M.Sc. Tommaso Frassetto

Research Assistant

Mornewegstraße 30
D-64293 Darmstadt
GERMANY

Building:S4|14
Room:4.1.21
Phone:+49 (0)6151 16 - 25340
Email:tommaso.frassetto(a-t)trust.tu-darmstadt.de (PGP key)
Website:https://www.trust.informatik.tu-darmstadt.de/tf

 

Vita

Since 2016

Research Assistant

at CYSEC and Technische Universität Darmstadt, Germany 

2013-2016

M.Sc. Computer Science

at University of Padua, Italy

2010-2013

B.Sc. Computer Science

at University of Padua, Italy

Awards

  • Best Poster Award, ICDCS 2017

    Markus Miettinen, Samuel Marchal, Ibbad Hafeez, Tommaso Frassetto, N. Asokan, Ahmad-Reza Sadeghi and Sasu Tarkoma, "IoT Sentinel Demo: Automated Device-Type Identification for Security Enforcement in IoT" In: Proc. 37th IEEE International Conference on Distributed Computing Systems (ICDCS 2017), June 5-8, 2017, Atlanta, Georgia, USA.

Publications

Fitness Trackers: Fit for Health but Unfit for Security and Privacy

Author Hossein Fereidooni, Tommaso Frassetto, Markus Miettinen, Ahmad-Reza Sadeghi, Mauro Conti
Date July 2017
Kind Inproceedings
Book titleThe Second IEEE International Workshop on Safe, Energy-Aware, & Reliable Connected Health (CHASE-SEARCH)
LocationPhiladelphia, Pennsylvania, USA
KeyTUD-CS-2017-0188
Research Areas System Security Lab
Abstract Wearable devices for fitness tracking and health monitoring have gained considerable popularity and become one of the fastest growing smart devices market. More and more companies are offering integrated health and activity monitoring solutions for fitness trackers. Recently insurances are offering their customers better conditions for health and condition monitoring. However, the extensive sensitive information collected by tracking products and accessibility by third party service providers poses vital security and privacy challenges on the employed solutions. In this paper, we present our security analysis of a representative sample of current fitness tracking products on the market. In particular, we focus on malicious user setting that aims at injecting false data into the cloud-based services leading to erroneous data analytics. We show that none of these products can provide data integrity, authenticity and confidentiality.
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