Developing Innovative Privacy Learning Modules to Engage Students in Cybersecurity Education

开发创新的隐私学习模块，让学生参与网络安全教育

• 批准号: 1712496
• 负责人: Na Li
• 金额: $ 30万
• 依托单位: Prairie View A & M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1712496&HistoricalAwards=false
• 关键词: Developing; Innovative; Privacy; Learning; Modules

The rapid development of Internet services such as cloud computing, social networks, and mobile applications has increased attention to privacy protection by both industry and academia. Demand for information security is at an all-time high, creating an urgent shortfall in the national workforce. Despite recognized and critical societal needs, privacy education has not been integrated satisfactorily into undergraduate Computer Science (CS) curricula. A serious lack of effective learning materials to help students understand critical privacy concepts and gain hands-on skills has created a barrier to expanding privacy education. To address this concern and better prepare qualified graduates for the future U.S. workforce, researchers from Prairie View A&M University (PVAMU) and the University of Tennessee at Chattanooga (UTC) will collaboratively develop hands-on learning materials on privacy protection and explore optimal integration of privacy into undergraduate cybersecurity education.This project serves the national interest by designing and develop innovative learning modules on cutting-edge privacy topics identified by federal funding priorities to respond to the lack of hands-on based curriculum in privacy and cybersecurity education. These new self-contained learning modules with real-world hands-on labs will not only enrich the CS curricula at the two participating institutions (PVAMU and UTC), but also ensure that they can be easily adopted by other institutions. With these modules, the PIs will revamp related CS core and elective courses, and develop a new course on privacy, which will have profound impacts on both the CS curriculum and student learning at PVAMU and UTC. As an HBCU, underrepresented minorities at PVAMU will benefit from this project. In addition, the project will evaluate the effectiveness of an experiential learning approach based on student learning outcomes, experiences, and motivation, and attitudes toward privacy issues. Project research data, developed learning modules, and teaching materials will be actively disseminated to the research and educational community to benefit other institutions and enrich the NSF cybersecurity learning material repository.

云计算、社交网络、移动应用等互联网服务的快速发展，使得隐私保护日益受到工业界和学术界的关注。对信息安全的需求空前高涨，造成国家劳动力的紧急短缺。尽管社会需求得到认可且至关重要，但隐私教育尚未令人满意地融入本科计算机科学 (CS) 课程。严重缺乏有效的学习材料来帮助学生理解重要的隐私概念并获得实践技能，这为扩大隐私教育造成了障碍。为了解决这一问题并更好地为未来的美国劳动力培养合格的毕业生，Prairie View A&M University (PVAMU) 和田纳西大学查塔努加分校 (UTC) 的研究人员将合作开发隐私保护实践学习材料，并探索将隐私最佳地融入本科网络安全教育中。该项目通过设计和开发前沿隐私的创新学习模块来服务于国家利益。 联邦资助优先事项确定的主题，以应对隐私和网络安全教育方面缺乏实践基础的课程。这些新的独立学习模块以及真实的动手实验室不仅将丰富两个参与机构（PVAMU 和 UTC）的计算机科学课程，而且还确保它们可以轻松地被其他机构采用。通过这些模块，PI将改进相关的CS核心和选修课程，并开发一门新的隐私课程，这将对PVAMU和UTC的CS课程和学生学习产生深远的影响。作为 HBCU，PVAMU 中代表性不足的少数群体将从该项目中受益。此外，该项目还将根据学生的学习成果、经验、动机以及对隐私问题的态度来评估体验式学习方法的有效性。项目研究数据、开发的学习模块和教材将积极向研究和教育界传播，以使其他机构受益并丰富 NSF 网络安全学习材料库。

项目成果

IDEAL: An Interactive De-Anonymization Learning System

IDEAL：交互式去匿名学习系统

• DOI: 10.1109/compsac48688.2020.0-210
• 发表时间: 2020
• 期刊: and Applications Conference
• 作者: Li, Na;Murugesan, Rajkumar;Li, Lin;Zheng, Hao
• 通讯作者: Zheng, Hao

Efficiently discovering people connectivity in Online Social Networks

有效发现在线社交网络中的人员联系

• 发表时间: 2020
• 期刊: Online social networks and media
• 作者: Li, Na;Das, Sajal K
• 通讯作者: Das, Sajal K

Facelock―A Labware for Teaching Photo Privacy in Online Social Networks Through Face Recognition

Facelock——一款通过人脸识别教授在线社交网络中照片隐私的实验室软件

• 发表时间: 2020
• 期刊: Journal of computing sciences in colleges
• 作者: Shormin, Sadia;Li, Lin;Li, Na
• 通讯作者: Li, Na

Learning and Preserving Relationship Privacy in Photo Sharing

• DOI: 10.1109/bdcat56447.2022.00029
• 发表时间: 2022-12
• 期刊: 2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT)
• 作者: Jialin Liu;Lin Li;Na Li

Hands-on Lab Development for Policy Violations in Voice Personal Assistants

语音个人助理政策违规的实践实验室开发

• 发表时间: 2023
• 期刊: Journal of computing sciences in colleges
• 作者: Sanchez, Alejandra Enriquez;Ogunbowale, Oludare;Adetola, Olayinka;Li, Na
• 通讯作者: Li, Na