机器学习在勒索软件检测和预防中的真实学习

Md Jobair Hossain Faruk, Mohammad Masum, H. Shahriar, K. Qian, D. Lo
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引用次数: 3

摘要

真实学习的主要目标是为学生提供一个有吸引力和激励的学习环境,让学生有解决现实世界安全问题的实践经验。每个学习主题包括实验前、实验和实验后(Pre/ lab /Post)活动。采用真实的学习方法,我们在谷歌CoLab上为ML设计和开发了用于勒索软件检测和预防的便携式实验室软件,使学生可以随时随地访问和练习这些动手实验室,而无需时间繁琐的安装和配置,这将帮助学生更专注于概念的学习,并获得更多动手解决问题的经验技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Authentic Learning of Machine Learning to Ransomware Detection and Prevention
The primary goal of the authentic learning provides students with an engaging and motivating learning environment for students with hands-on experiences in solving real-world security problems. Each learning topic consists of pre-lab, lab, and post-lab (Pre/Lab/Post) activities. With an authentic learning approach, we design and develop portable labware on Google CoLab for ML for ransomware detection and prevention so that students can access and practice these hands-on labs anywhere and anytime without time tedious installation and configuration which will help students more focus on learning of concepts and getting more experience for hands-on problem-solving skills.
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