An interdisciplinary team of computer scientists, information scientists, and planners explores the invisible environmental impacts of digital technologies in this essay, presenting some ideas on the forces that either de-emphasize or even actively push against considering these impacts. This essay was presented at Fourth Workshop on Computing within Limits (LIMITS 2018).
This paper, presented at the Network and Distributed System Security Symposium (NDSS) 2018, introduces Decentralized Action Integrity, a security principle that prevents an untrusted trigger-action platform from misusing compromised OAuth tokens in ways that are inconsistent with any given user’s set of trigger-action rules.
Computing is transitioning from single-user devices to the Internet of Things, in which multiple users with complex social relationships interact with a single device. In this paper from the 12th USENIX Workshop on Offensive Technologies (WOOT 2018), a team with Lab researchers begin re-envisioning access control and authentication for such settings in the home IoT.
This article in the UCLA Law Review is the first to consider how efforts to regulate bots, while falling short of per se censorship, might nonetheless run afoul of the First Amendment. The article further considers how premature regulation of bot speech may inadvertently curtail a novel and still emerging form of expression.
In this paper, presented at the 2018 Conference on Computer Vision and Pattern Recognition (CVPR 2018), researchers show that malicious alterations to real world objects could cause an object classifier to misread an image.
Presented at the 12th USENIX Workshop on Offensive Technologies (WOOT ’18), this paper explores physical adversarial attacks for object detection models, a broader class of deep learning algorithms widely used to detect and label multiple objects within a scene.
In research published in Transactions of the Association for Computational Linguistics, experts in information science and computational linguistics investigate data statements as a practice to address critical ethical and scientific issues that result when systems developed with data from certain populations are used in systems with other populations.
SeaGlass is a system designed by security researchers at the University of Washington to measure IMSI-catcher use across a city. The project aims to help communities maintain their privacy by building a community-driven, open data service to detect cellphone surveillance and produce high-quality cellular network data for research. This paper was published at Privacy Enhancing Technology Symposium 2017.
This paper evaluates the robustness of DNA processing tools if (or when) adversarial attacks manifest. We demonstrate, for the first time, the synthesis of DNA which — when sequenced and processed— gives an attacker arbitrary remote code execution. Informed by our experiments and results, we develop a broad framework and guidelines to safeguard security and privacy in DNA synthesis, sequencing, and processing. This paper was published at the 2017 USENIX Security Symposium.
In this work, we explore the following question: can third-parties use the purchasing of ads to extract private information about individuals? We find that the answer is yes. We also conduct a broad survey of other ad networks and assess their risks to similar attacks. We then step back and explore the implications of our findings. Published at the 16th ACM Workshop on Privacy in the Electronic Society (WPES 2017).