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Cybersecurity in the Age of AI: A Proactive Defense Approach

EasyChair Preprint no. 13306

9 pagesDate: May 16, 2024

Abstract

In the contemporary landscape of cybersecurity, the integration of artificial intelligence (AI) represents a transformative leap towards proactive defense methodologies. In contrast to conventional reactive strategies, which often struggle to keep pace with evolving threats, AI-driven approaches offer the potential to anticipate and neutralize cyber risks before they materialize. By harnessing the power of AI algorithms to analyze vast streams of data in real-time, organizations can detect subtle anomalies and patterns indicative of impending attacks, thereby gaining a crucial advantage in safeguarding their digital assets. , AI augments cybersecurity defenses with adaptive and context-aware capabilities, significantly enhancing their effectiveness and resilience. These systems continually refine their algorithms based on new information, enabling them to adapt dynamically to emerging threats. By contextualizing security decisions within the broader framework of user behavior, network topology, and threat intelligence, AI-driven defenses empower organizations to prioritize and respond to risks with unparalleled precision, ultimately fortifying their cybersecurity posture in the age of AI.  These systems continuously learn from new data, allowing them to evolve and adapt to emerging threats dynamically. By contextualizing security decisions based on factors such as user behavior, network context, and threat intelligence, AI-driven defenses enable organizations to prioritize and respond to risks more effectively, ultimately fortifying their cybersecurity posture in the age of AI.

Keyphrases: approach, Defense, Proactive

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:13306,
  author = {Jane Smith and Patrick Thomas},
  title = {Cybersecurity in the Age of AI: A Proactive Defense Approach},
  howpublished = {EasyChair Preprint no. 13306},

  year = {EasyChair, 2024}}
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