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

The Vulnerabilities Less Exploited: Cyberattacks on End-of-Life Satellites

Frank Lee and Gregory Falco (Johns Hopkins University) Presenter: Frank Lee

Read More

Do Not Give a Dog Bread Every Time He...

Chongqing Lei (Southeast University), Zhen Ling (Southeast University), Yue Zhang (Jinan University), Kai Dong (Southeast University), Kaizheng Liu (Southeast University), Junzhou Luo (Southeast University), Xinwen Fu (University of Massachusetts Lowell)

Read More

Fusion: Efficient and Secure Inference Resilient to Malicious Servers

Caiqin Dong (Jinan University), Jian Weng (Jinan University), Jia-Nan Liu (Jinan University), Yue Zhang (Jinan University), Yao Tong (Guangzhou Fongwell Data Limited Company), Anjia Yang (Jinan University), Yudan Cheng (Jinan University), Shun Hu (Jinan University)

Read More

Thwarting Smartphone SMS Attacks at the Radio Interface Layer

Haohuang Wen (Ohio State University), Phillip Porras (SRI International), Vinod Yegneswaran (SRI International), Zhiqiang Lin (Ohio State University)

Read More