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Advanced Cybersecurity Strategies: Leveraging Machine Learning for Deepfake and Malware Defense

EasyChair Preprint no. 12806

8 pagesDate: March 28, 2024


In today's digital landscape, the proliferation of deepfake technology and sophisticated malware poses significant threats to cybersecurity. Traditional methods of defense are proving insufficient against these evolving threats, necessitating the adoption of advanced tactics. This paper explores the application of machine learning techniques as a powerful tool in combating deepfakes and malicious software. By leveraging the capabilities of machine learning, cybersecurity professionals can enhance detection, prevention, and response mechanisms, thereby fortifying defenses against cyber threats. This paper discusses various approaches and strategies for utilizing machine learning in cybersecurity, highlighting its effectiveness in identifying and mitigating the risks posed by deepfakes and malware. Furthermore, it examines the challenges and ethical considerations associated with employing machine learning in cybersecurity practices.

Keyphrases: Artificial Intelligence, Cyber Defense Strategies, Cybersecurity, Deepfakes, machine learning, Malware Defense, Threat Detection

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lia Don},
  title = {Advanced Cybersecurity Strategies: Leveraging Machine Learning for Deepfake and Malware Defense},
  howpublished = {EasyChair Preprint no. 12806},

  year = {EasyChair, 2024}}
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