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Protecting visual secrets is an important problem due to the prevalence of cameras that continuously monitor our surroundings. Any viable solution to this problem should also minimize the impact on the utility of applications that use images. In this work, we build on the existing work of adversarial learning to design a perturbation mechanism that jointly optimizes privacy and utility objectives...
Online social networks (OSNs) are immensely popular, but participants are increasingly uneasy with centralized services’ handling of user data. Decentralized OSNs offer the potential to address user’s anxiety while also enhancing the features and scalability offered by existing, centralized services. In this paper, we present Confidant, a decentralized OSN designed to support a scalable application...
Security researchers and practitioners must strive to develop better techniques and tools to help verify the authenticity of the data on which we increasingly rely.
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