Date: Thursday, 22nd October 2020
Location: TEAMS - code to join the team: n25vdtt
Speakers: Davide Caputo & Marco Zuppelli
Time: 2:30 PM
Title Davide: Mobile Security Meets Data Anonymization: MobHide
Abstract Davide:
Developers of mobile apps gather a lot of user's personal information at runtime by exploiting third-party analytics libraries, without keeping the owner (i.e., the user) of such information in the loop. We argue that this is somehow paradoxical. To overcome this limitation, in this seminar, we discuss a methodology (i.e., MobHide) and its Android implementation (i.e., HideDroid), allowing the user to choose a different privacy level for each app installed on his device.
Bio Davide:
Davide Caputo is a second-year Ph.D. student in Computer Science. He obtained both his BSc and MSc in Computer Engineering at the University of Genoa and he is now working under the supervision of Alessio Merlo and Luca Verderame. His research topic focuses on Mobile and IoT Security.
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Title Marco: Detection Techniques for Stegomalware
Abstract Marco:
In the last few years, cyber-attacks are becoming stealthier and their detection increasingly complex. Attackers are currently using steganography and information hiding techniques to cloak their presence within various carriers, such as digital media and network traffic. Since each carrier has its own set of features and characteristics, the typical detection mechanisms are threat-specific, thus lacking of scalability and generality. Therefore, the data collection process is an essential phase to develop more efficient detection frameworks. In this talk, we present the use of the extended Berkeley Packet Filter (eBPF), a promising tool for gathering measurements and data originated by information-hiding-capable malware. Emphasis will be put on how eBPF can represent an initial step towards bringing the detection to an higher level of abstraction.
Bio Marco:
Marco Zuppelli is a first year PhD student at University of Genoa and a research fellow at the Institute for Applied Mathematics and Information Technologies of the National Research Council of Italy. Within the European Project SIMARGL (Secure Intelligent Methods for Advanced RecoGnition of malware and stegomalware), he is investigating detection methods for steganographic malware and developing new countermeasures against information-hiding-capable threats (including network IPv6-based covert channels and the use of in-kernel measurements to detect malicious activities).