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Discovering of Alternative Marketplaces on the Web for Mobile App Security Monitoring

Conference Paper
Publication Date:
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Machine Learning; Cyber Security; Ensemble Leaning; Text Mining
List of contributors:
Pisani, FRANCESCO SERGIO; Ritacco, Ettore; Guarascio, Massimo
Authors of the University:
GUARASCIO MASSIMO
PISANI FRANCESCO SERGIO
RITACCO ETTORE
Handle:
https://iris.cnr.it/handle/20.500.14243/336782
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URL

http://www.di.uniba.it/~loglisci/NFmcp17/NFMCP_2017_paper_14.pdf
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