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Xingchen Wang and Peng Li
With the widespread adoption of cloud computing, the face verification process often requires the client to upload the face to an untrusted cloud server to obtain the verification results. Privacy leakage issues may arise if the client?s private informat...
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Kanghee Park and Boyoung Kim
Within a construction project, the clients are categorized as private individuals, private companies, public institutions, etc. In this research, the private client is identified as a non-professional individual building owner and is involved in making d...
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Muhammad Mateen Yaqoob, Muhammad Nazir, Muhammad Amir Khan, Sajida Qureshi and Amal Al-Rasheed
One of the deadliest diseases, heart disease, claims millions of lives every year worldwide. The biomedical data collected by health service providers (HSPs) contain private information about the patient and are subject to general privacy concerns, and t...
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Hendrik Ballhausen and Ludwig Christian Hinske
Privacy-preserving computation (PPC) enables encrypted computation of private data. While advantageous in theory, the complex technology has steep barriers to entry in practice. Here, we derive design goals and principles for a middleware that encapsulat...
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Zacharias Anastasakis, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Stavroula Bourou, Konstantinos Psychogyios, Dimitrios Skias and Theodore Zahariadis
Federated Learning is identified as a reliable technique for distributed training of ML models. Specifically, a set of dispersed nodes may collaborate through a federation in producing a jointly trained ML model without disclosing their data to each othe...
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Yankai Lv, Haiyan Ding, Hao Wu, Yiji Zhao and Lei Zhang
Federated learning (FL) is an emerging decentralized machine learning framework enabling private global model training by collaboratively leveraging local client data without transferring it centrally. Unlike traditional distributed optimization, FL trai...
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Leina Abdelgalil and Mohamed Mejri
Electronic health records (EHRs) play an important role in our life. However, most of the
time, they are scattered and saved on different databases belonging to distinct institutions (hospitals,
laboratories, clinics, etc.) geographically distributed acr...
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Jestine Paul, Benjamin Hong Meng Tan, Bharadwaj Veeravalli and Khin Mi Mi Aung
Machine learning classification algorithms, such as decision trees and random forests, are commonly used in many applications. Clients who want to classify their data send them to a server that performs their inference using a trained model. The client m...
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Chin-Ling Chen, Zi-Yi Lim, Hsien-Chou Liao and Yong-Yuan Deng
Recently, private security services have become increasingly needed by the public. The proposed scheme involves blockchain technology with a smart contract. When a private security company signs a contract with a client, they install an Internet of Thing...
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Arthur Fournier, Franjieh El Khoury and Samuel Pierre
The rapid adoption of Android devices comes with the growing prevalence of mobile malware, which leads to serious threats to mobile phone security and attacks private information on mobile devices. In this paper, we designed and implemented a model for m...
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