Citation :

Rahul Gupta, 2024. "Safeguarding Digital Privacy with AI-Driven Solutions" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 2, Issue 1: 126-142.

Abstract :

Data protection has emerged as one of the most significant issues in the modern world due to the ever-increasing accumulation and use of personal information. The use and application of artificial intelligence include the following opportunities and threats that are associated with the subject. This article aims to discuss multiple approaches to AI-based solutions targeting the protection of individuals’ data and innovative implementations of the mentioned approaches. Explaining methods related to privacy-preserving of AI, like differential privacy that adds noise to the data to prevent identification of individuals or federated learning that enables joint model updating across devices, but without pooling data. Also, it is important to review modern encryption types, such as homomorphic encryption, that allow computational operations on encrypted information without their decryption. The paper also looks at the cardinal issue of how privacy can be preserved while making information as useful as possible. This section focuses on the ethical implications with a common understanding of their importance, which includes the aspects of openness, equal treatment, and responsibility. In addition, the article also discusses some of the existing regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), that offer guidance in data protection and privacy Shields. Thus, through the reasonable implementation of AI, it becomes possible to design effective protection of individuals’ rights to privacy alongside progress in technologies. This holistic approach ensures that personal data is safeguarded from breaches and other forms of misuse, hence enhancing security, especially in the contemporary world. This way, the study is going to try to dissect the directions of AI utilization to improve digital privacy while recognizing the opportunities and limits of these technologies.

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Keywords :

Digital Privacy, Ai, Differential Privacy, Federated Learning, Data Security, Privacy Laws.