Federated target trial emulation using distributed observational data for treatment effect estimation by Haoyang Li, Chengxi Zang, Zhenxing Xu, Weishen Pan, Suraj Rajendran, Yong Chen, Fei Wang

“…Abstract Target trial emulation (TTE) aims to estimate treatment effects by simulating randomized controlled trials using real-world observational data. Applying TTE across distributed datasets shows great promise in improving generalizability and power but is always infeasible due to privacy and data-sharing constraints. …”
Get full text

Real-Time Financial Fraud Detection Using Adaptive Graph Neural Networks and Federated Learning by Milad Rahmati

Get full text

Generating unseen diseases patient data using ontology enhanced generative adversarial networks by Chang Sun, Michel Dumontier

“…Abstract Generating realistic synthetic health data (e.g., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards. …”
Get full text

Predicting financial default risks: A machine learning approach using smartphone data by Shinta Palupi, Gunawan, Ririn Kusdyawati, Richki Hardi, Rana Zabrina

“…This study leverages machine learning (ML) techniques to predict financial default risks using smartphone data, providing a novel approach to financial risk assessment. …”
Get full text

Sample selection using multi-task autoencoders in federated learning with non-IID data by Emre Ardıç, Yakup Genç

“…Federated learning is a machine learning paradigm in which multiple devices collaboratively train a model under the supervision of a central server while ensuring data privacy. However, its performance is often hindered by redundant, malicious, or abnormal samples, leading to model degradation and inefficiency. …”
Get full text

A remote sensing encrypted data search method based on a novel double-chain by Xixi Yan, Pei Yin, Yongli Tang, Suwei Feng

“…However, with the rapid urbanisation and the increase in data capacity, how to store and retrieve remote sensing data which have more potential value and privacy with a more effective and safe method has become an imminent issue. …”
Get full text

Exploring the Use of AI in Qualitative Data Analysis: Comparing Manual Processing with Avidnote for Theme Generation by S. M. Akramul Kabir, Fareeha Ali, Rana Lotfy Ahmed, Ruqayya Sulaiman-Hill

“…However, fundamental concerns persist regarding the robustness, generalisability, credibility, reliability and trustworthiness of qualitative research when using AI technologies. Ethical considerations, such as data security and privacy, also need to be addressed in research settings. …”
Get full text

TrapMI: A Data Protection Method to Resist Model Inversion Attacks in Split Learning by Hyunsik Na, Daeseon Choi

“…However, concerns remain regarding data privacy leakage because an attacker can still attempt model inversion attacks based on the intermediate features. …”
Get full text

Defend Against Property Inference Attack for Flight Operations Data Sharing in FedMeta Framework by Jin Lei, Weiyun Li, Meng Yue, Zhijun Wu

“…FedMeta-CTGAN exploits the natural privacy-preserving properties of a two-stage update in meta-learning, using real data to train the CTGAN model and synthetic fake data as query data during meta-training. …”
Get full text

A Novel Linearly Complex Extended Signed Response-Based Node Authentication Scheme for Internet of Medical Things by Muhammad Saud Khan, Muhammad Sardaraz, Muhammad Tahir, Abdullah Alourani

Get full text

Consumer Protection in Cyberspace by Oscar H. Gandy, Jr.

Get full text

THE ETHICAL STARTUP? by Alexis Walker

“…Instead, the view proposed here would ask companies to do more to prevent or decrease the risk of a breach of privacy, unexpected later use of data, and reidentification. …”
Get full text

ZSS Signature-Based Audit Message Verification Process for Cloud Data Integrity by Paromita Goswami, Neetu Faujdar, Somen Debnath, Ajoy Kumar Khan, Ghanshyam Singh

“…Instead of establishing a secure communication route between all parties, a progressive technique is therefore required to thwart enemies’ attempts to collaborate with data owners who have outsourced their data. In this paper, we propose a model for an effective data integrity and audit message verification system based on the ZSS (Zhang, Safavi, and Susilo) signature, which protects data privacy in cloud storage and uses faked data recovery to pay back original data using a modular approach. …”
Get full text

Comprehensive Review and Analysis of Cryptography Techniques in Cloud Computing by K. Sasikumar, Sivakumar Nagarajan

Get full text

Federated Learning for Heterogeneous Multi-Site Crop Disease Diagnosis by Wesley Chorney, Abdur Rahman, Yibin Wang, Haifeng Wang, Zhaohua Peng

“…The objective of this collaboration is to create a classifier that every farm can use to detect and manage rice crop diseases by leveraging data sharing while safeguarding data privacy. …”
Get full text

A Systematic Literature Review of Machine Unlearning Techniques in Neural Networks by Ivanna Daniela Cevallos, Marco E. Benalcázar, Ángel Leonardo Valdivieso Caraguay, Jonathan A. Zea, Lorena Isabel Barona-López

“…This review examines the field of machine unlearning in neural networks, an area driven by data privacy regulations such as the General Data Protection Regulation and the California Consumer Privacy Act. …”
Get full text

Ethereum blockchain for electronic health records: securing and streamlining patient management by J. S. Simi Mole, J. S. Simi Mole, R. S. Shaji, R. S. Shaji

“…Electronic health records (EHRs) are increasingly replacing traditional paper-based medical records due to their speed, security, and ability to eliminate redundant data. However, challenges such as EHR interoperability and privacy concerns remain unresolved. …”
Get full text

Convergence Analysis for Differentially Private Federated Averaging in Heterogeneous Settings by Yiwei Li, Shuai Wang, Qilong Wu

“…Federated learning (FL) has emerged as a prominent approach for distributed machine learning, enabling collaborative model training while preserving data privacy. However, the presence of non-i.i.d. data and the need for robust privacy protection introduce significant challenges in theoretically analyzing the performance of FL algorithms. …”
Get full text

Edge Computing Architectures for Low-Latency Data Processing in Internet of Things Applications by Banoth Sreenu, M Vineesha, Punna Hari Shankar, P Mathiyalagan, Prakash Vijay, M Jasmin

Get full text

DEBPIR: enhancing information privacy in decentralized business modeling by Gulshan Kumar, Rahul Saha, Mauro Conti, Tai Hoon Kim

“…Abstract Business modelling often involves extensive data collection and analysis, raising concerns about privacy infringement. …”
Get full text