A Comprehensive Study of Cyber Attacks against Artificial Intelligence Systems

Author: Aayush Shah, Momin Samir, Deep Solanki, JigarGajjar
Published Online: July 1, 2026
DOI: http://doi.org/10.63766/spujstmr.26.000098
Abstract
References

AI security is an emerging industry focused on securing AI, as well as its models, data, and overall pipeline, against bad actors who want to manipulate, access, and misuse it. With AI increasingly integrated into critical domains like healthcare, finance, autonomous technology, and cyber security, the attack surface is growing exponentially. An AI system is no longer just vulnerable and open to attacks from malware and cyber-attacks, but it's now also exposed to 'adversarial examples,' 'poisoning,' 'model inversion attacks,' and 'prompt injection' and 'model extraction' attacks. These are attacks that put the overall 'confidentiality, integrity, and availability' of AI at grave risk. Securing AI requires a multidisciplinary approach comprising sound software engineering practices, robust machine learning paradigms, cryptography, and good governance. In other words, security needs to be embedded throughout the entire life cycle of an AI application—from data collection, to model training and deployment, to continuous monitoring and analysis. Methods such as adversarial training, differential privacy, federated learning, hosting the model securely, validating input data, and using continuous threat intelligence are just some other methods that can improve the security posture. Compliance, explainability tools, and red teaming have begun to be recognized as part of the fundamentally important concept of AI governance. As adversaries begin to deploy AI themselves, traditional security models need to begin to transform toward more adaptive and zero-trust-based security environments. Rather than simply a security concern, AI security is also a powerful strategic imperative for ensuring that AI is not only trusted but also employed ethically in our digital world. In this research our main focus is on evolution of artificial intelligence systems, uses of AI in cyberattacks , uses of AI in cyber defence and vulnerabilities to the AI models

Keywords: —Artificial Intelligence Security, Adversarial Attacks, Data Poisoning, Model Extraction, Prompt Injection, AI-Based Cybersecurity, AI Governance.
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