22 papers · ranked by Valyu relevance
Rose Adee, Haralambos Mouratidis, Naveen Chilamkurti
Cloud computing is a rapidly expanding field. It allows users to access computer system resources as needed, particularly data storage and computational power, without managing them directly. This paper aims to create a data security model based on cryptography and steganography for data in cloud computing that seeks…
Houda Ferradi, Jiannong Cao, Shan Jiang, Yinfeng Cao + 1 more
Big Data Sharing (BDS) refers to the act of the data owners to share data so that users can find, access and use data according to the agreement. In recent years, BDS has been an emerging topic due to its wide applications, such as big data trading and cross-domain data analytics. However, as the multiple parties are…
Zhenqi Wang, Shaopeng Guan, Sitharthan Ramachandran
The traditional data-sharing model relies on a centralized third-party platform, which presents challenges such as poor transaction transparency and unsecured data security. In this article, we propose a blockchain-based traceable and secure data-sharing scheme. Firstly, we designed an attribute encryption-based method…
Feng Wen, Zhuo Wang, Leda Qu, Haixin Huang + 2 more
'Anwitaman Datta'] Data sharing is increasingly important across various industries. However, issues such as data integrity verification during sharing, encryption key leakage, and difficulty sharing data between different user groups have been identified. To address these challenges, this study proposes a multi-group…
Maryam Almarwani, Boris Konev, Alexei Lisitsa
Data encryption limits the power and efficiency of queries. Direct processing of encrypted data should ideally be possible to avoid the need for data decryption, processing, and re-encryption. It is vital to keep the data searchable and sortable. That is, some information is intentionally leaked. This intentional…
Deborah Stacey, Kenneth Wulff, Nidhip Chikhalla, Theresa Bernardo
Solving complex global problems involving data and data analysis can require data from both the public and private sectors. The sharing of data has traditionally been restricted to open data. To facilitate the use of both open and private data, a new data-sharing framework has been constructed as an extension to the…
Owen Lo, William J. Buchanan, Sarwar Sayeed, Pavlos Papadopoulos + 3 more
'Nikolaos Pitropakis' 'Christos Chrysoulas' 'Paolo Bellavista'] E-governance is a process that aims to enhance a government’s ability to simplify all the processes that may involve government, citizens, businesses, and so on. The rapid evolution of digital technologies has often created the necessity for the…
Siyuan Xia, Zhi-ru Zhu, Chris Zhu, Jinjin Zhao + 6 more
'Aaron J. Elmore' 'Ian Foster' 'Michael J. Franklin' 'Sanjay Krishnan' 'Raul Castro Fernandez'] Pooling and sharing data increases and distributes its value. But since data cannot be revoked once shared, scenarios that require controlled release of data for regulatory, privacy, and legal reasons default to not sharing.…
Kexian Liu, Jianfeng Guan, HU Xiao-long, Jianli Liu + 1 more
Internet of Things Authors: ['Kexian Liu' 'Jianfeng Guan' 'HU Xiao-long' 'Jianli Liu' 'Hongke Zhang'] Abstract—The growing complexity of Internet of Things (IoT) environments, particularly in cross-domain data sharing, presents significant security challenges. Existing data-sharing schemes often rely on computationally…
Jason M. Carpenter, Zhi-Li Zhang
The modern data economy is built on sharing data. However, sharing data can be an expensive and risky endeavour. Existing sharing systems like Distributed File Systems provide full read, write, and execute Role-based Access Control (RBAC) for sharing data, but can be expensive and difficult to scale. Likewise such…
Cláudia Brito, Pedro Ferreira, João Paulo
Breakthroughs in sequencing technologies led to an exponential growth of genomic data, providing unprecedented biological in-sights and new therapeutic applications. However, analyzing such large amounts of sensitive data raises key concerns regarding data privacy, specifically when the information is outsourced to…
Manaswitha Edupalli, Tivadar Péter Török, Madhava Jay, Keelan Jordan + 5 more
Biomedical datasets representing diverse populations are essential for advancing precision medicine, yet remain siloed due to regulatory, sovereignty, and privacy constraints. Existing data-sharing solutions remain limited. Centralized repositories and Trusted Research Environments (TREs) require data migration into…
Hyunghoon Cho, David Froelicher, Jeffrey Chen, Manaswitha Edupalli + 4 more
Sharing data across multiple institutions for genome-wide association studies (GWAS) would enable discovery of novel genetic variants linked to health and disease. However, existing regulations on genomic data sharing and the sheer size of the data limit the scope of such collaborations. Although cryptographic tools…
Jeffrey Chen, Manaswitha Edupalli, Bonnie Berger, Hyunghoon Cho
Privacy-preserving algorithms for genome-wide association studies (GWAS) promise to facilitate data sharing across silos to accelerate new discoveries. However, existing approaches do not support an important, prevalent class of methods known as linear mixed model (LMM) association tests or would provide limited…
Khalid K. Almuzaini, Amit Kumar Sinhal, Raju Ranjan, Vikas Goel + 2 more
Cloud technology is a business strategy that aims to provide the necessary material to customers depending on their needs. Individuals and cloud businesses alike have embraced the cloud storage service, which has become the most widely used service. The industries outsource their data to cloud storage space to relieve…
Juha-Pekka Soininen, Gabriella Laatikainen
The paper presents a use case model and a logical architecture model of a data space system. The models view the data space system from the user and operator perspectives and describe the needed functionalities and their connection on an abstract level. The core features in our data space model are collaboration…
Authors not listed
Next Generation Risk Assessment (NGRA) promotes animal-free, exposure-informed, and hypothesis-driven approaches to chemical safety assessment. In silico tools, such as quantitative structure-activity relationship (QSAR) models, are valuable new approach methodologies (NAMs) for use in NGRA. However, the practical…
Jingcheng Zhang, Yingxuan Ren, Man Ho Au, Ka-Ho Chow + 5 more
With the rapid developments in sequencing technologies, individuals now have unprecedented access to their genomic data. However, existing data management systems or protocols are inadequate for protecting privacy, limiting individuals’ control over their genomic information, hindering data sharing, and posing a…
Authors not listed
The discoverability and reusability of data is critical for machine learning to drive new discovery in the chemical sciences, and the ‘FAIR Guiding Principles for scientific data management and stewardship’ provide a measurable set of guidelines that can be used to ensure the accessibility of reusable data. We…
Chia-Lin Lin, Pei-Chi Huang, Simone Graessle, Christoph Grathwol + 20 more
Results of scientific work in chemistry can usually be obtained in the form of materials and data. A big step towards transparency and reproducibility of the scientific work can be gained if scientists publish their data in a FAIR (Findable, Accessible, Interoperable, Reusable) manner in research data repositories.…
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Authors not listed
The nanosafety domain has seen significant advancements in data generation and sharing, yet challenges remain in ensuring data interoperability and reuse. This article focuses on developing a semantic interoperability framework for nanosafety data to maximize the FAIRness (Findability, Accessibility, Interoperability…