Masoumeh Shafieinejad (Vector Institute), Xi He (Vector Institute and Univesity of Waterloo), Bailey Kacsmar (Amii & University of Alberta)

Privacy is an instance of a social norm formed through legal, technical, and cultural dimensions. Institutions such as regulators, industry, and researchers act as societal agents that both influence and respond to evolving norms. Attempts to promote privacy must account for this complexity and the dynamic interactions among these actors. Privacy enhancing technologies (PETs) are technical solutions that allow for the development of solutions that benefit society, while ensuring the privacy of the individuals whose data is being used. However, despite increased privacy challenges and a corresponding increase in new regulations across the globe, a low adoption rate of PETs persists. In this work, we investigate the factors influencing industry’s decision-making processes around PETs adoption as well as the extent to which privacy regulations inspire such adoption through a qualitative survey study with 22 industry participants from across Canada Informed by the results of our analysis, we make recommendations for industry, researchers, and policymakers on how to support what each of them seeks from the other when attempting to improve digital privacy protections. By advancing our understanding of what challenges the industry faces, we increase the effectiveness of future privacy research that aims to help overcome these issues.

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UDIM: Formal User-Device Interaction Model for Approximating Artifact Coverage...

Maximilian Eichhorn (Friedrich-Alexander-Universitat Erlangen-Nurnberg), Andreas Hammer (Friedrich-Alexander-Universitat Erlangen-Nurnberg), Gaston Pugliese (Friedrich-Alexander-Universitat Erlangen-Nurnberg), Felix Freiling (Friedrich-Alexander-Universitat Erlangen-Nurnberg)

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Analyzing the Patterns and Behavior of Users When Detecting...

Nick Ceccio, Naman Gupta, Majed Almansoori, Rahul Chatterjee (University of Wisconsin-Madison)

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CoLD: Collaborative Label Denoising Framework for Network Intrusion Detection

Shuo Yang (The University of Hong Kong), Xinran Zheng (University College London), Jinze Li (The University of Hong Kong), Jinfeng Xu (The University of Hong Kong), Edith C. H. Ngai (The University of Hong Kong)

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