E. Dritsas, M. Trigka, Ph. Mylonas |
A Survey on Privacy-Enhancing Techniques in the Era of Artificial Intelligence |
4th International Conference on Novel & Intelligent Digital Systems (NiDS 2024), September 25-27, 2024, Athens, Greece |
ABSTRACT
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In the era of Big Data and Artificial Intelligence (AI), the unprecedented scale and complexity of data collection, processing, and analysis pose significant privacy challenges. This paper presents the first findings of a survey in progress providing a comprehensive and focused overview of privacy-enhancing technologies (PETs) designed to mitigate these challenges and ensure the protection of sensitive information. We explore cryptographic and non-cryptographic techniques including differential privacy (DP), homomorphic encryption (HE), secure multi-party computation (SMPC), and federated learning (FL). Each of these techniques is examined in terms of its basic principles and advantages. Also, some key challenges for implementing PETs are briefly discussed. Finally, we conclude the survey by denoting our future research directions in the field.
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25 September, 2024 |
E. Dritsas, M. Trigka, Ph. Mylonas, "A Survey on Privacy-Enhancing Techniques in the Era of Artificial Intelligence", 4th International Conference on Novel & Intelligent Digital Systems (NiDS 2024), September 25-27, 2024, Athens, Greece |
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