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  Published Paper Details:

  Paper Title

Adversarial Attacks and Defenses in Generative AI: A Comparative Analysis

  Authors

  Sanjay Kumar

  Keywords

Artificial Intelligence, Adversarial, Generative, Gradient, Perturbation, Deep Learning

  Abstract


This research paper explores the landscape of adversarial attacks and defenses in generative artificial intelligence (AI) systems. It provides an overview of different attack techniques and their impact on AI models. The paper also discusses various defense mechanisms, including adversarial training, randomization techniques, and model monitoring. Evaluating the effectiveness of attacks and defenses is discussed, along with the need for ongoing research to stay ahead of evolving threats. The research aims to enhance understanding of adversarial threats in generative AI and promote the development of secure deployment strategies for these technologies.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT24A4508

  Paper ID - 258141

  Page Number(s) - n97-n103

  Pubished in - Volume 12 | Issue 4 | April 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Sanjay Kumar,   "Adversarial Attacks and Defenses in Generative AI: A Comparative Analysis", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 4, pp.n97-n103, April 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A4508.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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