INTERNATIONAL JOURNAL FOR INNOVATIVE RESEARCH IN MULTIDISCIPLINARY FIELD

Abstract:    The research emphasises the necessity of robust techniques to preserve the integrity of medical data, highlighting the growing threat of data poisoning in Artificial Intelligence (AI) systems used in the healthcare industry. Among the goals are assessing data poisoning methods as a defensive weapon, finding weaknesses, and suggesting technical and legislative fixes. Using databases such as Scopus and Web of Science, along with sophisticated analytical methods to identify patterns, the approach combines a qualitative and exploratory study with a systematic literature review (2017-2025). The findings showed a 39.5% rise in publications on the subject in 2023, stressing phishing (47%) as the major danger and data poisoning as a potential technique, along with firewalls and cybersecurity education. The combination of AI with methods like data poisoning, backed by legal frameworks (e.g., HIPAA, GDPR) and interdisciplinary cooperation, is seen as vital to reducing risks. All recommendations are looking at new technologies, including blockchain, developing specific policies for AI in healthcare, and investing in continuous training. Future lines of research should look at how effectively these tactics perform against evolving threats and how they impact patient privacy.