5 papers
From UI to Code: Mobile Ads Detection via LLM-Unified Static-Dynamic Analysis
Shang Ma, Wei Cheng, Yanfang Ye +1
Mobile advertisements (ads) are essential to the app economy, yet detecting them is challenging because ad content is dynamically fetched from remote servers and rendered through d…
Agent+P: Guiding UI Agents via Symbolic Planning
Shang Ma, Xusheng Xiao, Yanfang Ye
Large Language Model (LLM)-based UI agents show great promise for UI automation but often hallucinate in long-horizon tasks due to their lack of understanding of the global UI tran…
PsyScam: A Benchmark for Psychological Techniques in Real-World Scams
Shang Ma, Tianyi Ma, Jiahao Liu +4
Over the years, online scams have grown dramatically, with nearly 50% of global consumers encountering scam attempts each week. These scams cause not only significant financial los…
The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections
Chaoran Chen, Zhiping Zhang, Bingcan Guo +8
A Large Language Model (LLM) powered GUI agent is a specialized autonomous system that performs tasks on the user's behalf according to high-level instructions. It does so by perce…
Careful About What App Promotion Ads Recommend! Detecting and Explaining Malware Promotion via App Promotion Graph
Shang Ma, Chaoran Chen, Shao Yang +5
In Android apps, their developers frequently place app promotion ads, namely advertisements to promote other apps. Unfortunately, the inadequate vetting of ad content allows malici…