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Full-Text Articles in Physical Sciences and Mathematics
An Exploratory Study Of Social Support Systems To Help Older Adults In Managing Mobile Safety, Tamir Mendel, Debin Gao, David Lo, Eran Toch
An Exploratory Study Of Social Support Systems To Help Older Adults In Managing Mobile Safety, Tamir Mendel, Debin Gao, David Lo, Eran Toch
Research Collection School Of Computing and Information Systems
Older adults face increased safety challenges, such as targeted online fraud and phishing, contributing to the growing technological divide between them and younger adults. Social support from family and friends is often the primary way older adults receive help, but it may also lead to reliance on others. We have conducted an exploratory study to investigate older adults' attitudes and experiences related to mobile social support technologies for mobile safety. We interviewed 18 older adults about their existing support and used the think-aloud method to gather data about a prototype for providing social support during mobile safety challenges. Our findings …
Data Pricing And Data Asset Governance In The Ai Era, Jian Pei, Feida Zhu, Zicun Cong, Luo Xuan, Liu Huiwen, Xin Mu
Data Pricing And Data Asset Governance In The Ai Era, Jian Pei, Feida Zhu, Zicun Cong, Luo Xuan, Liu Huiwen, Xin Mu
Research Collection School Of Computing and Information Systems
Data is one of the most critical resources in the AI Era. While substantial research has been dedicated to training machine learning models using various types of data, much less efforts have been invested in the exploration of assessing and governing data assets in end-to-end processes of machine learning and data science, that is, the pipeline where data is collected and processed, and then machine learning models are produced, requested, deployed, shared and evolved. To provide a state-of-the-art overall picture of this important and novel area and advocate the related research and development, we present a tutorial addressing two essential …
Privacy-Preserving Federated Deep Learning With Irregular Users, Guowen Xu, Hongwei Li, Yun Zhang, Shengmin Xu, Jianting Ning, Robert H. Deng
Privacy-Preserving Federated Deep Learning With Irregular Users, Guowen Xu, Hongwei Li, Yun Zhang, Shengmin Xu, Jianting Ning, Robert H. Deng
Research Collection School Of Computing and Information Systems
Federated deep learning has been widely used in various fields. To protect data privacy, many privacy-preserving approaches have also been designed and implemented in various scenarios. However, existing works rarely consider a fundamental issue that the data shared by certain users (called irregular users) may be of low quality. Obviously, in a federated training process, data shared by many irregular users may impair the training accuracy, or worse, lead to the uselessness of the final model. In this paper, we propose PPFDL, a Privacy-Preserving Federated Deep Learning framework with irregular users. In specific, we design a novel solution to reduce …
Traceable Monero: Anonymous Cryptocurrency With Enhanced Accountability, Yannan Li, Guomin Yang, Wily Susilo, Yong Yu, Man Ho Au, Dongxi Liu
Traceable Monero: Anonymous Cryptocurrency With Enhanced Accountability, Yannan Li, Guomin Yang, Wily Susilo, Yong Yu, Man Ho Au, Dongxi Liu
Research Collection School Of Computing and Information Systems
Monero provides a high level of anonymity for both users and their transactions. However, many criminal activities might be committed with the protection of anonymity in cryptocurrency transactions. Thus, user accountability (or traceability) is also important in Monero transactions, which is unfortunately lacking in the current literature. In this paper, we fill this gap by introducing a new cryptocurrency named Traceable Monero to balance the user anonymity and accountability. Our framework relies on a tracing authority, but is optimistic, in that it is only involved when investigations in certain transactions are required. We formalize the system model and security model …
An Efficient Privacy Preserving Message Authentication Scheme For Internet-Of-Things, Jiannan Wei, Tran Viet Xuan Phuong, Guomin Yang
An Efficient Privacy Preserving Message Authentication Scheme For Internet-Of-Things, Jiannan Wei, Tran Viet Xuan Phuong, Guomin Yang
Research Collection School Of Computing and Information Systems
As an essential element of the next generation Internet, Internet of Things (IoT) has been undergoing an extensive development in recent years. In addition to the enhancement of peoples daily lives, IoT devices also generate/gather a massive amount of data that could be utilized by machine learning and big data analytics for different applications. Due to the machine-to-machine communication nature of IoT, data security and privacy are crucial issues that must be addressed to prevent different cyber attacks (e.g., impersonation and data pollution/poisoning attacks). Nevertheless, due to the constrained computation power and the diversity of IoT devices, it is a …
Proxy-Free Privacy-Preserving Task Matching With Efficient Revocation In Crowdsourcing, Jiangang Shu, Kan Yang, Xiaohua Jia, Ximeng Liu, Cong Wang, Robert H. Deng
Proxy-Free Privacy-Preserving Task Matching With Efficient Revocation In Crowdsourcing, Jiangang Shu, Kan Yang, Xiaohua Jia, Ximeng Liu, Cong Wang, Robert H. Deng
Research Collection School Of Computing and Information Systems
Task matching in crowdsourcing has been extensively explored with the increasing popularity of crowdsourcing. However, privacy of tasks and workers is usually ignored in most of exiting solutions. In this paper, we study the problem of privacy-preserving task matching for crowdsourcing with multiple requesters and multiple workers. Instead of utilizing proxy re-encryption, we propose a proxy-free task matching scheme for multi-requester/multi-worker crowdsourcing, which achieves task-worker matching over encrypted data with scalability and non-interaction. We further design two different mechanisms for worker revocation including ServerLocal Revocation (SLR) and Global Revocation (GR), which realize efficient worker revocation with minimal overhead on the …