Yorick Last (Paderborn University), Patricia Arias Cabarcos (Paderborn University)

To facilitate the growing demand for a universal means of digital identification across services, while preserving user control and privacy, multiple digital identity implementations have emerged. From a technical perspective, many of these rely on established concepts within cryptography, allowing them to provide benefits in terms of security and privacy. Recent legislation also promises broader recognition and acceptance of digital identities, both in the digital world and beyond. However, research into the usability, accessibility, and user understanding of digital identities is rare. We argue that the development of usable digital identity wallets is vital to the successful and inclusive application of digital identities in society. In this vision paper, we describe our research plans for obtaining a better understanding of how to develop these usable digital identities wallets.

View More Papers

UI-CTX: Understanding UI Behaviors with Code Contexts for Mobile...

Jiawei Li (Beihang University & National University of Singapore), Jiahao Liu (National University of Singapore), Jian Mao (Beihang University), Jun Zeng (National University of Singapore), Zhenkai Liang (National University of Singapore)

Read More

Cross-Origin Web Attacks via HTTP/2 Server Push and Signed...

Pinji Chen (Tsinghua University), Jianjun Chen (Tsinghua University & Zhongguancun Laboratory), Mingming Zhang (Zhongguancun Laboratory), Qi Wang (Tsinghua University), Yiming Zhang (Tsinghua University), Mingwei Xu (Tsinghua University), Haixin Duan (Tsinghua University)

Read More

DLBox: New Model Training Framework for Protecting Training Data

Jaewon Hur (Seoul National University), Juheon Yi (Nokia Bell Labs, Cambridge, UK), Cheolwoo Myung (Seoul National University), Sangyun Kim (Seoul National University), Youngki Lee (Seoul National University), Byoungyoung Lee (Seoul National University)

Read More

URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning

Duanyi Yao (Hong Kong University of Science and Technology), Songze Li (Southeast University), Xueluan Gong (Wuhan University), Sizai Hou (Hong Kong University of Science and Technology), Gaoning Pan (Hangzhou Dianzi University)

Read More