FusionCrypt: Enhancing Image Security Through Hybrid Encryption
Year: 2025
Type: article
Abstract: The poster session of EuroS&P offers security and privacy researchers an opportunity to share recent results and receive valuable feedback on ongoing work from the participants at the conference. This year, 26 poster abstracts were submitted, 16 more than the previous year. This indicates a growing interest in the poster session of the conference. One abstract was desk-rejected, while the others underwent review. The reviewers were requested to check the coherence of the abstracts with the scope of EuroS&P, as well as novelty, timeliness and clarity, without being requested to provide in-depth technical feedback. Nonetheless, many reviewers provided detailed and constructive feedback to help authors improve their work. Each abstract was reviewed by at least two members of the program committee. After the review phase, the program committee decided to accept 18 submitted abstracts (acceptance rate 69%).I would like to thank all authors for their contributions, and in particular the poster presenters, whose efforts brought the poster session to life and made it a lively and engaging part of the conference. Special thanks go to the members of the program committee of the EuroS&P poster session, for their detailed and useful reviews. I am deeply grateful for their support. I would also like to thank Stefano Calzavara and Paolo Falcarin, the general chairs; Victoria Buchsbaum and Andreas Ekelhart, the publication chairs; Anja Lehmann and Ben Stock, the program chairs; Pietro Ferrara, the financial chair; the local team and everyone else who contributed to organizing the conference and, in particular, the poster session. I also thank Ivan Liang for managing the submission platform and Alvise Rabitti for keeping the website up to date with the latest information on the call for posters.Lorenzo Cazzaro, Università Ca’ Foscari Venezia, ItalyIEEE European Symposium on Security and Privacy 2025 Poster Chair
Author: Dembani, Rahool
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893526138
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