A Pattern Recognition System for Malicious PDF Files Detection

MAIORCA, DAVIDE;GIACINTO, GIORGIO;CORONA, IGINO
2012

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.
Machine Learning and Data Mining in Pattern Recognition
978-3-642-31536-7
Springer-Verlag
BERLIN HEIDELBERG
Perner P.
7376
510
524
15
http://dx.doi.org/10.1007/978-3-642-31537-4_40
8th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2012
contributo
Esperti anonimi
13-20 July 2012
Berlin, Germany
internazionale
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Maiorca, Davide; Giacinto, Giorgio; Corona, Igino
273
3
4.1 Contributo in Atti di convegno
none
info:eu-repo/semantics/conferenceObject
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