Adversarial Attacks on Machine Learning Models in Healthcare Applications

Keywords:
Artificial Intelligence, Machine learning, Adversarial attacks, Healthcare applications

Abstract:
With the accelerated development of software tools, fast lifestyle, and expensive healthcare, many healthcare applications have been developed in recent years. With the help of artificial intelligence, apps can significantly improve people's lives, solving various dilemmas regarding their health. As medicine is based on statistics, AI can be remarkably useful and accurate for healthcare applications, but there are potential vulnerabilities found in them too. AI can be both an excellent co-worker for improving apps and a great tool for hackers to steal data or compromise the operation of the application. This paper will propose AI algorithms in healthcare applications and their potential vulnerability to adversarial attacks.

CITATION:

IEEE format

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A. Stanković, M. Marjanović, “Adversarial Attacks on Machine Learning Models in Healthcare Applications,” in Sinteza 2024 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2024, pp. 385-391. doi:10.15308/Sinteza-2024-385-391

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Stanković, A., Marjanović, M. (2024). Adversarial Attacks on Machine Learning Models in Healthcare Applications. Paper presented at Sinteza 2024 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2024-385-391

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