Developing and Evaluating Fraud Informatics Curriculum among Institutions in the Appalachian Region

开发和评估阿巴拉契亚地区机构之间的欺诈信息学课程

• 批准号: 1820609
• 负责人: Dongwon Lee
• 金额: $ 49.96万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1820609&HistoricalAwards=false
• 关键词: Developing; Evaluating; Fraud; Informatics; Curriculum

As computer systems and information technologies rapidly advance, various abusive and fraudulent activities ("frauds") proliferate in the cyber world. This proliferation undermines the ecosystem of information systems and the cyber world, making it critically important for the general public, and in particular cybersecurity students, to be aware of popular online frauds, their implications to businesses and societies, and possible methods of prevention and solutions. However, curricula dedicated to online fraud, including new types of fraud, are lacking from existing cybersecurity curricula. To help address the threats of cyberspace and the knowledge gaps in cybersecurity curricula, this collaborative project between Penn State University (PSU) and Oak Ridge Associated Universities (ORAU) proposes to: (1) develop a fraud informatics curriculum with three delivery options (15-week-long offline, 5-week-long online, and 1-day offline), and (2) validate the effectiveness of this curriculum and learning materials by assessing changes in participants' knowledge, skills, and behaviors.This project will incorporate research-based pedagogical methods (i.e., group-based learning, context-based learning, and hands-on learning) to develop learning materials in three delivery options. The curriculum will be uniquely cohesive in its emphasis on recent online fraud and phenomena such as spam emails, social engineering attacks, astroturfing, misinformation, disinformation and data-driven solutions for detecting and preventing such frauds. The curriculum will be delivered by approximately 10 instructors to 400 undergraduate students in the Appalachian region and beyond. The goal is for the curriculum to strengthen the workforce development pipeline, and to ultimately contribute to an unrivaled, diverse cybersecurity workforce and citizenry. Pedagogical findings and course materials will benefit general computing education, specifically students focusing on cybersecurity in broader scientific and engineering communities throughout the nation. Materials developed through this project will be freely available from a project web site: http://fraudinformatics.org/.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.

随着计算机系统和信息技术的迅速发展，各种滥用和欺诈活动（“欺诈”）在网络世界中激增。这种扩散破坏了信息系统和网络世界的生态系统，使公众，特别是网络安全学生，意识到流行的在线欺诈及其对企业和社会的影响以及可能的预防方法和解决方案至关重要。然而，现有的网络安全课程缺乏专门针对网上欺诈，包括新型欺诈的课程。为了帮助解决网络空间的威胁和网络安全课程中的知识差距，宾夕法尼亚州立大学（PSU）和橡树岭联合大学（ORAU）之间的这个合作项目提出：（1）制定欺诈信息学课程，有三种授课方式（15周离线，5周在线，1天离线），及（2）通过评估参加者在知识、技能该项目将采用基于研究的教学方法（即，以小组为基础的学习，基于背景的学习，和动手学习），以开发学习材料的三个交付选项。该课程将独特地强调最近的在线欺诈和现象，如垃圾邮件，社会工程攻击，astroturfing，错误信息，虚假信息和数据驱动的解决方案，用于检测和防止此类欺诈。该课程将由大约10名教师向阿巴拉契亚地区及其他地区的400名本科生提供。该课程的目标是加强劳动力发展管道，并最终为无与伦比的，多样化的网络安全劳动力和公民做出贡献。教学成果和课程材料将有利于普通计算教育，特别是全国更广泛的科学和工程社区中关注网络安全的学生。通过该项目开发的材料将从项目网站免费获得：http://fraudinformatics.org/.This奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger’s Adversarial Attacks

• DOI: 10.18653/v1/2021.acl-long.296
• 发表时间: 2020-11
• 作者: Thai Le;Noseong Park;Dongwon Lee

Detecting False Claims in Low-Resource Regions: A Case Study of Caribbean Islands

检测资源匮乏地区的虚假声明：加勒比群岛案例研究

• 发表时间: 2022
• 期刊: ACL Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situation (CONSTRAINT
• 作者: Lucas, Jason;Cui, Limeng;Le, Thai;Lee, Dongwon
• 通讯作者: Lee, Dongwon

If You Have a Reliable Source, Say Something: Effects of Correction Comments on COVID-19 Misinformation

如果您有可靠的消息来源，请说些什么：更正评论对 COVID-19 错误信息的影响

• 发表时间: 2022
• 期刊: 16th Int'l AAAI Conf. on Web and Social Media (ICWSM
• 作者: Seo, Haeseung;Xiong, Aiping;Lee, Sian;Lee, Dongwon
• 通讯作者: Lee, Dongwon

Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspective

• DOI: 10.1145/3606274.3606276
• 发表时间: 2022-10
• 期刊: ACM SIGKDD Explorations Newsletter
• 作者: Adaku Uchendu;Thai Le;Dongwon Lee

Do Language Models Plagiarize?

• DOI: 10.1145/3543507.3583199
• 发表时间: 2022-03
• 期刊: Proceedings of the ACM Web Conference 2023
• 作者: Jooyoung Lee;Thai Le;Jinghui Chen;Dongwon Lee