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EAGER: DCL: SaTC: Enabling Interdisciplinary Collaboration: Studying Social Engineering Attacks Targeting Vulnerable Refugee Populations

EAGER: DCL: SaTC: Enabling Interdisciplinary Collaboration: Studying Social Engineering Attacks Targeting Vulnerable Refugee Populations
EAGER:DCL:SaTC:实现跨学科合作:研究针对弱势难民群体的社会工程攻击
批准号:
2210185
负责人:
Mythili Menon
金额:
$29.65万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-07-01 至 2024-06-30

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英文摘要
Two recent world events, an ongoing pandemic together with continuing regional wars and conflicts, have resulted in a sizable number of refugee population being forcibly displaced and resettled in the United States. Lack of English-language and digital literacy skills have made the refugee community an easy target for new and increased social engineering attacks. This project’s overarching goal is to study how language and linguistic features impact the perception and response of refugees to social engineering attacks. The project’s novelties are a) a language- or linguistic-centric approach for understanding social engineering threats to refugees resulting in development of novel educational materials, open access datasets, and improved cybersecurity policies to counter these threats, and b) tailored digital literacy and educational programs and workshops to raise awareness and mitigate social engineering threats among the refugee population. The project’s broader significance and importance are a) improved protection models and prevention techniques against social engineering attacks, b) informed policies and tools, resulting in better social and economic security, and reduced inequity gap within the vulnerable refugee population, and c) enhanced refugee integration into the U.S. society through increased awareness of cybersecurity threats. The project team systematically study the linguistic cues and triggers associated with social engineering attacks such as phishing and vishing. The deliverables and key contributions of the project include a) preliminary results documenting the impact of linguistic traits of the refugee population on their susceptibility to real-world social engineering attacks, b) open-access datasets of phishing emails, and voice calls, with attributions of interactions to promote further research, c) recommendations to improve cybersecurity policies including vulnerable population, resulting in the creation of new STEM educational material for the refugee population, and d) follow-up educational workshops to debrief, discuss, and disseminate relevant educational material to the target refugee population.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.
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  • 资助金额:
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