<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>Creating Your Own Hands-on Cybersecurity Exercises</dc:title><dc:creator>Weiss, Richard; Mache, Jens; Cook, Jack</dc:creator><dc:corporate_author/><dc:editor/><dc:description>Cybersecurity is a topic of growing interest. Do you have hands-on exercises that match the skills and levels of your students? Over the last few years, we have worked on making it easier to create, modify, and deploy exercises with assessment questions. EDURange is an open source project with exercises that span a wide range and can serve as templates for new ones. In addition to providing a framework for editing exercises, EDURange also allows Instructors to see student interaction and offer hints while they are doing the exercise. The features, that support this include chat with the instructor and machine learning algorithms for identifying which students need help.
We plan to share some of the existing exercises and show how to adapt them to different students' profiles. We will also share our experiences with the hint system. Participants will gain experience in designing and adapting cybersecurity exercises and writing learning objectives and assessments. All backgrounds are welcome, whether you are new to teaching cybersecurity and have little experience with the command line, or whether you can create a network of containers and bash scripts to configure them. You will come away with a better understanding of how to design and create your own hands-on exercises.</dc:description><dc:publisher>ACM</dc:publisher><dc:date>2025-02-18</dc:date><dc:nsf_par_id>10595439</dc:nsf_par_id><dc:journal_name/><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation>1775 to 1775</dc:page_range_or_elocation><dc:issn/><dc:isbn>9798400705328</dc:isbn><dc:doi>https://doi.org/10.1145/3641555.3704764</dc:doi><dcq:identifierAwardId>2216492; 2216485</dcq:identifierAwardId><dc:subject>security and privacy</dc:subject><dc:subject>machine learning</dc:subject><dc:subject>interactive learning</dc:subject><dc:version_number/><dc:location>Pittsburgh PA USA</dc:location><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>