Knowledge Graph based Learning Guidance for Cybersecurity Hands-on Labs
Knowledge Graph based Learning Guidance for Cybersecurity Hands-on Labs
复制标题
基于知识图的网络安全动手实验室学习指南
DOI：
10.1145/3300115.3309531
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Lin, Fanjie
中科院分区：
文献类型：
--
作者：
Deng, Yuli;Lu, Duo;Huang, Dijiang;Chung, Chun-Jen;Lin, Fanjie
动手实践是网络安全教育的重要组成部分。大多数现有的实践练习或实验室材料通常以问题为中心进行管理，而它缺乏一种连贯的方式来管理现有的实验室，并为网络安全学习者提供富有成效的实验室练习计划。随着大数据和自然语言处理（NLP）技术的优势，构建一个大的知识图和挖掘概念从非结构化文本成为可能，这促使我们建立一个基于机器学习的网络安全教育实验练习计划。在本文提出的研究中，我们已经构建了一个知识图谱在网络安全领域使用自然语言处理技术，包括机器学习的词嵌入和基于超链接的概念挖掘。然后，我们基于以下方法在常规学习过程中使用知识图：1.构建了一个基于Web的前端知识图谱可视化平台，学生可以通过该平台浏览和搜索网络安全相关概念以及相应的相互依赖关系; 2.我们根据每个学生的学习进度和状态为他们创建了个性化的知识图谱; 3.我们建立了一个个性化的实验室推荐系统，根据学生过去的学习历史，建议更多相关的实验室，以最大限度地提高他们的学习成果。为了衡量所提出的解决方案的有效性，我们进行了用例研究，并从研究生级别的网络安全课程中收集了调查数据。我们的研究表明，通过利用知识图谱进行网络安全领域的研究，学生往往会受益更多，并对网络安全领域表现出更多的兴趣。
Hands-on practice is a critical component of cybersecurity education. Most of the existing hands-on exercises or labs materials are usually managed in a problem-centric fashion, while it lacks a coherent way to manage existing labs and provide productive lab exercising plans for cybersecurity learners. With the advantages of big data and natural language processing (NLP) technologies, constructing a large knowledge graph and mining concepts from unstructured text becomes possible, which motivated us to construct a machine learning based lab exercising plan for cybersecurity education. In the research presented by this paper, we have constructed a knowledge graph in the cybersecurity domain using NLP technologies including machine learning based word embedding and hyperlink-based concept mining. We then utilized the knowledge graph during the regular learning process based on the following approaches: 1. We constructed a web-based front-end to visualize the knowledge graph, which allows students to browse and search cybersecurity-related concepts and the corresponding interdependence relations; 2. We created a personalized knowledge graph for each student based on their learning progress and status; 3. We built a personalized lab recommendation system by suggesting more relevant labs based on students' past learning history to maximize their learning outcomes. To measure the effectiveness of the proposed solution, we have conducted a use case study and collected survey data from a graduate-level cybersecurity class. Our study shows that, by leveraging the knowledge graph for the cybersecurity area study, students tend to benefit more and show more interests in cybersecurity area.
影响因子：
22.7
作者：
MILLER, GA
通讯作者：
MILLER, GA
网络安全课程指南
DOI：
--
发表时间：
2017
期刊：
WISE
影响因子：
--
作者：
M. Bishop;D. Burley;Scott Buck;J. Ekstrom;L. Futcher;David S. Gibson;Elizabeth K. Hawthorne;Siddharth Kaza;Y. Levy;H. Mattord;Allen S. Parrish
通讯作者：
Allen S. Parrish
计算机科学教育虚拟实践实验室平台中的个性化学习
DOI：
10.1109/fie.2018.8659291
发表时间：
2018
期刊：
IEEE Frontiers in Education Conference (FIE
影响因子：
--
作者：
Deng, Yuli;Lu, Duo;Chung, Chun-Jen;Huang, Dijiang;Zeng, Zhen
通讯作者：
Zeng, Zhen