Improving Zero-Trust Architectures by Machine Learning Algorithms: An All-Inclusive Cybersecurity Real-Time Anomaly Detection Framework
Keywords:
Zero-Trust Architecture, machine learning, anomaly detection, cybersecurityAbstract
Zero-confidence architecture (ZTA) is a new cybersecurity idea aimed to lower security risks by erasing implicit trust in any user or system, regardless of their location within or outside the network edge. Apart from least-privilege access policies, this design calls for extensive identity validation for every request. Zero-trust systems have to evolve, however, to include innovative approaches for spotting and handling more complicated intrusions. Strong real-time anomaly detection given by machine learning (ML) techniques might help zero-trust systems. Emphasizing anomaly detection systems that enhance security by spotting abnormal patterns in network traffic, user behavior, and system operations, this work explores how machine learning may be implemented into Zero-Trust systems.
Downloads
References
Madupati, Bhanuprakash. "Data Science in Public Relations Software Development." Available at SSRN 5076688 (2022).
Singu, Santosh Kumar. "Real-Time Data Integration: Tools, Techniques, and Best Practices." ESP Journal of Engineering & Technology Advancements 1.1 (2021): 158-172.
S. Kumari, “Kanban and Agile for AI-Powered Product Management in Cloud-Native Platforms: Improving Workflow Efficiency Through Machine Learning-Driven Decision Support Systems”, Distrib Learn Broad Appl Sci Res, vol. 5, pp. 867–885, Aug. 2019
Pillai, Vinayak. Anomaly Detection for Innovators: Transforming Data into Breakthroughs. Libertatem Media Private Limited, 2022.
Gondaliya, Jayraj, et al. "Hybrid security RSA algorithm in application of web service." 2018 1st International Conference on Data Intelligence and Security (ICDIS). IEEE, 2018.
Talati, Dhruvitkumar. "Quantum minds: Merging quantum computing with next-gen AI." (2023).
Kalluri, Kartheek. "Migrating Legacy System to Pega Rules Process Commander v7. 1." (2015).
Madupati, Bhanuprakash. "Machine Learning for Cybersecurity in Industrial Control Systems (ICS)." Available at SSRN 5076696 (2022).
S. Kumari, “Cloud Transformation and Cybersecurity: Using AI for Securing Data Migration and Optimizing Cloud Operations in Agile Environments”, J. Sci. Tech., vol. 1, no. 1, pp. 791–808, Oct. 2020.
Singu, Santosh Kumar. "Designing scalable data engineering pipelines using Azure and Databricks." ESP Journal of Engineering & Technology Advancements 1.2 (2021): 176-187.
Talati, Dhruvitkumar. "Artificial intelligence (AI) in mental health diagnosis and treatment." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 251-253.
Kalluri, Kartheek. "ENHANCING CUSTOMER SERVICE EFFICIENCY: A COMPARATIVE STUDY OF PEGA'S AI-DRIVEN SOLUTIONS."
S. Kumari, “AI-Powered Cloud Security for Agile Transformation: Leveraging Machine Learning for Threat Detection and Automated Incident Response ”, Distrib Learn Broad Appl Sci Res, vol. 6, pp. 467–488, Oct. 2020
Madupati, Bhanuprakash. "Cybersecurity in Day-to-Day Life: A Technical Perspective." Available at SSRN 5076692 (2022).
Talati, Dhruvitkumar. "Telemedicine and AI in Remote Patient Monitoring." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 254-255.
Singu, Santosh Kumar. "ETL Process Automation: Tools and Techniques." ESP Journal of Engineering & Technology Advancements 2.1 (2022): 74-85.
Kalluri, Kartheek. "Federate Machine Learning: A Secure Paradigm for Collaborative AI in Privacy-Sensitive Domains." International Journal on Science and Technolo-gy 13.4 (2022): 1-13.
Madupati, Bhanuprakash. "Cybersecurity in the Airline Industry: A Technical Perspective." Available at SSRN 5076684 (2022).
S. Kumari, “AI-Powered Cybersecurity in Agile Workflows: Enhancing DevSecOps in Cloud-Native Environments through Automated Threat Intelligence ”, J. Sci. Tech., vol. 1, no. 1, pp. 809–828, Dec. 2020.
Singu, Santosh Kumar. "Impact of Data Warehousing on Business Intelligence and Analytics." ESP Journal of Engineering & Technology Advancements 2.2 (2022): 101-113.
Kalluri, Kartheek. "Optimizing Financial Services Implementing Pega's Decisioning Capabilities for Fraud Detection." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 10.1 (2022): 1-9.
Talati, Dhruvitkumar. "AI in healthcare domain." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.3 (2023): 256-262.
Kalluri, Kartheek. "Blockchain Augment AI: Securing Decision Pipelines Decentralized in Systems."
