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Designing A New Graduate Course on Artificial Intelligence for Cybersecurity

Authors:
Ping Wang

Keywords: AI; cybersecurity; vulnerability; learning outcomes; assessment.

Abstract:
Artificial intelligence (AI) technologies and solutions are increasingly integrated into various applications and domains of studies. Generative AI (Gen AI) also has significant impacts and implications for the fast-growing field of Cybersecurity and cybersecurity education for workforce development. This research proposes the design of a new graduate master’s level credit course to integrate AI into cybersecurity education. This new course explores the evolving impacts of artificial intelligence on the cybersecurity ecosystem. The course is intended for students to learn to identify and evaluate AI-powered cyber threats and attacks and their implications as well as to utilize AI-powered systems for enhancing cyber threat detection, incident response, security automation, vulnerability analytics, and security risk assessment. The proposed course design will summarize initial suggestions of main topics, outcomes, activities, and assessment criteria for implementation.

Pages: 1 to 2

Copyright: Copyright (c) IARIA, 2025

Publication date: July 6, 2025

Published in: conference

ISBN: 978-1-68558-287-6

Location: Venice, Italy

Dates: from July 6, 2025 to July 10, 2025