Cross-Company Data Sharing Using Distributed Analytics by Soo-Yon Kim, Stefanie Berninger, Max Kocher, Martin Perau, Sandra Geisler

“…Furthermore, we find that the framework supports integration of data quality assessment and privacy preservation mechanisms. …”
Get full text

Identification of hazardous road locations using ambulance data by Anne Vingaard Olesen, Tim Alex Lindskou, Rasmus Øhlenschlæger, Torben Anders Kløjgaard, Anders Brogaard Tallaksen, Jens Lauritsen, Erika Frischknecht Christensen, Harry Lahrmann

“…Results: Compared to police data in the same study period, we found 3.2 times as many unique crash sites through the use of combined hospital patient and ambulance data. …”
Get full text

Sharing is CAIRing: Characterizing principles and assessing properties of universal privacy evaluation for synthetic tabular data by Tobias Hyrup, Anton Danholt Lautrup, Arthur Zimek, Peter Schneider-Kamp

“…However, the ability to share data is hindered by regulations protecting the privacy of natural persons. …”
Get full text

Privacy under threat – The intersection of IoT and mass surveillance by Siniša Domazet, Darko Marković, Tatjana Skakavac

“…It has been shown that there are issues with applying existing regulations to IoT and mass surveillance and that no universal legal framework currently exists to protect the right to privacy. The use of IoT technology, especially given the rapid development of artificial intelligence, will in the future raise numerous dilemmas regarding the entities responsible for collecting personal data, the consents required for data usage and processing, where the collected personal data will be used, and for what purposes. …”
Get full text

Ensuring Privacy and Security on Banking Websites in Malaysia: A Cookies Scanner Solution by Yi Hong Tay, Shih Yin Ooi, Ying Han Pang, Ying Huey Gan, Sook Ling Lew

Get full text

A Differential Privacy Framework with Adjustable Efficiency–Utility Trade-Offs for Data Collection by Jongwook Kim, Sae-Hong Cho

“…The widespread use of mobile devices has led to the continuous collection of vast amounts of user-generated data, supporting data-driven decisions across a variety of fields. …”
Get full text

Multiple modes of data sharing can facilitate secondary use of sensitive health data for research by Nicki Tiffin, Themba Mutemaringa, Tsaone Tamuhla, Eddie T Lulamba

“…Increasing volumes of highly granular data provide opportunities to leverage the evidence base, with growing recognition that health data are highly sensitive and onward research use may create privacy issues for individuals providing data. …”
Get full text

Mining privacy-preserving association rules using transaction hewer allocator and facile hash algorithm in multi-cloud environments by D. Dhinakaran, S. Gopalakrishnan, D. Selvaraj, M.S. Girija, G. Prabaharan

“…However, in outsourced data for tasks like frequent itemset mining, privacy is an important issue. …”
Get full text

The Dual Nature of Trust in Participatory Sciences: An Investigation into Data Quality and Household Privacy Preferences by Danielle Lin Hunter, Valerie Johnson, Caren Cooper

“…In Crowd the Tap, we engaged participants through facilitator organizations including high schools, faith communities, universities, and a corporate volunteer program. We used Kruskal Wallis tests and chi-square tests with Bonferroni post hoc tests to assess how data quality and privacy preferences differed across facilitator groups and amongst those who participated in the project independently (unfacilitated). …”
Get full text

A Comprehensive Study of Traditional and Deep-learning Schemes for Privacy and Data Security in the Cloud by mohammed sheet, Melad saeed

“…However, it faces great difficulties in ensuring data confidentiality and privacy. People hesitate to use it due to the risk of innumerable attacks and security breaches. …”
Get full text

Soulbound Tokens: Enabler for Privacy-Aware and Decentralized Authentication Mechanism in Medical Data Storage by Biagio Boi, Franco Cirillo, Marco De Santis, Christian Esposito

Get full text

Efficient privacy-preserving image retrieval scheme over outsourced data with multi-user by Xiangyu WANG, Jianfeng MA, Yinbin MIAO

“…The traditional privacy-preserving image retrieval schemes not only bring large computational and communication overhead,but also cannot protect the image and query privacy in multi-user scenarios.To solve above problems,an efficient privacy-preserving content-based image retrieval scheme was proposed in multi-user scenarios.The scheme used Euclidean distance comparison technique to rank the pictures according to similarity of picture feature vectors and return top-k returned.Meanwhile,the efficient key conversion protocol designed in proposed image retrieval scheme allowed each search user to generate queries based on his own private key so that he can retrieval encrypted images generated by different data owners.Strict security analysis shows that the user privacy and cloud data security can be well protected during the image retrieval process,and the performance analysis using real-world dataset shows that the proposed image retrieval scheme is efficient and feasible in practical applications.…”
Get full text

A synchronous compression and encryption method for massive electricity consumption data privacy preserving by Ruifeng Zhao, Jiangang Lu, Zhiwen Yu, Kaiwen Zeng

“…Our proposed algorithm uses a ternary Logistic-Tent chaotic system for generating a chaotic measurement matrix, allowing simultaneous data compression and encryption of user-side voltage and current data. …”
Get full text

Privacy-Preserving Keyword Search With Access Control for Secret Sharing-Based Data Outsourcing by Ahmad Akmal Aminuddin Mohd Kamal, Masamune Okada, Masaya Fujisawa

Get full text

Efficient and privacy-preserving certificateless data aggregation in Internet of things–enabled smart grid by Aijing Sun, Axin Wu, Xiaokun Zheng, Fangyuan Ren

“…If the user’s electricity consumption is transmitted in plaintext, the data may be used by some illegal users. At the same time, malicious users may send false data such that the control center makes a wrong power resource scheduling. …”
Get full text

Privacy-preserving federated learning for collaborative medical data mining in multi-institutional settings by Rahul Haripriya, Nilay Khare, Manish Pandey

“…Abstract Ensuring data privacy in medical image classification is a critical challenge in healthcare, especially with the increasing reliance on AI-driven diagnostics. …”
Get full text

An explainable federated blockchain framework with privacy-preserving AI optimization for securing healthcare data by Tanisha Bhardwaj, K. Sumangali

“…Abstract With the rapid growth of healthcare data and the need for secure, interpretable, and decentralized machine learning systems, Federated Learning (FL) has emerged as a promising solution. …”
Get full text

Decoding privacy concerns: the role of perceived risk and benefits in personal health data disclosure by Havva Nur Atalay, Şebnem Yücel

“…Results The analysis revealed a significant negative relationship between individuals’ personal health data disclosure behaviour and their privacy concerns. …”
Get full text

Shuffled differential privacy protection method for K-Modes clustering data collection and publication by Weijin JIANG, Yilin CHEN, Yuqing HAN, Yuting WU, Wei ZHOU, Haijuan WANG

“…Aiming at the current problem of insufficient security in clustering data collection and publication, in order to protect user privacy and improve data quality in clustering data, a privacy protection method for K-Modes clustering data collection and publication was proposed without trusted third parties based on the shuffled differential privacy model.K-Modes clustering data collection algorithm was used to sample the user data and add noise, and then the initial order of the sampled data was disturbed by filling in the value domain random arrangement publishing algorithm.The malicious attacker couldn’t identify the target user according to the relationship between the user and the data, and then to reduce the interference of noise as much as possible a new centroid was calculated by cyclic iteration to complete the clustering.Finally, the privacy, feasibility and complexity of the above three methods were analyzed from the theoretical level, and the accuracy and entropy of the three real data sets were compared with the authoritative similar algorithms KM, DPLM and LDPKM in recent years to verify the effectiveness of the proposed model.The experimental results show that the privacy protection and data quality of the proposed method are superior to the current similar algorithms.…”
Get full text

A controllable privacy data transmission mechanism for Internet of things system based on blockchain by ZiXiang Nie, YuanZhenTai Long, SenLin Zhang, YueMing Lu

“…With the in-depth integration of traditional industries and information technology in Internet of things, wireless sensor networks are used more frequently to transmit the data generated from various application scenarios. …”
Get full text