Fábio Fernando de Oliveira Silva, Graduate Research Assistant
Distributed Systems Laboratory (LSD)
Federal University of Campina Grande (UFCG)
Rua Aprígio Veloso, 882, Bloco CO, Bodocongó
58.429-900, Campina Grande, PB, Brazil

Contact info:
E-mail: fabiosilva@lsd.ufcg.edu.br
Phone: +55 83 2101 1638
Mobile: +55 83 98858 2685
Skype: ffosilva

Publications:

Secure and Privacy-Aware Data Dissemination for Cloud-Based Applications (pdf)
UCC '17 Proceedings of the 10th International Conference on Utility and Cloud Computing
Authors: Lilia Sampaio, Fábio Silva, Amanda Souza, Andrey Brito, Pascal Felber
Abstract: In this paper we propose a data dissemination platform that supports data security and different privacy levels even when the platform and the data are hosted by untrusted infrastructures. The proposed system aims at enabling an application ecosystem that uses off-the-shelf trusted platforms (in this case, Intel SGX), so that users may allow or disallow third parties to access the live data stream with a specific sensitivity-level. Moreover, this approach does not require users to manage the encryption keys directly. Our experiments show that such an approach is indeed practical for medium scale systems, where participants disseminate small volumes of data at a time, such as in smart grids and IoT environments.

PubSub-SGX: Exploiting Trusted Execution Environments for Privacy-Preserving Publish/Subscribe Systems (pdf)
SRDS '18 Proceedings of The 37th Symposium on Reliable Distributed Systems
Authors: Sergei Arnautov, Andrey Brito, Pascal Felber, Christof Fetzer, Franz Gregor, Robert Krahn, Wojciech Ozga, André Martin, Valerio Schiavoni, Fábio Silva, Marcus Tenorio, Nikolaus Thümmel
Abstract: This paper presents PubSubSGX, a content-based publish-subscribe system that exploits trusted execution environments (TEEs), such as Intel SGX, to guarantee confidentiality and integrity of data as well as anonymity and privacy of publishers and subscribers. We describe the technical details of our Python implementation, as well as the required system support introduced to deploy our system in a container-based runtime. Our evaluation results show that our approach is sound, while at the same time highlighting the performance and scalability trade-offs. In particular, by supporting just-in-time compilation inside of TEEs, Python programs inside of TEEs are in general faster than when executed natively using standard CPython.

Education:

Federal University of Campina Grande (UFCG)
Bachelor's degree in Computer Science
Dates attended: 2012 - 2017
Brazilian Grade: 8.18 / 10.00
Cumulative GPA: 3.42 / 4.00 (converter tool)

Faculdade Técnica Infogenius
Technical Degree in Information Technology
Dates attended: 2010 - 2012