MANA: Towards Efficient Mobile Ad Detection via Multimodal Agentic UI Navigation
Mobile advertising dominates app monetization but introduces risks ranging from intrusive user experience to malware delivery. Existing detection methods rely either on static analysis, which misses runtime behaviors, or on heuristic UI exploration, which struggles with sparse and obfuscated ads. In this paper, we present MANA, the first agentic multimodal reasoning framework for mobile ad detection. MANA integrates static, visual, temporal, and experiential signals into a reasoning-guided navigation strategy that determines not only how to traverse interfaces but also where to focus, enabling efficient and robust exploration. We implement and evaluate MANA on commercial smartphones over ...
| Authors | Yizhe Zhao, Yongjian Fu, Zihao Feng et al. |
|---|---|
| Primary category | cs.CR |
| Published | 20 March 2026 |
| Last updated at source | 20 March 2026 |
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