Eric Pauley and Patrick McDaniel (University of Wisconsin–Madison)

Measurement of network data received from or transmitted over the public Internet has yielded a myriad of insights towards improving the security and privacy of deployed services. Yet, the collection and analysis of this data necessarily involves the processing of data that could impact human subjects, and anonymization often destroys the very phenomena under study. As a result, Internet measurement faces the unique challenge of studying data from human subjects who could not conceivably consent to its collection, and yet the measurement community has tacitly concluded that such measurement is beneficial and even necessary for its positive impacts. We are thus at an impasse: academics and practitioners routinely collect and analyze sensitive user data, and yet there exists no cohesive set of ethical norms for the community that justifies these studies. In this work, we examine the ethical considerations of Internet traffic measurement and analysis, analyzing the ethical considerations and remediations in prior works and general trends in the community. We further analyze ethical expectations in calls-for-papers, finding a general lack of cohesion across venues. Through our analysis and recommendations, we hope to inform future studies and venue expectations towards maintaining positive impact while respecting and protecting end users.

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Sian Kim (Ewha Womans University), Changhun Jung (Ewha Womans University), RhongHo Jang (Wayne State University), David Mohaisen (University of Central Florida), DaeHun Nyang (Ewha Womans University)

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REaaS: Enabling Adversarially Robust Downstream Classifiers via Robust Encoder...

Wenjie Qu (Huazhong University of Science and Technology), Jinyuan Jia (University of Illinois Urbana-Champaign), Neil Zhenqiang Gong (Duke University)

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Kostas Drakonakis (FORTH), Sotiris Ioannidis (Technical University of Crete), Jason Polakis (University of Illinois at Chicago)

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Jelena Mirkovic (USC Information Sciences Institute)

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