With a society that spends more and more time online, web communities have proliferated to support a wide range of activities. In this talk, I will provide a panoramic of some of the threats that have proliferated recently in certain web ecosystems. I will first talk about cybercrime. Cyber-dependent crimes have rocketed in recent years. Illicit services, knowledge, and tools are a commodity exchanged in anonymous online markets. I will present as an example the case of crypto-mining malware, a criminal operation that has produced over 57M USD of revenues by levering these services. This income fuels the underground economy and gears other cyber-criminal activities. All this poses a threat to our society, costing governments, private companies, and citizens billions per year. I will then discuss the problem of online radicalization. Finally, I will conclude my talk by discussing some of my ongoing work on studying the smart personal ecosystem.
Guillermo Suarez-Tangil is Assistant Professor at IMDEA Networks Institute. His research focuses on systems security and malware analysis and detection. In particular, his area of expertise lies in the study of smart malware, ranging from the detection of advanced obfuscated malware to automated analysis of targeted malware. Guillermo also holds a position at King's College London (KCL) as an Assistant Professor, where he has been part of the Cybersecurity group since 2018. Before joining KCL, he has been a senior research associate at University College London (UCL) where he explored the use of program analysis to study malware. He has also been actively involved in other research directions aiming at detecting and preventing of Mass-Marketing Fraud (MMF) and security and privacy on the social web.
Prior to that, he held a post-doctoral position at Royal Holloway, University of London (RHUL) where he was part of the development team of CopperDroid, a tool to dynamically test malware that uses machine learning to model malicious behaviors. He also holds solid expertise in building novel data learning algorithms for malware analysis. He obtained his PhD in smart malware analysis in UC3M with distinction. He received the FUNCAS Best National Student Academic Award---a highly competitive award given to the best Thesis in the field of Engineering between 2014-2015.