Christoph Kerschbaumer (Mozilla Corporation), Frederik Braun (Mozilla Corporation), Simon Friedberger (Mozilla Corporation), Malte Jürgens (Mozilla Corporation)

The web was originally developed in an attempt to allow scientists from around the world to share information efficiently. As the web evolved, the threat model for the web evolved as well. While it was probably acceptable for research to be freely shared with the world, current use cases like online shopping, media consumption or private messaging require stronger security safeguards which ensure that network attackers are not able to view, steal, or even tamper with the transmitted data. Unfortunately the Hypertext Transfer Protocol (http) does not provide any of these required security guarantees.

The Hypertext Transfer Protocol Secure (https) on the other hand allows carrying http over the Transport Layer Security (TLS) protocol and in turn fixes these security shortcomings of http by creating a secure and encrypted connection between the browser and the website. While the majority of websites support https nowadays, https remains an opt-in mechanism that not everyone perceives as necessary or affordable.

In this paper we evaluate the state of https adoption on the web. We survey different mechanisms which allow upgrading connections from http to https, and provide real world browsing data from over 140 million Firefox release users. We provide numbers showcasing https adoption in different geographical regions as well as on different operating systems and highlight the effectiveness of the different upgrading mechanisms. In the end, we can use this analysis to make actionable suggestions to further improve https adoption on the web.

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Crosstalk-induced Side Channel Threats in Multi-Tenant NISQ Computers

Ruixuan Li (Choudhury), Chaithanya Naik Mude (University of Wisconsin-Madison), Sanjay Das (The University of Texas at Dallas), Preetham Chandra Tikkireddi (University of Wisconsin-Madison), Swamit Tannu (University of Wisconsin, Madison), Kanad Basu (University of Texas at Dallas)

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Jingwen Yan (Clemson University), Song Liao (Texas Tech University), Mohammed Aldeen (Clemson University), Luyi Xing (Indiana University Bloomington), Danfeng (Daphne) Yao (Virginia Tech), Long Cheng (Clemson University)

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Passive Inference Attacks on Split Learning via Adversarial Regularization

Xiaochen Zhu (National University of Singapore & Massachusetts Institute of Technology), Xinjian Luo (National University of Singapore & Mohamed bin Zayed University of Artificial Intelligence), Yuncheng Wu (Renmin University of China), Yangfan Jiang (National University of Singapore), Xiaokui Xiao (National University of Singapore), Beng Chin Ooi (National University of Singapore)

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AegisSat: A Satellite Cybersecurity Testbed

Roee Idan, Roy Peled, Aviel Ben Siman Tov, Eli Markus, Boris Zadov, Ofir Chodeda, Yohai Fadida (Ben Gurion University of the Negev), Oliver Holschke, Jan Plachy (T-Labs (Research & Innovation)), Yuval Elovici, Asaf Shabtai (Ben Gurion University of the Negev)

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