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The U.S. National Science Foundation (NSF) celebrated the 20th anniversary of its research funding programs in cybersecurity, and more generally, secure and trustworthy computing, with a panel session at its conference held in June, 2022. The panel members, distinguished researchers in different research areas of trustworthy computing, were asked to comment on what has been learned, what perhaps should be “unlearned,” what still needs to be learned, and the status of education and training in their respective areas of expertise. Laurie Williams covered enterprise security and measuring security, Gene Tsudik commented on cryptographic security, Trent Jaeger addressed computing infrastructure security, Tadayoshi Kohno reviewed security in cyberphysical systems, and Apu Kapadia provided insights on human-centered security. Michael K. Reiter chaired the panel and moderated questions from the audience. This report provides a brief summary of NSF's research programs in the area and an edited transcript of the panel discussion. 

Deceptive design patterns (sometimes called “dark patterns”) are user interface design elements that may trick, deceive, or mislead users into behaviors that often benefit the party implementing the design over the end user. Prior work has taxonomized, investigated, and measured the prevalence of such patterns primarily in visual user interfaces (e.g., on websites). However, as the ubiquity of voice assistants and other voice-assisted technologies increases, we must anticipate how deceptive designs will be (and indeed, are already) deployed in voice interactions. This paper makes two contributions towards characterizing and surfacing deceptive design patterns in voice interfaces. First, we make a conceptual contribution, identifying key characteristics of voice interfaces that may enable deceptive design patterns, and surfacing existing and theoretical examples of such patterns. Second, we present the findings from a scenario-based user survey with 93 participants, in which we investigate participants’ perceptions of voice interfaces that we consider to be both deceptive and non-deceptive.