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De-Kodi: Understanding the Kodi Ecosystem

Published: 20 April 2020 Publication History

Abstract

Free and open source media centers are currently experiencing a boom in popularity for the convenience and flexibility they offer users seeking to remotely consume digital content. This newfound fame is matched by increasing notoriety—for their potential to serve as hubs for illegal content—and a presumably ever-increasing network footprint. It is fair to say that a complex ecosystem has developed around Kodi, composed of millions of users, thousands of “add-ons”—Kodi extensions from 3rd-party developers—and content providers. Motivated by these observations, this paper conducts the first analysis of the Kodi ecosystem. Our approach is to build “crawling” software around Kodi which can automatically install an addon, explore its menu, and locate (video) content. This is challenging for many reasons. First, Kodi largely relies on visual information and user input which intrinsically complicates automation. Second, no central aggregators for Kodi addons exist. Third, the potential sheer size of this ecosystem requires a highly scalable crawling solution. We address these challenges with de-Kodi, a full fledged crawling system capable of discovering and crawling large cross-sections of Kodi’s decentralized ecosystem. With de-Kodi, we discovered and tested over 9,000 distinct Kodi addons. Our results demonstrate de-Kodi, which we make available to the general public, to be an essential asset in studying one of the largest multimedia platforms in the world. Our work further serves as the first ever transparent and repeatable analysis of the Kodi ecosystem at large.

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Cited By

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  • (2025)Unmasking hidden threats: Enhanced detection of embedded malicious domains in pirate streaming videosComputers and Electrical Engineering10.1016/j.compeleceng.2025.110087123(110087)Online publication date: Apr-2025
  • (2023)Investigating IPTV Malware in the WildFuture Internet10.3390/fi1510032515:10(325)Online publication date: 28-Sep-2023
  • (2022)Jujuby: Design and Deployment of a Crawler for Twitch CDN MappingProceedings of the 17th Asian Internet Engineering Conference10.1145/3570748.3570755(44-52)Online publication date: 19-Dec-2022

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            cover image ACM Conferences
            WWW '20: Proceedings of The Web Conference 2020
            April 2020
            3143 pages
            ISBN:9781450370233
            DOI:10.1145/3366423
            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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            Publication History

            Published: 20 April 2020

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            WWW '20
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            WWW '20: The Web Conference 2020
            April 20 - 24, 2020
            Taipei, Taiwan

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            Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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            Cited By

            View all
            • (2025)Unmasking hidden threats: Enhanced detection of embedded malicious domains in pirate streaming videosComputers and Electrical Engineering10.1016/j.compeleceng.2025.110087123(110087)Online publication date: Apr-2025
            • (2023)Investigating IPTV Malware in the WildFuture Internet10.3390/fi1510032515:10(325)Online publication date: 28-Sep-2023
            • (2022)Jujuby: Design and Deployment of a Crawler for Twitch CDN MappingProceedings of the 17th Asian Internet Engineering Conference10.1145/3570748.3570755(44-52)Online publication date: 19-Dec-2022

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