Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware
By Davide Maiorca, Battista Biggio. 2017
41 citations recorded by the source corpus.
As it continues to proliferate, malware has shown increasing sophistication, and PDF malware is a major threat on the cybersecurity landscape. We provide an overview of current attack techniques used to convey PDF malware and the analysis tools that support digital forensic investigations.
Subfields: Artificial Intelligence, Information Systems, Signal Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Giorgio Giacinto
- Battista Biggio
- Davide Maiorca
- Maria Elena Chiappe
- Fabio Roli
- Nicholas Carlini
- Nicolas Papernot
- Giorgio Fumera
In Information Systems
- Battista Biggio
- Giorgio Giacinto
- Davide Maiorca
- Fabio Roli
- Maria Elena Chiappe
- Giorgio Fumera
- Joseph Gardiner
- Shishir Nagaraja
In Signal Processing
- Battista Biggio
- Giorgio Giacinto
- Davide Maiorca
- Fabio Roli
- Maria Elena Chiappe
- Giorgio Fumera
- Nicholas Carlini
- Ambra Demontis
Citations in the corpus
- Adversarial Detection of Flash Malware: Limitations and Open Issues (2017, background): “Popular case-studies in which these techniques have been systematically studied are the detection of malicious PDF files [3, 19, 20, 8] and the detection of Android malware [21, 22, 23].”
- Towards Adversarial Malware Detection (2018, methodology): “ the PDF malware sample. In both cases, three major strategies were used to inject material while minimizing the risk of compromising the intrusive functionality of PDF malware, as depicted in Figure5[62]. We now provide a comprehensive description of each technique, by also referring to the works w”