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AI and Machine Learning in Cybersecurity: Leveraging Technology to Combat Threats

EasyChair Preprint no. 11610

9 pagesDate: December 23, 2023


The rapid evolution of technology has catalyzed the advancement of cybersecurity threats, necessitating innovative approaches to safeguard sensitive information and systems. This abstract explores the role of Artificial Intelligence (AI) and Machine Learning (ML) as pivotal tools in fortifying cybersecurity defenses against an increasingly sophisticated landscape of threats. AI and ML technologies have emerged as indispensable assets in augmenting the capabilities of cybersecurity professionals. Through their capacity to analyze vast amounts of data with speed and precision, these technologies enable the identification of anomalous patterns and potential threats in real time. They empower security systems to adapt dynamically to evolving attack methodologies, mitigating risks and vulnerabilities more effectively. This abstract delves into the various applications of AI and ML in cybersecurity, including anomaly detection, predictive analysis, behavioral analytics, and threat intelligence. Leveraging these technologies equips security teams with proactive measures, enabling preemptive responses to potential breaches and minimizing the impact of cyberattacks. Ultimately, this abstract underscores the critical synergy between AI, ML, and cybersecurity, emphasizing the imperative for ongoing research, collaboration, and innovation. Harnessing the potential of these technologies holds promise in fortifying defenses and creating more resilient systems to combat the ever-evolving landscape of cyber threats.

Keyphrases: Artificial Intelligence, Cybersecurity, Threat Detection

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lee Kasowaki and Koraye Emir},
  title = {AI and Machine Learning in Cybersecurity: Leveraging Technology to Combat Threats},
  howpublished = {EasyChair Preprint no. 11610},

  year = {EasyChair, 2023}}
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