Title:  A Pattern Recognition System for Malicious PDF Files Detection
Internal authors: 
Issue Date:  2012
Authors:  Maiorca D; Giacinto G; Corona I
Book title:  Machine Learning and Data Mining in Pattern Recognition
ISBN:  978-3-642-31536-7
Publisher name:  Springer-Verlag
Book editors:  Perner P.
Conference section:  contributo
Volume:  7376
First page:  510
Last page:  524
Number of pages:  15
Digital Object Identifier (DOI):  http://dx.doi.org/10.1007/978-3-642-31537-4_40
Scopus identifier:  2-s2.0-84864937789
URL:  http://dx.doi.org/10.1007/978-3-642-31537-4_40
Peer review:  Esperti anonimi
Conference name:  8th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2012
Conference date:  13-20 July 2012
Conference place:  Berlin, Germany
Abstract:  Malicious PDF files have been used to harm computer security during the past two-three years, and modern antivirus are proving to be not completely effective against this kind of threat. In this paper an innovative technique, which combines a feature extractor module strongly related to the structure of PDF files and an effective classifier, is presented. This system has proven to be more effective than other state-of-the-art research tools for malicious PDF detection, as well as than most of antivirus in commerce. Moreover, its flexibility allows adopting it either as a stand-alone tool or as plug-in to improve the performance of an already installed antivirus.
Type: 4.1 Contributo in Atti di convegno

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