相关论文: Self-Sovereign Identity: A Systematic Review, Mapp…

Sensitive citizen data, such as social, medical, and fiscal data, is heavily fragmented across public bodies and the private domain. Mining the combined data sets allows for new insights that otherwise remain hidden. Examples are improved…

The unique identities of every mobile user (phone number,IMSI) and device (IMEI) are far from secure and are increasingly vulnerable to a variety of network-level threats. The exceedingly high reliance on the weak SIM authentication layer…

Ensuring the timeliness and reliability of master data remains a persistent challenge for many organizations. To mitigate these quality deficits, organizations frequently rely on commercial data brokers. However, this practice creates…

Single sign-on (SSO) allows a user to maintain only the credential for an identity provider (IdP) to log into multiple relying parties (RPs). However, SSO introduces privacy threats, as (a) a curious IdP could track a user's all visits to…

Personal data related to a user's activities, preferences and services, is considered to be a valuable commodity not only for a wide range of technology-oriented companies like Google, Amazon and Apple but also for more traditional…

While the adoption of connected vehicles is growing, security and privacy concerns are still the key barriers raised by society. These concerns mandate automakers and standardization groups to propose convenient solutions for privacy…

Single sign-on (SSO) systems, such as OpenID and OAuth, allow web sites, so-called relying parties (RPs), to delegate user authentication to identity providers (IdPs), such as Facebook or Google. These systems are very popular, as they…

Digital identities today continue to be a company resource instead of belonging to the actual person they represent. At the same time, the digitalization of everyday services intensifies the Identity Management problem and leads to a…

Training generative machine learning models to produce synthetic tabular data has become a popular approach for enhancing privacy in data sharing. As this typically involves processing sensitive personal information, releasing either the…

In the current data driven era, synthetic data, artificially generated data that resembles the characteristics of real world data without containing actual personal information, is gaining prominence. This is due to its potential to…

This paper studies the current "identity crisis" caused by the substantial security, privacy and usability shortcomings encountered in existing systems for identity management. Some of these issues are well known, while others are much less…

The analysis of consumers' personal information (PI) is a significant source to learn about consumers. In online settings, many consumers disclose PI abundantly -- this is particularly true for information provided on social network…

Identity documents automatic reading and verification is an appealing technology for nowadays service industry, since this task is still mostly performed manually, leading to waste of economic and time resources. In this paper the prototype…

Many assumptions that underpin human concepts of identity do not hold for machine minds that can be copied, edited, or simulated. We argue that there exist many different coherent identity boundaries (e.g.\ instance, model, persona), and…

Modern distributed applications in healthcare, supply chain, and the Internet of Things handle a large amount of data in a diverse application setting with multiple stakeholders. Such applications leverage advanced artificial intelligence…

Data privacy and ownership are significant in social data science, raising legal and ethical concerns. Sharing and analyzing data is difficult when different parties own different parts of it. An approach to this challenge is to apply…

Person re-identification (ReId), a crucial task in surveillance, involves matching individuals across different camera views. The advent of Deep Learning, especially supervised techniques like Convolutional Neural Networks and Attention…

This document considers the counteracting requirements of privacy and accountability applied to identity management. Based on the requirements of GDPR applied to identity attributes, two forms of identity, with differing balances between…

Participatory sensing is emerging as an innovative computing paradigm that targets the ubiquity of always-connected mobile phones and their sensing capabilities. In this context, a multitude of pioneering applications increasingly carry out…

Recently, with the advancement of the Internet of Things (IoT), WiFi CSI-based HAR has gained increasing attention from academic and industry communities. By integrating the deep learning technology with CSI-based HAR, researchers achieve…