P
Pablo García Bringas
Researcher at University of Deusto
Publications - 150
Citations - 3180
Pablo García Bringas is an academic researcher from University of Deusto. The author has contributed to research in topics: Malware & The Internet. The author has an hindex of 25, co-authored 145 publications receiving 2807 citations. Previous affiliations of Pablo García Bringas include Deenbandhu Chhotu Ram University of Science and Technology.
Papers
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Journal ArticleDOI
Opcode sequences as representation of executables for data-mining-based unknown malware detection
TL;DR: This paper proposes a new method to detect unknown malware families based on the frequency of the appearance of opcode sequences, and describes a technique to mine the relevance of each opcode and assess the Frequency of Each opcode sequence.
Book ChapterDOI
PUMA: Permission Usage to Detect Malware in Android
Borja Sanz,Igor Santos,Carlos Laorden,Xabier Ugarte-Pedrero,Pablo García Bringas,Gonzalo Alvarez +5 more
TL;DR: PUMA, a new method for detecting malicious Android applications through machine-learning techniques by analysing the extracted permissions from the application itself, is presented.
Book ChapterDOI
Idea: opcode-sequence-based malware detection
Igor Santos,Felix Brezo,Javier Nieves,Yoseba K. Penya,Borja Sanz,Carlos Laorden,Pablo García Bringas +6 more
TL;DR: It is shown that this method provides an effective way to detect variants of known malware families, based on the frequency of appearance of opcode sequences, which is described a method to mine the relevance of each opcode and weigh each opcodes sequence frequency.
Proceedings ArticleDOI
N-grams-based file signatures for malware detection
TL;DR: It is shown that n-grams signatures provide an effective way to detect unknown malware while keeping low false positive ratio.
Proceedings Article
Supervised Machine Learning for the Detection of Troll Profiles in Twitter Social Network: Application to a Real Case of Cyberbullying.
Patxi Galán-García,José Gaviria de la Puerta,Carlos Laorden Gómez,Igor Santos,Pablo García Bringas +4 more
TL;DR: A methodology to detect and associate fake profiles on Twitter social network which are employed for defamatory activities to a real profile within the same network by analysing the content of comments generated by both profiles is presented.