INCREASE THE SECURITY OF QR CODES IN MOBILE APPLICATIONS THROUGH AI PROTECTION AGAINST FRAUD AND PHISHING

QR codes have become an important tool in modern mobile applications, allowing users to instantly access various information, make payments, interact with advertising campaigns, and use social networks. Such popularity of QR codes contributes to their rapid spread, but at the same time increases the risk of fraud and phishing attacks. Dangerous QR codes can contain links to fake web pages created by attackers to collect users' personal data or to redirect them to malicious resources that threaten data security and user privacy. This paper focuses on the study of methods to improve the security of QR codes in mobile applications using modern artificial intelligence (AI) algorithms that can detect potentially malicious QR codes and protect user data. The proposed approach involves the use of several AI tools, such as recurrent neural networks (RNNs) for analyzing the structure of URLs, classification algorithms for verifying the legitimacy of domains, and autoencoders for detecting anomalies that may indicate malicious intent. The developed system allows timely detection and blocking of suspicious QR codes, preventing possible attacks on user privacy and misuse of their data. Additionally, the study emphasizes the importance of the data collection and preparation stage for training AI models. Since the quality of the results depends on the completeness and quality of the training data, considerable attention is paid to the development of optimal methods for collecting and filtering information to ensure the effectiveness of detecting malicious elements in QR codes. The use of artificial intelligence to ensure the security of QR codes is a promising area that allows mobile application developers to integrate modern technologies to protect users from fraud and phishing attacks. This approach contributes to the creation of a safer digital environment and increases consumer confidence in mobile technologies, enhancing the overall security of using QR codes in everyday life