SeniorSafeAI: LLM-based Chatbot to Assist Senior Citizen Victims of Cybercrime

This study introduces SeniorSafeAI, an open-source chatbot trained on a curated dataset of cybersecurity Q&As to assist senior citizens in identifying and responding to cybercrimes. We trained and evaluated eight large language models using both quantitative metrics (F1, BertScore, n-gram overlap) and qualitative assessments (clarity, accuracy, relevance, and usefulness). While quantitative results indicate modest performance, qualitative evaluations of top models, including ChatGPT-4o and Qwen2.5 variants, reveal a notable discrepancy between numerical precision/recall and perceived response quality. Future work will focus on further finetuning with an expanded evaluation dataset and conducting user testing to improve usability and interface accessibility.

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Publication Details

Journal
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Published
2025-05-14
DOI
https://doi.org/10.32473/flairs.38.1.138856
Primary Topic
Cybercrime and Law Enforcement Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

SeniorSafeAI: LLM-based Chatbot to Assist Senior Citizen Victims of Cybercrime

Lingyao Li, Loni Hagen, Michael Bolton, Courtney Weber et al.
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference
Cybercrime and Law Enforcement Studies
article

SeniorSafeAI: LLM-based Chatbot to Assist Senior Citizen Victims of Cybercrime

Lingyao Li, Loni Hagen, Michael Bolton, Courtney Weber, Mai-Tram B. Dinh, George W. Burruss
article en

Abstract

This study introduces SeniorSafeAI, an open-source chatbot trained on a curated dataset of cybersecurity Q&As to assist senior citizens in identifying and responding to cybercrimes. We trained and evaluated eight large language models using both quantitative metrics (F1, BertScore, n-gram overlap) and qualitative assessments (clarity, accuracy, relevance, and usefulness). While quantitative results indicate modest performance, qualitative evaluations of top models, including ChatGPT-4o and Qwen2.5 variants, reveal a notable discrepancy between numerical precision/recall and perceived response quality. Future work will focus on further finetuning with an expanded evaluation dataset and conducting user testing to improve usability and interface accessibility.

Proceedings of the ... International Florida Artificial Intelligence Research Society ConferenceVol. 38
University of South Florida (US)
Florida Center for Cybersecurity, University of South Florida
Openalex Percentile: Top 64%
Cybercrime and Law Enforcement Studies
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