Sentinel AI-powered security game platform¶
Product or Programme · All products and programmes
Evidence · 2 claims (2 for) · 1 study (1 design),q2· 0 of 1 report an effect size · 2 claims rest on one study
Description¶
Sentinel is a mobile game platform developed by Bingjun Li et al. that uses AI-driven adversarial personas, subgames, analytics, and badges to train college students in phishing, password security, and social-engineering awareness.
Components¶
- Sentinel AI-powered security game platform with LLM-driven adversarial persona and badge system: Sentinel is an AI-powered mobile game platform offering subgames on phishing detection, password cracking, text scams, and phone call scams. Its core interaction engine uses a Large Language Model (Google Gemini API) fine-tuned with system prompts defining the attacker's persona, with LLM output piped through a low-latency ElevenLabs text-to-speech engine for realistic voice modulation. The platform "provides player analytics and a badge-reward system to enhance motivation and sustained engagement," and adjusts scam sophistication based on the user's initial streak. (Bingjun Li et al. (2025))
Claims¶
- Expert reviewers rated the TikTok mini-game most engaging and the Text Phishing Detective game highest in learning value [+M]
- College students overwhelmingly prefer short, mobile-friendly gamified security training over long desktop training or videos [+M]
Related Products and Programmes¶
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Key Sources¶
- Bingjun Li, Christopher Buzaid, Weihao Qu. (2025). Security Education in Higher Education through AI-Powered Gamification. Journal of Cybersecurity, Digital Forensics and Jurisprudence. https://doi.org/10.65879/3070-5789.2025.01.07
Page metadata
| Field | Value |
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type |
product |
id |
sentinel-ai-powered-security-game-platform |
title |
Sentinel AI-powered security game platform |
description |
Sentinel is a mobile game platform developed by Bingjun Li et al. |
status |
review |
product_kind |
software |
generated |
by process:settle-candidates on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
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