Secure Use of Artificial Intelligence with Artificial Intelligence Based Control
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Abstract
Artificial intelligence applications have increased in recent years, providing benefits that increase the productivity of individuals and organizations. Individuals and organizations consult with AI tools in many areas, seek their assistance, and create value using these tools. However, the use of AI tools brings with it various security concerns. Open-source AIs have higher capabilities than those hosted on-premise environments. This encourages individuals and organizations to use open-source or paid versions. This study aims to identify and prevent unauthorized sharing of potentially sensitive data with third parties during paid or open-source use of AI tools using AI-assisted detection and prevention. The study, aims to use a combination of natural language processing, big data, and machine learning methods during detection processes, will also focus on customizing the models to be organizations or person-focused, in addition to general sensitive data, and increasing success in capturing sensitive data by fine-tuning the models. It will enable the implementation of blocking or masking processes after a successful detection process.
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