Enhancing Cybersecurity in IoT Networks: A Blockchain-Based Approach
Abstract
The Internet of Things (IoT) has introduced numerous vulnerabilities due to its distributed nature and lack of standardized security mechanisms. Traditional cybersecurity models struggle to provide robust protection against cyber threats in IoT ecosystems. This paper proposes a blockchain-based security framework to enhance data integrity, authentication, and access control in IoT networks. We evaluate the efficiency of smart contracts in mitigating attacks such as data breaches, device spoofing, and denial-of-service attacks. The results demonstrate the potential of blockchain in fortifying IoT security while maintaining scalability and low latency.
References
Whig, P., & Sankaranarayanan, L. S. (2025). Graph Data Science and ML techniques: Applications and future. In Applied Graph Data Science (pp. 105-117). Morgan Kaufmann.
Whig, P., Sharma, R., Yathiraju, N., Jain, A., & Sharma, S. (2025). Blockchain‐Enabled Secure Federated Learning Systems for Advancing Privacy and Trust in Decentralized AI. Model Optimization Methods for Efficient and Edge AI: Federated Learning Architectures, Frameworks and Applications, 321-340.
Whig, P., Kasula, B. Y., Yathiraju, N., Jain, A., & Sharma, S. (2025). Securing the future. Network Security and Data Privacy in 6G Communication: Trends, Challenges, and Applications, 103.
Chintale, P. (2020). Designing a secure self-onboarding system for internet customers using Google cloud SaaS framework. Ijar, 6(5), 482-487.
Chintale, P. (2023). DevOps Design Pattern: Implementing DevOps best practices for secure and reliable CI/CD pipeline (English Edition). Bpb Publications.
Chintale, P. (2022). Optimizing data governance and privacy in Fintech: leveraging Microsoft Azure hybrid cloud solutions. Int J Innov Eng Res, 11.
Chintale, P. SCALABLE AND COST-EFFECTIVE SELF-ONBOARDING SOLUTIONS FOR HOME INTERNET USERS UTILIZING GOOGLE CLOUD'S SAAS FRAMEWORK.
Gonzalez, P. M. (2024). Utilizing Blockchain Technology for Enhanced Security and Efficiency in Healthcare Data Management. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-15. https://jmlai.in/index.php/ijmlai/article/view/20
Kapoor, D. R. (2024). Unlocking the Potential of Healthcare Data: AI, ML, and Master Data Management Synergy. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-10. https://jmlai.in/index.php/ijmlai/article/view/21
Nguyen, P. A. (2024). Enhanced Patient Care: The Intersection of AI, ML, and Data Master Management in Healthcare. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-8. https://jmlai.in/index.php/ijmlai/article/view/22
Lopez, D. J. (2024). Innovations in Healthcare Information Management: AI, ML, and Master Data Integration Perspectives. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-10. https://jmlai.in/index.php/ijmlai/article/view/23
Yadav, H. (2024). Structuring SQL/ NoSQL databases for IoT data. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-12. https://jmlai.in/index.php/ijmlai/article/view/27
Vegesna, D. V. V. (2024). Machine Learning Approaches for Anomaly Detection in Cyber-Physical Systems: A Case Study in Critical Infrastructure Protection. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-13. https://jmlai.in/index.php/ijmlai/article/view/31
Rodriguez, P. A. (2024). The Role of AI in Autonomous Vehicles: A Review of Safety and Efficiency. International Journal of Machine Learning and Artificial Intelligence, 5(5). https://jmlai.in/index.php/ijmlai/article/view/37
Kumar, P. D. (2024). AI-Powered Emotional Wellness Companion for Mental Health Support. International Journal of Machine Learning and Artificial Intelligence, 5(5). https://jmlai.in/index.php/ijmlai/article/view/71
Harrison, P. E. (2024). AI-Based Ethical Decision-Making Framework for Autonomous Vehicles. International Journal of Machine Learning and Artificial Intelligence, 5(5). https://jmlai.in/index.php/ijmlai/article/view/70
Kim, P. C. (2024). Autonomous AI-Driven Disaster Management System. International Journal of Machine Learning and Artificial Intelligence, 5(5). https://jmlai.in/index.php/ijmlai/article/view/69
Federated Learning for Healthcare: Privacy-Preserving AI in Collaborative Diagnostics. (2024). Research-Gate Journal, 10(10). https://research-gate.in/index.php/Rgj/article/view/54
An Overview of Natural Language Processing in Analyzing Clinical Text Data for Patient Health Insights. (2024). Research-Gate Journal, 10(10). https://research-gate.in/index.php/Rgj/article/view/53
Improving Drug Discovery and Development Using AI: Opportunities and Challenges. (2024). Research-Gate Journal, 10(10). https://research-gate.in/index.php/Rgj/article/view/52
Ethical Considerations in AI Development: A Critical Analysis. (2024). Research-Gate Journal, 10(10). https://research-gate.in/index.php/Rgj/article/view/26
Human-Centric AI: Bridging Emotional Intelligence with Computational Efficiency. (2024). International Machine Learning Journal and Computer Engineering, 7(7). https://mljce.in/index.php/Imljce/article/view/65
Generative Zero-Shot Reasoning: Unifying Few-Shot Learning with Unsupervised Semantic Understanding. (2024). International Machine Learning Journal and Computer Engineering, 7(7). https://mljce.in/index.php/Imljce/article/view/64
AI in Healthcare Fraud Detection: Ensuring Integrity in Medical Billing. (2024). International Machine Learning Journal and Computer Engineering, 7(7). https://mljce.in/index.php/Imljce/article/view/54
A Comprehensive Review of AI Applications in Cybersecurity. (2024). International Machine Learning Journal and Computer Engineering, 7(7). https://mljce.in/index.php/Imljce/article/view/39
Carter, D. E. (2024). The Evolution of Natural Language Processing: A Review of Techniques and Future Directions. International Numeric Journal of Machine Learning and Robots, 8(8). https://injmr.com/index.php/fewfewf/article/view/202
Davil, P. J. (2024). Reinforcement Learning in Autonomous Systems: A Comprehensive Framework for Dynamic Decision-Making. International Numeric Journal of Machine Learning and Robots, 8(8). https://injmr.com/index.php/fewfewf/article/view/196
Snha, D. R. (2024). Ethical AI Development: Balancing Innovation and Responsibility in Machine Learning. International Numeric Journal of Machine Learning and Robots, 8(8). https://injmr.com/index.php/fewfewf/article/view/195
Kunal, D. S. (2024). Enhancing Decision-Making in Healthcare: A Deep Learning Approach for Predictive Diagnostics. International Numeric Journal of Machine Learning and Robots, 8(8). https://injmr.com/index.php/fewfewf/article/view/194
