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Published in:
2011 | OriginalPaper | Chapter
Online Social Honeynets: Trapping Web Crawlers in OSN
Authors : Jordi Herrera-Joancomartí, Cristina Pérez-Solà
Published in: Modeling Decision for Artificial Intelligence
Publisher: Springer Berlin Heidelberg
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Web crawlers are complex applications that explore the Web with different purposes. Web crawlers can be configured to crawl online social networks (OSN) to obtain relevant data about its global structure. Before a web crawler can be launched to explore the web, a large amount of settings have to be configured. This settings define the behavior of the crawler and have a big impact on the collected data. The amount of collected data and the quality of the information that it contains are affected by the crawler settings and, therefore, by properly configuring this web crawler settings we can target specific goals to achieve with our crawl. In this paper, we analyze how different scheduler algorithms affect to the collected data in terms of users’ privacy. Furthermore, we introduce the concept of online social honeynet (OShN) to protect OSN from web crawlers and we provide an OShN proof-of-concept that achieve good results for protecting OSN from a specific web crawler.