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Innovative Defenses: How AI Redefines Cybersecurity Protocols

EasyChair Preprint no. 13327

10 pagesDate: May 17, 2024

Abstract

The integration of artificial intelligence (AI) into cybersecurity protocols signifies a revolutionary shift in digital defense strategies. AI-powered defense mechanisms offer unparalleled capabilities in threat detection, leveraging extensive data analysis and pattern recognition to identify potential breaches swiftly. This proactive approach not only reduces the risk of successful attacks but also enhances overall resilience by minimizing the window of vulnerability. Moreover, AI-driven defenses redefine traditional cybersecurity protocols by providing adaptive responses that evolve in tandem with the dynamic threat landscape. Continuously learning from new data and experiences, AI systems adapt their defense strategies to counter emerging threats effectively, thereby fortifying the cybersecurity infrastructure of organizations. However, while AI-driven defenses offer promising benefits, they also present challenges such as algorithm bias, adversarial attacks, and ethical considerations. Overcoming these challenges requires a holistic approach that integrates AI technologies with human expertise and oversight. By fostering collaboration between AI systems and human professionals, organizations can harness the full potential of AI-driven defenses while ensuring ethical decision-making and contextual understanding. In conclusion, the integration of AI redefines cybersecurity protocols, offering organizations proactive and adaptive defenses to safeguard their digital assets in an increasingly complex and dynamic threat landscape.

Keyphrases: Cybersecurity, Protocols, Redefines

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:13327,
  author = {Micho Orio and Kurez Oroy},
  title = {Innovative Defenses: How AI Redefines Cybersecurity Protocols},
  howpublished = {EasyChair Preprint no. 13327},

  year = {EasyChair, 2024}}
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