A decentralised architecture for secure exchange of assets in data spaces: The case of SEDIMARKGitHub by Erika Duriakova, Diarmuid O’Reilly-Morgan, Maroua Bahri, Maxime Costalonga, Gabriel Danciu, Septimiu Nechifor, Stefan-Cristian Jarcau, Tarek Elsaleh, Peipei Wu, Franck Le Gall, Grigorios Koutantos, Panagiotis Vlacheas, Luis Sánchez, Juan Ramón Santana, Pablo Sotres, Elias Tragos

“…Together the technologies used in SEDIMARK ensure privacy, trust and data quality for secure management, sharing, and monetisation of assets in data spaces.…”
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Mitigating Malicious Insider Threats to Common Data Environments in the Architecture, Engineering, and Construction Industry: An Incomplete Information Game Approach by KC Lalropuia, Sanjeev Goyal, Borja García de Soto, Dongchi Yao, Muammer Semih Sonkor

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Attitudes and preferences toward the adoption of voice-controlled intelligent personal assistants: Evidence from Croatia by Antun Biloš, Bruno Budimir, Borna Kraljević

“…This paper provides an examination of the differences between IPA users and non-users as well as an overview of (non-)user perception related to privacy and security issues associated with IPA and trust in companies' appropriate use of IPA-generated data. …”
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A DLP Module Design Based on Plug-in for MS Word by Hussein Al-sanabani, Murat İskefiyeli

“…This model uses security measures such as data encryption and access control to prevent accidental leakage of the classified files by the insiders. …”
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Data-Centric Fine-Tuning of Small Language Models for Automatic Extraction of Technical Requirements by Leopold Muller, Nina Schwarz, Lars Bocking, Andreas Bereczuk, Hanno Stagge, Wolfgang Kratsch, Niklas Kuhl

“…These results underscore the potential of data-centric fine-tuning for adapting small language models to high-stakes, privacy-sensitive tasks, offering a scalable alternative to LLMs enabling their applications to real-world use cases.…”
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Legal Reform of Artificial Intelligence's Liability to Personal Data Perspectives of Progressive Legal Theory by Junaidi Junaidi, Pujiono Pujiono, Rozlinda Mohamed Fadzil

“…The research found that the use of Artificial Intelligence in collecting and analysing personal data can threaten individual privacy. …”
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COMPUTATIONAL THINKING IN THE PROBLEM OF RELIABLE AND SECURE DATA TRANSMISSION OVER A COMMUNICATION CHANNEL by Kirill V. Agievets, Andarbek Z. Ahmadov, Grigory A. Ivanenko, Mikhail A. Ivanov, Mikael A. Kondakhchan, Andrey V. Starikovsky

“…There are three problems that have to be solved when transmitting data over communication channels: detection and correction of errors caused by interference in communication channels; ensuring of transmitted data privacy; protection against injection of false data. …”
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Reversible data hiding algorithm in encrypted images based on prediction error and bitplane coding by Haiyong WANG, Mengning JI

“…With the increasing use of cloud backup methods for storing important files, the demand for privacy protection has also grown.Reversible data hiding in encrypted images (RDHEI) is an important technology in the field of information security that allows embedding secret information in encrypted images while ensuring error-free extraction of the secret information and lossless recovery of the original plaintext image.This technology not only enhances image security but also enables efficient transmission of sensitive information over networks.Its application in cloud environments for user privacy protection has attracted significant attention from researchers.A reversible data hiding method in encrypted images based on prediction error and bitplane coding was proposed to improve the embedding rate of existing RDHEI algorithms.Different encoding methods were employed by the algorithm depending on the distribution of the bitplanes, resulting in the creation of additional space in the image.The image was rearranged to allocate the freed-up space to the lower-order planes.Following this, a random matrix was generated using a key to encrypt the image, ensuring image security.Finally, the information was embedded into the reserved space.The information can be extracted and the image recovered by the receiver using different keys.The proposed algorithm achieves a higher embedding rate compared to five state-of-the-art RDHEI algorithms.The average embedding rates on BOWS-2, BOSSBase, and UCID datasets are 3.769 bit/pixel, 3.874 bit/pixel, and 3.148 bit/pixel respectively, which represent an improvement of 12.5%, 6.9% and 8.6% compared to the best-performing algorithms in the same category.Experimental results demonstrate that the proposed algorithm effectively utilizes the redundancy of images and significantly improves the embedding rate.…”
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Pursuit of Digital Innovation in Psychiatric Data Handling Practices in Ireland: Comprehensive Case Study by Rana Zeeshan, John Bogue, Amna Gill, Mamoona Naveed Asghar

“…Our survey reported an average score of 4.37 of 10 (SD 1.25) given by participants in terms of technology use. Regarding privacy measures, 75% (n=12) of participants mentioned that staff members are allowed to keep their phones while accessing psychiatric case notes. …”
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Blockchain-enabled federated learning with edge analytics for secure and efficient electronic health records management by Munusamy S, Jothi K R

“…Abstract The rapid adoption of Federated Learning (FL) in privacy-sensitive domains such as healthcare, IoT, and smart cities underscores its potential to enable collaborative machine learning without compromising data ownership. …”
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Federated learning with tensor networks: a quantum AI framework for healthcare by Amandeep Singh Bhatia, David E Bernal Neira

“…The healthcare industry frequently handles sensitive and proprietary data, and due to strict privacy regulations, it is often reluctant to share it directly. …”
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Hierarchical Swin Transformer Ensemble with Explainable AI for Robust and Decentralized Breast Cancer Diagnosis by Md. Redwan Ahmed, Hamdadur Rahman, Zishad Hossain Limon, Md Ismail Hossain Siddiqui, Mahbub Alam Khan, Al Shahriar Uddin Khondakar Pranta, Rezaul Haque, S M Masfequier Rahman Swapno, Young-Im Cho, Mohamed S. Abdallah

“…However, deep learning (DL) models used in healthcare face significant challenges, including concerns about data privacy, domain-specific overfitting, and limited interpretability. …”
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Traffic concealed data detection method based on contrastive learning and pre-trained Transformer by HE Shuai, ZHANG Jingchao, XU Di, JIANG Shuai, GUO Xiaowei, FU Cai

“…To solve the problems of characterizing representing massive encrypted traffic, perceiving malicious behaviors, and identifying the ownership of privacy data, a traffic concealed data detection method was proposed based on contrastive learning and pre-trained Transformer. …”
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Substation Inspection Safety Risk Identification Based on Synthetic Data and Spatiotemporal Action Detection by Chengcheng Liu, Weihua Zhang, Weijin Xu, Bo Lu, Weijie Li, Xuefeng Zhao

“…Model training is conducted using three datasets: a real dataset, a synthetic dataset generated via a VWP, and a mixed dataset comprising both real and synthetic data. …”
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Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare by Anshul Thakur, Soheila Molaei, Pafue Christy Nganjimi, Fenglin Liu, Andrew Soltan, Patrick Schwab, Kim Branson, David A. Clifton

“…Abstract Robust data privacy regulations hinder the exchange of healthcare data among institutions, crucial for global insights and developing generalised clinical models. …”
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Ciphertext policy hidden access control scheme based on blockchain and supporting data sharing by Ruizhong DU, Tianhe ZHANG, Pengliang SHI

“…Objectives: Although the traditional attribute-based encryption scheme achieves one-to-many access control,there are still challenges such as single point of failure,low efficiency,no support for data sharing,and privacy leakage.To solve these problems,a ciphertext policy hidden access control scheme based on blockchain and supporting data sharing is proposed. …”
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Sense (and) the city: From Internet of Things sensors and open data platforms to urban observatories by Vijay Kumar, Sam Gunner, Maria Pregnolato, Patrick Tully, Nektarios Georgalas, George Oikonomou, Stylianos Karatzas, Theo Tryfonas

“…Anyone can monitor from their fitness to the air quality of their immediate environment using everyday technologies. With caveats around privacy and accuracy, such data could even complement those collected by authorities at city‐scale, for validating or improving policies. …”
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Optimising Data Analytics to Enhance Postgraduate Student Academic Achievement: A Systematic Review by Mthokozisi Masumbika Ncube, Patrick Ngulube

“…As such, this review aimed to identify data analytics approaches used by HEIs and explore challenges and best practices in their application. …”
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Multimodal Face Data Sets—A Survey of Technologies, Applications, and Contents by Kamela Al-Mannai, Khaled Al-Thelaya, Jens Schneider, Spiridon Bakiras

“…Additionally, biometric data is privacy-sensitive, and a comprehensive review from a data set perspective is missing. …”
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The impact of big data analytics on digital marketing decision-making: A comprehensive analysis by Roberta Bajrami, Adelina Gashi, Kaltrina Bajraktari, Etleva Namligjiu

“…An online questionnaire, delivered through SurveyMonkey, achieved a 92% response rate (n = 230), capturing data on tool usage, benefits, and problems. Data pre-processing includes duplicate removal and mean imputation, followed by K-means clustering and logistic regression analysis using Python (scikit-learn, pandas). …”
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