricultural Machinery: Assessing the Impact of Advanced Technologies on Farm Efficiency. Journal of Artificial Intelligence and Big Data, 2(1), 10-31586.
Reddy, R. (2020). Predictive modeling with AI and ML for small business health plans: Improving employee health outcomes and reducing costs. Available at SSRN 5018069.
Reddy, R. (2022). Application of neural networks in optimizing health outcomes in Medicare Advantage and supplement plans. Available at SSRN 5031287.
Mandala, G., Danda, R. R., Nishanth, A., Yasmeen, Z., & Maguluri, K. K. (2023). AI AND ML IN HEALTHCARE: REDEFINING DIAGNOSTICS. TREATMENT, AND PERSONALIZED MEDICINE.
Danda, R. R. (2022). Telehealth In Medicare Plans: Leveraging AI For Improved Accessibility And Senior Care Quality. Migration Letters, 19(6), 999-1009.
Danda, R. R. (2022). Deep Learning Approaches For Cost-Benefit Analysis Of Vision And Dental Coverage In Comprehensive Health Plans. Migration Letters, 19(6), 1103-1118.
Davuluri, M. (2023). AI for Healthcare Workflow Optimization: Reducing Burnout and Enhancing Efficiency. International Numeric Journal of Machine Learning and Robots, 7(7).
Davuluri, M. (2023). AI in Surgical Assistance: Enhancing Precision and Outcomes. International Machine learning journal and Computer Engineering, 6(6).
Davuluri, M. (2022). AI in Mental Health: Transforming Diagnosis and Therapy. International Machine learning journal and Computer Engineering, 5(5).
Vattikuti, M. C. (2023). Real-Time Anomaly Detection in Industrial IoT Systems Using Hybrid AI Models. International Scientific Journal for Research, 5(5).
Vattikuti, M. C. (2023). Ethical AI Framework for Bias Mitigation in Machine Learning Algorithms. International Scientific Journal for Research, 5(5).
Vattikuti, M. C. (2022). Federated Learning for Privacy-Preserving AI in Healthcare Applications. International Transactions in Artificial Intelligence, 6(6).
Deekshith, A. (2019). Integrating AI and Data Engineering: Building Robust Pipelines for Real-Time Data Analytics. International Journal of Sustainable Development in Computing Science, 1(3), 1-35.
Deekshith, A. (2020). AI-Enhanced Data Science: Techniques for Improved Data Visualization and Interpretation. International Journal of Creative Research In Computer Technology and Design, 2(2).
Deekshith, A. (2021). Data engineering for AI: Optimizing data quality and accessibility for machine learning models. International Journal of Management Education for Sustainable Development, 4(4), 1-33.
Deekshith, A. (2022). Cross-Disciplinary Approaches: The Role of Data Science in Developing AI-Driven Solutions for Business Intelligence. International Machine learning journal and Computer Engineering, 5(5).
Deekshith, A. (2023). Scalable Machine Learning: Techniques for Managing Data Volume and Velocity in AI Applications. International Scientific Journal for Research, 5(5).
Mane, S., & Immidi, K. (2023). Enhancing SAP Available-to-Promise (ATP) Capabilities through AI Integration: A Transformative Approach to Supply Chain Optimization. International Journal of Creative Research In Computer Technology and Design, 5(5), 1-24.
Mane, S. (2023). Optimizing SAP Sales Order Processing: Strategies, Technologies, and Impact on Operational Efficiency. International Journal of Interdisciplinary Finance Insights, 2(2), 1-32.
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2020). Optimizing SAP Data Processing with Machine Learning Algorithms in Cloud Environments. International Transactions in Artificial Intelligence, 4(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2020). Artificial Intelligence in Business Analytics: Cloud-Based Strategies for Data Processing and Integration. International Journal of Sustainable Development in Computing Science, 2(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2020). Scalable Data Processing Pipelines: The Role of AI and Cloud Computing. International Scientific Journal for Research, 2(2).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2021). Leveraging Cloud Computing for Efficient Data Processing in SAP Enterprise Solutions. International Journal of Machine Learning for Sustainable Development, 3(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2021). Machine Learning in SAP Workflows: A Study of Predictive Analytics and Automation. Transactions on Latest Trends in Artificial Intelligence, 2(2).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2021). Machine Learning Models for Optimizing SAP-Based Data Processing in Cloud Environments. International Journal of Sustainable Development in Computing Science, 3(3).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2022). Advanced Business Analytics Using Machine Learning and Cloud-Based Data Integration. International Scientific Journal for Research, 4(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2023). AI-Driven Business Analytics Framework for Data Integration Across Hybrid Cloud Systems. Transactions on Latest Trends in Artificial Intelligence, 4(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2023). Integrating AI and Cloud Computing for Scalable Business Analytics in Enterprise Systems. International Journal of Sustainable Development in Computing Science, 5(3).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2023). Enhancing Data Integration Using AI and ML Techniques for Real-Time Analytics. International Journal of Machine Learning for Sustainable Development, 5(3).
