Vol. 4 No. 2 (2024): African Journal of Artificial Intelligence and Sustainable Development
Articles

The Role of AI-Driven Cybersecurity Solutions in Protecting U.S. Manufacturing Supply Chains

Dr. Li Wang
Professor of Electrical Engineering, Beijing Jiaotong University, China

Published 23-09-2024

Keywords

  • Cybersecurity,
  • Manufacturing Supply Chains

How to Cite

[1]
Dr. Li Wang, “The Role of AI-Driven Cybersecurity Solutions in Protecting U.S. Manufacturing Supply Chains”, African J. of Artificial Int. and Sust. Dev., vol. 4, no. 2, pp. 266–280, Sep. 2024, Accessed: Nov. 23, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/164

Abstract

AI-driven cybersecurity solutions play a pivotal role in fortifying the resilience of manufacturing supply chains against cyber threats and vulnerabilities. The escalating reliance on information technologies has led to a surge in security challenges and frequent cyberattacks targeting businesses and critical infrastructures. To address these challenges, AI offers significant advantages in threat identification and appropriate countermeasures [1]. Recent advancements in AI-driven threat response systems have paved the way for the development of autonomous threat response systems, reflecting a diverse range of strategies for dealing with cyber threats. These AI-powered systems not only enhance security but also assist human experts in decision-making, thereby bolstering the overall security posture of digital systems and interconnected networks [2].

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References

  1. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence and Blockchain Integration for Enhanced Security in Insurance: Techniques, Models, and Real-World Applications." African Journal of Artificial Intelligence and Sustainable Development 1.2 (2021): 187-224.
  2. Singh, Puneet. "AI-Driven Personalization in Telecom Customer Support: Enhancing User Experience and Loyalty." Distributed Learning and Broad Applications in Scientific Research 9 (2023): 325-363.
  3. Rambabu, Venkatesha Prabhu, Selvakumar Venkatasubbu, and Jegatheeswari Perumalsamy. "AI-Enhanced Workflow Optimization in Retail and Insurance: A Comparative Study." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 163-204.
  4. Pradeep Manivannan, Rajalakshmi Soundarapandiyan, and Amsa Selvaraj, “Navigating Challenges and Solutions in Leading Cross-Functional MarTech Projects”, Journal of AI-Assisted Scientific Discovery, vol. 2, no. 1, pp. 282–317, Feb. 2022
  5. Jasrotia, Manojdeep Singh. "Unlocking Efficiency: A Comprehensive Approach to Lean In-Plant Logistics." International Journal of Science and Research (IJSR) 13.3 (2024): 1579-1587.
  6. Gayam, Swaroop Reddy. "AI for Supply Chain Visibility in E-Commerce: Techniques for Real-Time Tracking, Inventory Management, and Demand Forecasting." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 218-251.
  7. Nimmagadda, Venkata Siva Prakash. "AI-Powered Predictive Analytics for Credit Risk Assessment in Finance: Advanced Techniques, Models, and Real-World Applications." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 251-286.
  8. Putha, Sudharshan. "AI-Driven Decision Support Systems for Insurance Policy Management." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 326-359.
  9. Sahu, Mohit Kumar. "Machine Learning Algorithms for Automated Underwriting in Insurance: Techniques, Tools, and Real-World Applications." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 286-326.
  10. Kasaraneni, Bhavani Prasad. "Advanced AI Techniques for Fraud Detection in Travel Insurance: Models, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 455-513.
  11. Kondapaka, Krishna Kanth. "Advanced AI Models for Portfolio Management and Optimization in Finance: Techniques, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 560-597.
  12. Kasaraneni, Ramana Kumar. "AI-Enhanced Claims Processing in Insurance: Automation and Efficiency." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 669-705.
  13. Pattyam, Sandeep Pushyamitra. "Advanced AI Algorithms for Predictive Analytics: Techniques and Applications in Real-Time Data Processing and Decision Making." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 359-384.
  14. Kuna, Siva Sarana. "AI-Powered Customer Service Solutions in Insurance: Techniques, Tools, and Best Practices." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 588-629.
  15. Gayam, Swaroop Reddy. "Artificial Intelligence for Financial Fraud Detection: Advanced Techniques for Anomaly Detection, Pattern Recognition, and Risk Mitigation." African Journal of Artificial Intelligence and Sustainable Development 1.2 (2021): 377-412.
  16. Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Automated Loan Underwriting in Banking: Advanced Models, Techniques, and Real-World Applications." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 174-218.
  17. Putha, Sudharshan. "AI-Driven Molecular Docking Simulations: Enhancing the Precision of Drug-Target Interactions in Computational Chemistry." African Journal of Artificial Intelligence and Sustainable Development 1.2 (2021): 260-300.
  18. Sahu, Mohit Kumar. "Machine Learning Algorithms for Enhancing Supplier Relationship Management in Retail: Techniques, Tools, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 227-271.
  19. Kasaraneni, Bhavani Prasad. "Advanced AI Techniques for Predictive Maintenance in Health Insurance: Models, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 513-546.
  20. Kondapaka, Krishna Kanth. "Advanced AI Models for Retail Supply Chain Network Design and Optimization: Techniques, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 598-636.
  21. Kasaraneni, Ramana Kumar. "AI-Enhanced Clinical Trial Design: Streamlining Patient Recruitment, Monitoring, and Outcome Prediction." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 706-746.
  22. Pattyam, Sandeep Pushyamitra. "AI in Data Science for Financial Services: Techniques for Fraud Detection, Risk Management, and Investment Strategies." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 385-416.
  23. Kuna, Siva Sarana. "AI-Powered Techniques for Claims Triage in Property Insurance: Models, Tools, and Real-World Applications." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 208-245.
  24. Pradeep Manivannan, Priya Ranjan Parida, and Chandan Jnana Murthy. “The Influence of Integrated Multi-Channel Marketing Campaigns on Consumer Behavior and Engagement”. Journal of Science & Technology, vol. 3, no. 5, Oct. 2022, pp. 48-87
  25. Rambabu, Venkatesha Prabhu, Jeevan Sreerama, and Jim Todd Sunder Singh. "AI-Driven Data Integration: Enhancing Risk Assessment in the Insurance Industry." Australian Journal of Machine Learning Research & Applications 2.2 (2022): 130-179.
  26. Selvaraj, Akila, Deepak Venkatachalam, and Gunaseelan Namperumal. "Synthetic Data for Financial Anomaly Detection: AI-Driven Approaches to Simulate Rare Events and Improve Model Robustness." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 373-425.
  27. Paul, Debasish, Praveen Sivathapandi, and Rajalakshmi Soundarapandiyan. "Evaluating the Impact of Synthetic Data on Financial Machine Learning Models: A Comprehensive Study of AI Techniques for Data Augmentation and Model Training." Journal of Artificial Intelligence Research and Applications 2.2 (2022): 303-341.
  28. Namperumal, Gunaseelan, Praveen Sivathapandi, and Deepak Venkatachalam. "The Role of Blockchain Technology in Enhancing Data Integrity and Transparency in Cloud-Based Human Capital Management Solutions." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 546-582.
  29. Soundarapandiyan, Rajalakshmi, Praveen Sivathapandi, and Akila Selvaraj. "Quantum-Resistant Cryptography for Automotive Cybersecurity: Implementing Post-Quantum Algorithms to Secure Next-Generation Autonomous and Connected Vehicles." Cybersecurity and Network Defense Research 3.2 (2023): 177-218.
  30. Sudharsanam, Sharmila Ramasundaram, Akila Selvaraj, and Praveen Sivathapandi. "Enhancing Vehicle-to-Everything (V2X) Communication with Real-Time Telematics Data Analytics: A Study on Safety and Efficiency Improvements in Smart Cities." Australian Journal of Machine Learning Research & Applications 3.1 (2023): 461-507.