FairPlay：Google Play中的欺诈和恶意软件检测
FairPlay: Fraud and Malware Detection in Google Play
摘要：
Google Android应用市场中的欺诈行为助长了搜索排名滥用和恶意软件扩散。我们介绍了FairPlay，这是一个新颖的系统，通过挑选欺诈者留下的痕迹来发现恶意软件和搜索排名欺诈应用程序。为了识别可疑应用，FairPlay PCF算法将评论活动关联起来，并将检测到的评论关系与从纵向Google Play应用数据中收集的语言和行为信号进行独特的组合。我们向社区贡献了一个新的纵向应用数据集，其中包括超过87K的应用程序，290万评论和240万评论者，收集了超过半年的时间。FairPlay在对恶意软件、欺诈和合法应用程序的黄金标准数据集进行分类方面达到了95%以上的准确率。我们发现，75%已识别的恶意软件应用程序参与搜索排名欺诈。FairPlay发现了数百个目前逃避Google Bouncer检测技术的欺诈应用程序，并揭示了一种新型的攻击活动，用户被骚扰撰写积极的评论，并安装和审查其他应用程序。
英文摘要：
Fraudulent behaviors in Google Android app market fuel search rank abuse and malware proliferation. We present FairPlay, a novel system that uncovers both malware and search rank fraud apps, by picking out trails that fraudsters leave behind. To identify suspicious apps, FairPlay PCF algorithm correlates review activities and uniquely combines detected review relations with linguistic and behavioral signals gleaned from longitudinal Google Play app data. We contribute a new longitudinal app dataset to the community, which consists of over 87K apps, 2.9M reviews, and 2.4M reviewers, collected over half a year. FairPlay achieves over 95% accuracy in classifying gold standard datasets of malware, fraudulent and legitimate apps. We show that 75% of the identified malware apps engage in search rank fraud. FairPlay discovers hundreds of fraudulent apps that currently evade Google Bouncer detection technology, and reveals a new type of attack campaign, where users are harassed into writing positive reviews, and install and review other apps.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
