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Practical Data Access Minimization in Trigger-Action Platforms.

, , , , and . USENIX Security Symposium, page 2929-2945. USENIX Association, (2022)

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Analyzing the Interpretability Robustness of Self-Explaining Models., , and . CoRR, (2019)Data Privacy in Trigger-Action IoT Systems., , , , , and . CoRR, (2020)GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems., , , , , and . EuroS&P, page 664-683. IEEE, (2022)CPSIoTSec'23: Fifth Workshop on CPS & IoT Security and Privacy., and . CCS, page 3648-3650. ACM, (2023)Computer Security and Privacy for the Physical World.. IoT S&P@CCS, page 55. ACM, (2017)Applying the Opacified Computation Model to Enforce Information Flow Policies in IoT Applications., , and . SecDev, page 88-93. IEEE Computer Society, (2016)Analyzing the Security of the Business Collaboration Platform App Model., , , , , and . CoRR, (2022)Anception: Application Virtualization For Android., , , and . CoRR, (2014)Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect., , , , and . CVPR, page 14666-14675. Computer Vision Foundation / IEEE, (2021)ContexloT: Towards Providing Contextual Integrity to Appified IoT Platforms., , , , , , and . NDSS, The Internet Society, (2017)