EAGER: SaTC-EDU: Exploring Visualized and Explainable Artificial Intelligence to Improve Students’ Learning Experience in Digital Forensics Education

EAGER：SaTC-EDU：探索可视化和可解释的人工智能，以改善学生在数字取证教育中的学习体验

基本信息

批准号：
2039288
负责人：
Dianxiang Xu
金额：
$ 9万
依托单位：
University of Missouri-Kansas City
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2039288&HistoricalAwards=false
关键词：
EAGER SaTC EDU Exploring Visualized

项目摘要

With the exponential increase in cybercrimes in recent years, the need for Computer Forensics and Digital Evidence (CFDE) expertise is rapidly growing. A qualified CFDE professional needs to have deep knowledge of digital forensic evidence identification, acquisition, and examination, as well as the ability to present and explain digital forensic evidence in courtrooms. However, there are major barriers to instilling the core knowledge of CFDE and practice of cyber investigation techniques in a diverse body of interested students. For example, a systematic approach for collecting, organizing, and analyzing digital forensic evidence is lacking. This project will engage novel interdisciplinary perspectives, including artificial intelligence (AI), cybersecurity, criminal justice, and computer science to re-examine the emerging CFDE field with a formal approach. This project will then explore visualized and explainable AI to improve students’ learning experience in digital forensics education at Minority-Serving Institutions (MSIs) including Historically Black Colleges and Universities (HBCUs).The project brings together faculty from the University of Baltimore, an MSI, Bowie State University, one of the oldest HBCUs in Maryland, and the University of Missouri Kansas City, who have synergistic expertise in digital forensics, cybersecurity, AI, law, and computer science. The project will leverage graph-based AI models to provide students with visualized depictions of forensic evidence, the patterns of evidence, and the connections among the evidence. It will also explore explainable AI to support the development of forensic evidence that is accountable and presentable to courts, and develop AI-aided CFDE instructional materials. The project will address research questions at the intersection of AI, CFDE, and education including the following: (a) How do graph-based models store, retrieve, and present digital forensic evidence? (b) How do graph-based AI models discover new evidence and to what extent should we trust AI-discovered evidence/patterns? (c) How can knowledge and techniques of AI-assisted investigation be infused into CFDE instructional materials, and to what extent do the materials improve students’ learning experiences? Learning materials will be made available to both the CFDE and data science communities. This project is supported by a special initiative of the Secure and Trustworthy Cyberspace (SaTC) program to foster new, previously unexplored, collaborations between the fields of cybersecurity, artificial intelligence, and education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

近年来，随着网络犯罪的指数增长，对计算机取证和数字证据（CFDE）专业知识的需求正在迅速增长。合格的CFDE专业人员需要深入了解数字法医证据识别，获取和检查，以及在法庭中呈现和解释数字法医证据的能力。但是，在各种有趣的学生中灌输了CFDE的核心知识和网络调查技术实践的主要障碍。例如，缺乏一种用于收集，组织和分析的数字法医证据的系统方法。该项目将吸引新的跨学科观点，包括人工智能（AI），网络安全，刑事司法和计算机科学，以正式的方法重新检查新兴的CFDE领域。 This project will then explore visualized and explainable AI to improve students’ learning experience in digital forensics education at Minority-Serving Institutions (MSIs) including Historically Black Colleges and University (HBCUs).The project brings together faculty from the University of Baltimore, an MSI, Bowie State University, one of the oldest HBCUs in Maryland, and the University of Missouri Kansas City, who have synergistic expertise in digital forensics,网络安全，人工智能，法律和计算机科学。该项目将利用基于图的AI模型为学生提供法医证据，证据模式以及证据之间的联系。它还将探索可解释的AI，以支持法院对法院负责和表现出的法医证据的发展，并开发AI辅助的CFDE教学材料。该项目将在AI，CFDE和教育的交集中解决研究问题，包括以下内容：（a）基于图形的模型如何存储，检索和现在的数字法医证据？（b）基于图的AI模型如何发现新的证据？我们应该在多大程度上信任AI发现的证据/模式？（c）如何将AI辅助调查的技术感染到CFDE教学材料中，这些材料在多大程度上改善了学生的学习经验？学习材料将提供给CFDE和数据科学社区。该项目得到了安全且值得信赖的网络空间（SATC）计划的特别主动，以促进网络安全，人工智能和教育领域之间的新，以前出乎意料的合作。 SATC计划与联邦网络安全研究与发展战略计划以及国家隐私研究策略保持一致，以保护和维护网络系统的社会和经济益处，同时确保安全和隐私。该奖项反映了NSF的法定任务，并通过使用基金会的知识和更广泛的影响来评估NSF的法定使命，并通过评估诚实地表示支持。