Fortifying Networks based AI Models for Early Vulnerability Detection
- Title
- Fortifying Networks based AI Models for Early Vulnerability Detection
- Creator
- Kumar, Prince; Sharma, Nandini; Sabarmathi, G.; Chinnaiyan, R.; Khanna, Vimal Kumar; Bushra, Seema
- Description
- Early identification of network vulnerabilities is now essential for protecting sensitive data and guaranteeing system resilience due to the increasing complexity of digital infrastructures. An extensive analysis of artificial intelligence (AI) models intended for the early identification of network vulnerabilities is presented in this research. The study examines current approaches, assesses their efficacy, and pinpoints research gaps while drawing on ideas from recent studies and cutting-edge academic research tools. The results show how AI has the ability to revolutionize cybersecurity tactics and point to new avenues for improving vulnerability detection systems. 2025 IEEE.
- Source
- 2025 2nd International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2025;
- Date
- 01-01-2025
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- AI-driven cybersecurity; AI-powered threat intelligence; anomaly detection; federated learning; graph neural networks; hybrid AI models; network vulnerability detection; quantum computing; reinforcement learning; supervised learning; unsupervised learning
- Coverage
- Kumar P., Lingaya's Vidyapeeth, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India; Sharma N., Lingaya's Vidyapeeth Deemed to be University, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India; Sabarmathi G., Christ University, School of Computer Science, Bangalore, India; Chinnaiyan R., Lingaya's Vidyapeeth, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India; Khanna V.K., Lingaya's Vidyapeeth, AI/ML Lab, Centre of Excellence, Department of Computer Science and Engineering, Haryana, Faridabad, India; Bushra S., School of Commerce & Management, Lingaya's, AI/ML Lab, Centre of Excellence, Haryana, Faridabad, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISBN: 979-833159610-1;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Kumar, Prince; Sharma, Nandini; Sabarmathi, G.; Chinnaiyan, R.; Khanna, Vimal Kumar; Bushra, Seema, “Fortifying Networks based AI Models for Early Vulnerability Detection,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25919.