Article
Health Care Sciences & Services
Andrew Graham Rundle, Michael David Miller Bader, Stephen John Mooney
Summary: Clinical epidemiology and patient-oriented health care research often use neighborhood-level data and require geocoding of patient address data to conduct the study. However, commonly used geocoding methods may reveal patients' personally identifiable information and compromise their protected health information when publishing research findings.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2022)
Article
Education & Educational Research
Joshua M. Rosenberg, Conrad Borchers, Sondra M. Stegenga, Macy A. Burchfield, Daniel Anderson, Christian Fischer
Summary: Schools and school districts using social media may unintentionally reveal students' personally identifiable information, such as faces and full names. Districts with higher student poverty rates and those that share more posts are more likely to depict students.
LEARNING MEDIA AND TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Chunchun Ni, Li Shan Cang, Prosanta Gope, Geyong Min
Summary: The growth of big data can increase risks of re-identification in complex IoT environment. This work proposes a data anonymisation evaluation framework that can evaluate commonly used data anonymization algorithms in terms of privacy preserving level, data utility, and performance. Experiment results demonstrate that the proposed solution can effectively evaluate the performance and de-identification features that can help to prevent inappropriate usage of anonymized data.
INFORMATION SCIENCES
(2022)
Article
Multidisciplinary Sciences
Ana-Maria Cretu, Federico Monti, Stefano Marrone, Xiaowen Dong, Michael Bronstein, Yves-Alexandre de Montjoye
Summary: In this study, a behavioral profiling attack model is proposed to re-identify individuals in anonymous datasets based on the stability of their interaction networks over time. The results show that the learned profiles are stable and can identify individuals even after a certain period of time.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Farough Ashkouti, Keyhan Khamforoosh
Summary: Recently, there has been significant growth in the field of big data and its applications in various areas such as IoT, bioinformatics, eCommerce, and social media. The large volume of data poses challenges to IT systems, leading to the need for large-scale and robust computing systems. Data publishing allows analysts to extract useful patterns, but it also raises concerns about individual privacy. Apache Spark, a fast in-memory computing framework, is used in this paper to propose an efficient parallel implementation of a new computing model for big data anonymization. This model addresses runtime, scalability, and performance issues through three phases of in-memory computations.
Article
Computer Science, Hardware & Architecture
Shipeng Li, Jingwei Li, Yuxing Tang, Xiapu Luo, Zheyuan He, Zihao Li, Xi Cheng, Yang Bai, Ting Chen, Yuzhe Tang, Zhe Liu, Xiaosong Zhang
Summary: This paper introduces BlockExplorer, an efficient and flexible blockchain exploration system for Ethereum. BlockExplorer utilizes a master-slave architecture, transaction-based partitioning, and code instrumentation to achieve data balance and complete data acquisition, accelerating data retrieval speed and detecting Ethereum attacks within a short time.
IEEE TRANSACTIONS ON COMPUTERS
(2023)
Article
Chemistry, Analytical
Arsalan Shahid, Thien-An Ngoc Nguyen, M-Tahar Kechadi
Summary: Obesity, especially childhood obesity, is a major public health issue globally. The Big Data against Childhood Obesity (BigO) project aims to collect data from children to create obesity prevalence models and provide real-time monitoring. Data security and privacy protection are crucial in ensuring the success of the project.
Article
Computer Science, Theory & Methods
Ying Zhao, Jinjun Chen
Summary: This article summarizes and analyzes the application of differential privacy solutions in protecting unstructured data, including various privacy models and mechanisms, as well as the challenges they face. It also discusses the privacy guarantees of these methods against AI attacks and utility losses, and proposes several possible directions for future research.
ACM COMPUTING SURVEYS
(2022)
Article
Computer Science, Artificial Intelligence
Huan Liu, Kai Li, Yan Chen, Xin (Robert) Luo
Summary: Information privacy is still not fully understood in terms of its value, and it is unclear how much firms should pay consumers to obtain their data. This study found that although consumers believe personally identifiable information (PII) is more valuable than non-PII, they do not demand a higher price when monetizing PII. However, consumers are more cautious and provide less data when dealing with PII compared to non-PII. The context and cultural dimensions such as individualism and uncertainty avoidance play a role in explaining international differences in willingness-to-accept (WTA) prices.
DECISION SUPPORT SYSTEMS
(2023)
Article
Computer Science, Information Systems
Lo'ai A. Tawalbeh, Gokay Saldamli
Summary: Large scale distributed systems, especially cloud and mobile cloud deployments, offer services that improve quality of life and organizational efficiency. Data-driven applications are popular and successful, but also bring challenges like storage, big data processing, and privacy concerns. Solutions using cloud computing, P2P systems, and hybrid mobile cloud models can enhance performance and address these issues.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Cigdem Bakir
Summary: This study discusses the issues of big data security and privacy, and proposes a blockchain-based security model called BSKM. The BSKM model integrates confidentiality, integrity, and availability to ensure the security of big data. It provides a practical and flexible structure for all database operations and guarantees data confidentiality, integrity, and consistency.
Article
Computer Science, Artificial Intelligence
G. Dumindu Samaraweera, J. Morris Chang
Summary: The relational database model has been the leading model for data storage and management for decades, but alternative models like NoSQL and NewSQL have emerged with the Big Data explosion. These database systems have the potential to change the architecture from centralized to distributed with the advancement of communication technology, but ensuring the security and privacy of the information they handle remains a major concern.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Article
Economics
Jiwen Chai, Lihao Wang
Summary: This study constructs a four-party evolutionary game model, using the Lotka-Volterra model to explore the impact of regulatory behavior on the diffusion of big data discriminatory pricing (BDDP) in two-sided enterprises. MATLAB simulation tools are used to mathematically deduce the evolutionary game and diffusion models, and analog simulation is used for correlation analysis. This study helps two-sided enterprises, governments, suppliers, and consumers better understand the diffusion pattern of BDDP and accurately predict its development, providing a quantitative theoretical basis for rational decision-making.
MANAGERIAL AND DECISION ECONOMICS
(2023)
Article
Computer Science, Artificial Intelligence
Yueyue Zhang, Cheng Zhang, Yunjie Xu
Summary: The study suggests that DPS investment reduces firm risk, with a more significant effect seen in non-BDA firms, further demonstrating that the business value of specific information technology (such as DPS) investment is influenced by firms' other IT assets (such as BDA).
DECISION SUPPORT SYSTEMS
(2021)
Article
Business
Lauren Labrecque, Ereni Markos, Kunal Swani, Priscilla Pena
Summary: The research shows that stress and perceptions of social contract violation significantly impact the outcomes of data breaches, and different data types also affect consumer coping behaviors. Taking actions could help reduce negative consumer responses.
JOURNAL OF BUSINESS RESEARCH
(2021)
