NSF Convergence Accelerator Track F: Online Deception Awareness and Resilience Training (DART)
NSF 融合加速器轨道 F:在线欺骗意识和弹性培训 (DART)
基本信息
- 批准号:2230494
- 负责人:
- 金额:$ 500万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Cooperative Agreement
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-15 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
As one of the most vexing problems of the century, we are witnessing the escalating speed, scale, and level of sophistication of online deception (spear phishing and catfishing scams, personal information hunting schemes, fake content, impersonation, and disinformation on social media) that have severe consequences (ransomware attack, financial loss, and breach of private information). The most vulnerable demographic is older adults, who are disproportionately targeted for online exploitation, manipulation, and fraud resulting in significant financial loss and emotional distress. Deception Awareness and Resilience Training (DART) aims to equip older adults with the tools they need to recognize various forms of online deception and help others in their social circle avoid or mitigate harm. Designed by experts in education, psychology, communication, cybersecurity, and media studies, the DART curriculum contains high-quality and timely synthetic contents and real-world scenarios. The DART project team includes experts in psychology, communications and media, economics, cybersecurity, computer science, game design, synthetic media, and aging studies. DART deliverables will be developed by a professional development team and tested with older adults.The DART system consists of two complementary components: (1) DART Learn: a web-based structured, dynamic, and self-paced learning program on online deceptions. (2) DART Practice: an interactive social media simulation that provides a safe and realistic platform for the users to practice what they learned about online deception. (3) DART Play: a set of simple, fun mobile Games on mobile platforms (iOS and Android) designed to familiarize older adults with common deceptions.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.
作为本世纪最令人烦恼的问题之一,我们目睹了在线欺骗的速度,规模和水平的升级(长矛网络钓鱼和cat鱼骗局,个人信息狩猎方案,虚假内容,对社交媒体的冒充和虚假信息)具有严重的后果(Ransomware攻击,金融攻击,财务损失,私人信息)。最脆弱的人群是老年人,他们针对在线剥削,操纵和欺诈的目标不成比例,从而造成了巨大的财务损失和情绪困扰。欺骗意识和弹性训练(DART)旨在为老年人配备所需的工具,以识别各种形式的在线欺骗,并帮助他人的社交圈子中的其他人避免或减轻伤害。 DART课程由教育,心理学,沟通,网络安全和媒体研究专家设计,其中包含高质量且及时的合成内容和现实世界情景。 DART项目团队包括心理学,传播和媒体,经济学,网络安全,计算机科学,游戏设计,合成媒体和衰老研究专家。 DART可交付成果将由专业开发团队开发,并与老年人进行了测试。该飞镖系统由两个互补的组成部分组成:(1)DART学习:基于网络的结构化,动态和自定进度的学习计划。 (2)DART实践:一种交互式社交媒体模拟,为用户提供了一个安全,现实的平台,以练习他们对在线欺骗的了解。 (3)DART PLAY:在移动平台(iOS和Android)上的一组简单有趣的手机游戏旨在使老年人具有共同的欺骗。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准通过评估来进行评估的。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

暂无数据
数据更新时间:2024-06-01
Siwei Lyu其他文献
Deep Constrained Low-Rank Subspace Learning for Multi-View Semi-Supervised Classification
用于多视图半监督分类的深度约束低秩子空间学习
- DOI:10.1109/lsp.2019.292385710.1109/lsp.2019.2923857
- 发表时间:20192019
- 期刊:
- 影响因子:0
- 作者:Zhe Xue;Junping Du;Dawei Du;Guorong Li;Qingming Huang;Siwei LyuZhe Xue;Junping Du;Dawei Du;Guorong Li;Qingming Huang;Siwei Lyu
- 通讯作者:Siwei LyuSiwei Lyu
Countering JPEG anti-forensics based on noise level estimation
基于噪声水平估计的 JPEG 反取证对抗
- DOI:10.1007/s11432-016-0426-110.1007/s11432-016-0426-1
- 发表时间:2017-082017-08
- 期刊:
- 影响因子:0
- 作者:Hui Zeng;Xiangui Kang;Jingjing Yu;Siwei LyuHui Zeng;Xiangui Kang;Jingjing Yu;Siwei Lyu
- 通讯作者:Siwei LyuSiwei Lyu
Online Deformable Object Tracking Based on Structure-Aware Hyper-Graph
基于结构感知超图的在线变形目标跟踪
- DOI:10.1109/tip.2016.257055610.1109/tip.2016.2570556
- 发表时间:2016-082016-08
- 期刊:
- 影响因子:10.6
- 作者:Dawei Du;Honggang Qi;Wenbo Li;Longyin Wen;Qingming Huang;Siwei LyuDawei Du;Honggang Qi;Wenbo Li;Longyin Wen;Qingming Huang;Siwei Lyu
- 通讯作者:Siwei LyuSiwei Lyu
Vertebral artery course variation leading to an insufficient proximal anchoring area for thoracic endovascular aortic repair.
椎动脉走行变化导致胸主动脉腔内修复的近端锚固区域不足。
- DOI:10.1177/1708538122114031910.1177/17085381221140319
- 发表时间:20222022
- 期刊:
- 影响因子:1.1
- 作者:Zuanbiao Yu;Siwei Lyu;Dehai Lang;Di Wang;Songjie Hu;Xiaoliang Yin;Yunpeng Ding;Chunbo Xu;Chen Lin;Jiangnan HuZuanbiao Yu;Siwei Lyu;Dehai Lang;Di Wang;Songjie Hu;Xiaoliang Yin;Yunpeng Ding;Chunbo Xu;Chen Lin;Jiangnan Hu
- 通讯作者:Jiangnan HuJiangnan Hu
Nonnegative matrix factorization with matrix exponentiation
- DOI:10.1109/icassp.2010.549497510.1109/icassp.2010.5494975
- 发表时间:2010-032010-03
- 期刊:
- 影响因子:0
- 作者:Siwei LyuSiwei Lyu
- 通讯作者:Siwei LyuSiwei Lyu
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Siwei Lyu的其他基金
SaTC: CORE: Small: Combating AI Synthesized Media Beyond Detection
SaTC:核心:小型:对抗无法检测的人工智能合成媒体
- 批准号:21531122153112
- 财政年份:2022
- 资助金额:$ 500万$ 500万
- 项目类别:Standard GrantStandard Grant
NSF Convergence Accelerator Track F: A Disinformation Range to Improve User Awareness and Resilience to Online Disinformation
NSF 融合加速器轨道 F:提高用户对在线虚假信息的认识和抵御能力的虚假信息范围
- 批准号:21378712137871
- 财政年份:2021
- 资助金额:$ 500万$ 500万
- 项目类别:Standard GrantStandard Grant
RI: Small: A Study of New Aggregate Losses for Machine Learning
RI:小:机器学习新总损失的研究
- 批准号:20085322008532
- 财政年份:2020
- 资助金额:$ 500万$ 500万
- 项目类别:Standard GrantStandard Grant
RI: Small: A Study of New Aggregate Losses for Machine Learning
RI:小:机器学习新总损失的研究
- 批准号:21034502103450
- 财政年份:2020
- 资助金额:$ 500万$ 500万
- 项目类别:Standard GrantStandard Grant
NRI: Collaborative Research: A Dynamic Bayesian Approach to Real Time Estimation and Filtering in Grasp Acquisition and Other Contact Tasks (Continuation)
NRI:协作研究:抓取采集和其他接触任务中实时估计和过滤的动态贝叶斯方法(续)
- 批准号:15372571537257
- 财政年份:2015
- 资助金额:$ 500万$ 500万
- 项目类别:Standard GrantStandard Grant
Blind Noise Estimation Using Signal Statistics in Random Band-Pass Domains
使用随机带通域中的信号统计进行盲噪声估计
- 批准号:13198001319800
- 财政年份:2013
- 资助金额:$ 500万$ 500万
- 项目类别:Standard GrantStandard Grant
NRI-Small: Collaborative Research: A Dynamic Bayesian Approach to Real-Time Estimation and Filtering in Grasp Acquisition and Other Contact Tasks
NRI-Small:协作研究:在抓取采集和其他接触任务中进行实时估计和过滤的动态贝叶斯方法
- 批准号:12084631208463
- 财政年份:2012
- 资助金额:$ 500万$ 500万
- 项目类别:Standard GrantStandard Grant
CAREER: A New Statistical Framework for Natural Images with Applications in Vision
职业:一种新的自然图像统计框架及其在视觉中的应用
- 批准号:09533730953373
- 财政年份:2010
- 资助金额:$ 500万$ 500万
- 项目类别:Continuing GrantContinuing Grant
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Landau方程和Vlasov-Poisson-Boltzmann方程组解的适定性和收敛率的研究
- 批准号:12301284
- 批准年份:2023
- 资助金额:30 万元
- 项目类别:青年科学基金项目
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- 批准号:12301228
- 批准年份:2023
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- 项目类别:青年科学基金项目
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- 资助金额:44.00 万元
- 项目类别:面上项目
深度神经网络的收敛性理论
- 批准号:12371103
- 批准年份:2023
- 资助金额:44.00 万元
- 项目类别:面上项目
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