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  1. ; ; ; ; ; (, Proceedings of The 33rd USENIX Security Symposium (USENIX Security))
    Free, publicly-accessible full text available August 14, 2025
  2. ; ; ; ; ; ; ; ; ; ; et al (, Proceedings of The 33rd USENIX Security Symposium (USENIX Security))
    Free, publicly-accessible full text available August 14, 2025
  3. ; ; ; ; ; (, Proceedings of the 41st International Conference on Machine Learning (ICML))
    Free, publicly-accessible full text available July 21, 2025
  4. ; ; (, Proceedings of The IEEE CVPR Workshop on Fair, Data-efficient, and Trusted Computer Vision (TCV))
    Accepted Manuscript Full Text Available
  5. ; ; ; (, Proceedings of the International AAAI Conference on Web and Social Media)
    Recently, deepfake techniques have been adopted by real-world adversaries to fabricate believable personas (posing as experts or insiders) in disinformation campaigns to promote false narratives and deceive the public. In this paper, we investigate how fake personas influence the user perception of the disinformation shared by such accounts. Using Twitter as an exemplary platform, we conduct a user study (N=417) where participants read tweets of fake news with (and without) the presence of the tweet authors' profiles. Our study examines and compares three types of fake profiles: deepfake profiles, profiles of relevant organizations, and simple bot profiles. Our results highlight the significant impact of deepfake and organization profiles on increasing the perceived information accuracy of and engagement with fake news. Moreover, deepfake profiles are rated as significantly more real than other profile types. Finally, we observe that users may like/reply/share a tweet even though they believe it was inaccurate (e.g., for fun or truth-seeking), which could further disseminate false information. We then discuss the implications of our findings and directions for future research. 
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    Full Text Available 
  6. ; ; (, Proceedings of The 45th IEEE Symposium on Security and Privacy (IEEE SP))
    Accepted Manuscript Full Text Available
  7. ; ; ; ; (, ACM)
    Full Text Available 
  8. ; ; ; ; ; ; (, ACM Proceedings of ACM CHI Conference on Human Factors in Computing Systems (CHI))
    Full Text Available 
  9. ; ; ; ; ; ; ; ; (, Deep Learning Security and Privacy Workshop (DLSP))
    Full Text Available 
  10. ; ; ; ; ; ; (, Proceedings of The 44th IEEE Symposium on Security and Privacy (IEEE SP))
    Accepted Manuscript Full Text Available