Brand reputation is an open issue for several companies delivering services through dedicated apps. The latter are often targeted by malicious developers who spread unauthorized (fake, malicious, obsolete or deprecated) versions through alternative distribution channels and app stores. The aim of the work is the early detection of these alternative markets advertised through social media such as Twitter of Facebook or hosted in the Dark Web. Specifically, we propose a semi-automatic approach to monitor these media and to recommend web pages that are likely to represent alternative marketplaces. The underlying predictive platform allows to analyze web pages extracted from the Web and exploits an ensemble classification model to distinguish between real app stores and similar pages (i.e. blogs, forums, etc.) which can be erroneously returned by a common search engine. An experimental evaluation on a real dataset confirms the validity of the approach in terms of accuracy.
Discovering of Alternative Marketplaces on the Web for Mobile App Security Monitoring
Massimo Guarascio;Ettore Ritacco;Francesco Sergio Pisani;
2017
Abstract
Brand reputation is an open issue for several companies delivering services through dedicated apps. The latter are often targeted by malicious developers who spread unauthorized (fake, malicious, obsolete or deprecated) versions through alternative distribution channels and app stores. The aim of the work is the early detection of these alternative markets advertised through social media such as Twitter of Facebook or hosted in the Dark Web. Specifically, we propose a semi-automatic approach to monitor these media and to recommend web pages that are likely to represent alternative marketplaces. The underlying predictive platform allows to analyze web pages extracted from the Web and exploits an ensemble classification model to distinguish between real app stores and similar pages (i.e. blogs, forums, etc.) which can be erroneously returned by a common search engine. An experimental evaluation on a real dataset confirms the validity of the approach in terms of accuracy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.