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| Hauptverfasser: | , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| Online-Zugang: | https://arxiv.org/abs/2601.17025 |
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| _version_ | 1866908785131388928 |
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| author | Pervez, Muhammad Muneeb Ullah, Muhammad Qasim Atiq Khan, Ibrahim Ahmed Rahat, Roshnik Zaffar, Muhammad Fareed Tahir, Rashid Rahwan, Talal Zaki, Yasir |
| author_facet | Pervez, Muhammad Muneeb Ullah, Muhammad Qasim Atiq Khan, Ibrahim Ahmed Rahat, Roshnik Zaffar, Muhammad Fareed Tahir, Rashid Rahwan, Talal Zaki, Yasir |
| contents | Among populations with limited literacy in emerging digital markets, the adoption of mobile phones, combined with comprehension barriers and poor cybersecurity hygiene, has created hidden privacy risks. This paper examines how informed consent is often abused by predatory financial applications, leading to financial scams that disproportionately affect users with low literacy. We focus on predatory loan, gambling, and trading apps, analyzing a dataset of 50 Google Play Store apps to measure how many omit or obfuscate critical privacy disclosures. We also evaluate comprehension gaps among users with low literacy via a targeted user study and assess whether Large Language Model (LLM)-generated summaries, translations, and visual cues can improve consent clarity. Our findings show that 85% of study participants did not understand basic app permissions, underscoring the urgent need for stronger regulatory oversight and scalable LLM-driven privacy-literacy tools. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_17025 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | (Mis-)Informed Consent: Predatory Apps and the Exploitation of Populations with Limited Literacy Pervez, Muhammad Muneeb Ullah, Muhammad Qasim Atiq Khan, Ibrahim Ahmed Rahat, Roshnik Zaffar, Muhammad Fareed Tahir, Rashid Rahwan, Talal Zaki, Yasir Computers and Society Among populations with limited literacy in emerging digital markets, the adoption of mobile phones, combined with comprehension barriers and poor cybersecurity hygiene, has created hidden privacy risks. This paper examines how informed consent is often abused by predatory financial applications, leading to financial scams that disproportionately affect users with low literacy. We focus on predatory loan, gambling, and trading apps, analyzing a dataset of 50 Google Play Store apps to measure how many omit or obfuscate critical privacy disclosures. We also evaluate comprehension gaps among users with low literacy via a targeted user study and assess whether Large Language Model (LLM)-generated summaries, translations, and visual cues can improve consent clarity. Our findings show that 85% of study participants did not understand basic app permissions, underscoring the urgent need for stronger regulatory oversight and scalable LLM-driven privacy-literacy tools. |
| title | (Mis-)Informed Consent: Predatory Apps and the Exploitation of Populations with Limited Literacy |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2601.17025 |