A Multi-Layer Security Framework for Adversarial SQL Injection in Machine Learning Systems
- Title
- A Multi-Layer Security Framework for Adversarial SQL Injection in Machine Learning Systems
- Creator
- Veigas, Christine Maria; Sangeetha, G.; Kulkarni, Manasa
- Description
- Adversarial machine learning (AML) is a field that works with attacks from hackers that deliberately cause machine learning systems to work incorrectly or identify data wrongly. Modern day machine learning systems grow in a very fast manner. This often introduces new threats and vulnerabilities that are above the capacity of the traditional cyber security measures. These attacks can in turn affect the trustworthiness and security of artificial systems across many domains like healthcare, education, finance, etc. This paper introduces a multi-layer security framework. It focuses on modelling and defending against SQL injection based attacks in machine learning. The paper emphasizes technical defences, governance and collaboration across various domains. By combining the risks with the existing cybersecurity frameworks such as NIST, MITRE ATLAS, and the EU AI Act, the framework provides a way to develop resilient, ethical and secure AI systems. 2025 IEEE.
- Source
- 2025 17th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2025;pp.714-720
- Date
- 01-01-2025
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Adversarial Defenses; Adversarial Machine Learning; AI Governance; Injection Attacks; Mathematical Modelling; Threat Analysis
- Coverage
- Veigas C.M., Christ University, Department of Computer Science, India; Sangeetha G., Christ University, Department of Computer Science, India; Kulkarni M., Christ University, Department of Computer Science, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISBN: 979-833158733-8;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Veigas, Christine Maria; Sangeetha, G.; Kulkarni, Manasa, “A Multi-Layer Security Framework for Adversarial SQL Injection in Machine Learning Systems,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25781.