Guillermo Suarez-Tangil
King's College London
58 Papers
202 Citations
Guillermo Suarez-Tangil is an academic researcher from King's College London. The author has contributed to research in topics: Computer science & Malware. The author has an hindex of 20, co-authored 50 publications. Previous affiliations of Guillermo Suarez-Tangil include Royal Holloway, University of London & Carlos III Health Institute.
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Papers
AndrEnsemble: Leveraging API Ensembles to Characterize Android Malware Families
Omid Mirzaei,Guillermo Suarez-Tangil,José María de Fuentes,Juan E. Tapiador,Gianluca Stringhini +4 more
- 02 Jul 2019
TL;DR: AndrEnsemble is presented, a characterization system for Android malware families based on ensembles of sensitive API calls extracted from aggregated call graphs of different families, which has several advantages over similar characterization approaches, including a greater reduction ratio with respect to original call graphs, robustness against transformation attacks, and flexibility to be applied at different granularity levels.
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Providing SIEM systems with self-adaptation
TL;DR: This article provides SIEM correlation with self-adaptation capabilities to optimize and significantly reduce the intervention of operators and automatically learns and produces correlation rules based on the context for different types of multi-step attacks using genetic programming.
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Characterizing Linux-based malware: Findings and recent trends
TL;DR: In this article, the authors present a comprehensive characterization of Linux-based malware and combine their features with a custom distance function to discover new threats by clustering together similar samples, and further study each of the unknown threats by using state-of-the-art reverse engineering and forensic techniques and expertise as malware analysts.
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Security analysis and exploitation of arduino devices in the internet of things
Carlos Alberca,Sergio Pastrana,Guillermo Suarez-Tangil,Paolo Palmieri +3 more
- 16 May 2016
TL;DR: It is shown that Arduino Yun is vulnerable to a number of attacks and a proof of concept capable of exploiting some of them is implemented and implemented.
•Posted Content
"You Know What to Do": Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks
Enrico Mariconti,Guillermo Suarez-Tangil,Jeremy Blackburn,Emiliano De Cristofaro,Nicolas Kourtellis,Ilias Leontiadis,Jordi Luque Serrano,Gianluca Stringhini +7 more
TL;DR: In this article, an automated solution was proposed to identify YouTube videos that are likely to be targeted by coordinated harassers from fringe communities like 4chan, based on a ground truth dataset of videos that were targeted by raids.
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