* update 2024-10-12 06:19:44

yuriufo · Oct 11, 2024 · dae492d · dae492d
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diff --git a/arXiv_db/Malware/2024.md b/arXiv_db/Malware/2024.md
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 </details>
 
+<details>
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+<summary>2024-10-10 03:39:13 - Careful About What App Promotion Ads Recommend! Detecting and Explaining Malware Promotion via App Promotion Graph</summary>
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+- *Shang Ma, Chaoran Chen, Shao Yang, Shifu Hou, Toby Jia-Jun Li, Xusheng Xiao, Tao Xie, Yanfang Ye*
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+- `2410.07588v1` - [abs](http://arxiv.org/abs/2410.07588v1) - [pdf](http://arxiv.org/pdf/2410.07588v1)
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+> In Android apps, their developers frequently place app promotion ads, namely advertisements to promote other apps. Unfortunately, the inadequate vetting of ad content allows malicious developers to exploit app promotion ads as a new distribution channel for malware. To help detect malware distributed via app promotion ads, in this paper, we propose a novel approach, named ADGPE, that synergistically integrates app user interface (UI) exploration with graph learning to automatically collect app promotion ads, detect malware promoted by these ads, and explain the promotion mechanisms employed by the detected malware. Our evaluation on 18, 627 app promotion ads demonstrates the substantial risks in the app promotion ecosystem.
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+</details>
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