Carlotta Tagliaro (TU Wien)

Smart TVs enable the integration of the traditional broadcast signal with services offered by the Internet. Specifically, the Hybrid Broadcast Broadband TV (HbbTV) protocol allows broadcasters to offer consumers additional features via the Internet (e.g., quizzes and the ability to restart programs), enriching their viewing experience. HbbTV works using standard web technologies as transparent overlays over a TV channel. Despite the increasing adoption of HbbTV worldwide, studies on its privacy are scarce.

In this study, we show how we tested a range of 36 channels across five European countries and what challenges we faced; specifically, every country adopts different ways of delivering the broadcast signal to the TVs. Thus, we identified a common experimental setup and instructions adopted in each country to assess the channels' privacy level. We also show how the extracted URLs pointing to the HbbTV application can foster further replicability and studies. Finally, we delve into how we measured users' awareness of HbbTV security and privacy risks and how we avoided bias in our results.

Speaker's Biography

Carlotta Tagliaro is a second year PhD student at TU Wien (Vienna, Austria). She has a great interest in Internet of Things security, especially in what concerns application-layer messaging protocols adopted by everyday users. She obtained her double master's degree in cyber security from the University of Trento (Italy) and the University of Twente (the Netherlands). She has worked as a junior researcher at the Fondazione Bruno Kessler - FBK in Trento, Italy on the security of the MQTT protocol.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 42 [1] => 66 ) ) ) [post__not_in] => Array ( [0] => 12763 ) )

MyTEE: Own the Trusted Execution Environment on Embedded Devices

Seungkyun Han (Chungnam National University), Jinsoo Jang (Chungnam National University)

Read More

Analysing Adversarial Threats to Rule-Based Local-Planning Algorithms for Autonomous...

Andrew Roberts (Tallinn University of Technology), Mohsen Malayjerdi (Tallinn University of Technology), Mauro Bellone (Tallinn University of Technology), Olaf Maennel (The University of Adelaide), Ehsan Malayjerdi (Tallinn University of Technology)

Read More

BARS: Local Robustness Certification for Deep Learning based Traffic...

Kai Wang (Tsinghua University), Zhiliang Wang (Tsinghua University), Dongqi Han (Tsinghua University), Wenqi Chen (Tsinghua University), Jiahai Yang (Tsinghua University), Xingang Shi (Tsinghua University), Xia Yin (Tsinghua University)

Read More

Taking a Closer Look at the Alexa Skill Ecosystem

Christopher Lentzsch (Ruhr-Universität Bochum), Anupam Das (North Carolina State University)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)