Decoding the Kodi Ecosystem

IF 2.6 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yunming Xiao, Matteo Varvello, Marc Warrior, Aleksandar Kuzmanovic
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引用次数: 0

Abstract

Free and open-source media centers are experiencing a boom in popularity for the convenience they offer users seeking to remotely consume digital content. Kodi is today’s most popular home media center, with millions of users worldwide. Kodi’s popularity derives from its ability to centralize the sheer amount of media content available on the Web, both free and copyrighted. Researchers have been hinting at potential security concerns around Kodi, due to add-ons injecting unwanted content as well as user settings linked with security holes. Motivated by these observations, this article conducts the first comprehensive analysis of the Kodi ecosystem: 15,000 Kodi users from 104 countries, 11,000 unique add-ons, and data collected over 9 months.

Our work makes three important contributions. Our first contribution is that we build “crawling” software (de-Kodi) which can automatically install a Kodi add-on, explore its menu, and locate (video) content. This is challenging for two main reasons. First, Kodi largely relies on visual information and user input which intrinsically complicates automation. Second, the potential sheer size of this ecosystem (i.e., the number of available add-ons) requires a highly scalable crawling solution. Our second contribution is that we develop a solution to discover Kodi add-ons. Our solution combines Web crawling of popular websites where Kodi add-ons are published (LazyKodi and GitHub) and SafeKodi, a Kodi add-on we have developed which leverages the help of Kodi users to learn which add-ons are used in the wild and, in return, offers information about how safe these add-ons are, e.g., do they track user activity or contact sketchy URLs/IP addresses. Our third contribution is a classifier to passively detect Kodi traffic and add-on usage in the wild.

Our analysis of the Kodi ecosystem reveals the following findings. We find that most installed add-ons are unofficial but safe to use. Still, 78% of the users have installed at least one unsafe add-on, and even worse, such add-ons are among the most popular. In response to the information offered by SafeKodi, one-third of the users reacted by disabling some of their add-ons. However, the majority of users ignored our warnings for several months attracted by the content such unsafe add-ons have to offer. Last but not least, we show that Kodi’s auto-update, a feature active for 97.6% of SafeKodi users, makes Kodi users easily identifiable by their ISPs. While passively identifying which Kodi add-on is in use is, as expected, much harder, we also find that many unofficial add-ons do not use HTTPS yet, making their passive detection straightforward.1

解码Kodi生态系统
免费和开源媒体中心正因其为寻求远程消费数字内容的用户提供便利而受到广泛欢迎。Kodi是当今最受欢迎的家庭媒体中心,在全球拥有数百万用户。Kodi的受欢迎程度源于它能够集中网络上可用的大量媒体内容,无论是免费的还是受版权保护的。研究人员一直在暗示,由于附加组件注入不需要的内容以及与安全漏洞相关的用户设置,Kodi存在潜在的安全问题。受这些观察的启发,本文对Kodi生态系统进行了首次全面分析:来自104个国家的15,000名Kodi用户,11,000个独特的附加组件,以及9个多月收集的数据。我们的工作有三个重要贡献。我们的第一个贡献是我们建立了“爬行”软件(去Kodi),它可以自动安装一个Kodi附加组件,探索它的菜单,并定位(视频)内容。这是一个挑战,主要有两个原因。首先,Kodi很大程度上依赖于视觉信息和用户输入,这本质上使自动化变得复杂。其次,这个生态系统的潜在规模(即可用附加组件的数量)需要一个高度可扩展的爬行解决方案。我们的第二个贡献是,我们开发了一个解决方案来发现Kodi附加组件。我们的解决方案结合了流行网站的网络爬行Kodi插件发布(LazyKodi和GitHub)和SafeKodi,一个Kodi插件,我们已经开发了它利用Kodi用户的帮助来学习哪些插件在野外使用,并作为回报,提供有关这些插件的安全性的信息,例如,他们是否跟踪用户活动或联系粗略的url /IP地址。我们的第三个贡献是一个分类器,用于被动地检测Kodi流量和附加组件的使用情况。我们对Kodi生态系统的分析揭示了以下发现。我们发现大多数安装的插件都是非官方的,但可以安全使用。尽管如此,78%的用户至少安装了一个不安全的附加组件,更糟糕的是,这些附加组件是最受欢迎的。作为对SafeKodi提供的信息的回应,三分之一的用户关闭了他们的一些插件。然而,大多数用户忽视了我们的警告几个月来吸引的内容,这些不安全的附加组件必须提供。最后但并非最不重要的是,我们显示Kodi的自动更新,97.6%的SafeKodi用户活跃的功能,使Kodi用户很容易被他们的互联网服务提供商识别。虽然被动识别哪个Kodi插件正在使用,正如预期的那样,困难得多,我们还发现许多非官方的插件还不使用HTTPS,使他们的被动检测变得直接
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Transactions on the Web
ACM Transactions on the Web 工程技术-计算机:软件工程
CiteScore
4.90
自引率
0.00%
发文量
26
审稿时长
7.5 months
期刊介绍: Transactions on the Web (TWEB) is a journal publishing refereed articles reporting the results of research on Web content, applications, use, and related enabling technologies. Topics in the scope of TWEB include but are not limited to the following: Browsers and Web Interfaces; Electronic Commerce; Electronic Publishing; Hypertext and Hypermedia; Semantic Web; Web Engineering; Web Services; and Service-Oriented Computing XML. In addition, papers addressing the intersection of the following broader technologies with the Web are also in scope: Accessibility; Business Services Education; Knowledge Management and Representation; Mobility and pervasive computing; Performance and scalability; Recommender systems; Searching, Indexing, Classification, Retrieval and Querying, Data Mining and Analysis; Security and Privacy; and User Interfaces. Papers discussing specific Web technologies, applications, content generation and management and use are within scope. Also, papers describing novel applications of the web as well as papers on the underlying technologies are welcome.
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