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941
Gradual Geometry-Guided Knowledge Distillation for Source-Data-Free Domain Adaptation
Published 2025-04-01“…Due to access to the source data during the transfer phase, conventional domain adaptation works have recently raised safety and privacy concerns. …”
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942
Bibliometric mapping of data science in education: Trends, benefits, challenges, and future directions
Published 2025-01-01“…Co-occurrence analysis reveals three main clusters: DS approaches, student interactions with learning, and data analysis techniques. This study identifies key research trends and challenges, including limited infrastructure, skills gaps among educators, and privacy concerns, while addressing gaps in the literature regarding the long-term impact and contextualization of DS in education. …”
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943
Personal Information Sharing Behavior Using Social Media
Published 2025-06-01“…The three-factor (keywords, countries and sources) revealed that the researchers of top countries used mostly six keywords (self-disclosure, social media, privacy, Facebook, social networking sites, and social support) and they preferably published in two major sources. …”
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944
A decentralised architecture for secure exchange of assets in data spaces: The case of SEDIMARKGitHub
Published 2025-08-01“…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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945
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946
A DLP Module Design Based on Plug-in for MS Word
Published 2020-08-01“…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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947
Attitudes and preferences toward the adoption of voice-controlled intelligent personal assistants: Evidence from Croatia
Published 2023-06-01“…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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948
Blockchain-enabled federated learning with edge analytics for secure and efficient electronic health records management
Published 2025-07-01“…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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949
Federated learning with tensor networks: a quantum AI framework for healthcare
Published 2024-01-01“…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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950
Hierarchical Swin Transformer Ensemble with Explainable AI for Robust and Decentralized Breast Cancer Diagnosis
Published 2025-06-01“…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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951
Pursuit of Digital Innovation in Psychiatric Data Handling Practices in Ireland: Comprehensive Case Study
Published 2025-06-01“…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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952
COMPUTATIONAL THINKING IN THE PROBLEM OF RELIABLE AND SECURE DATA TRANSMISSION OVER A COMMUNICATION CHANNEL
Published 2025-05-01“…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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953
Reversible data hiding algorithm in encrypted images based on prediction error and bitplane coding
Published 2023-12-01“…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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954
Data-Centric Fine-Tuning of Small Language Models for Automatic Extraction of Technical Requirements
Published 2025-01-01“…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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955
Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare
Published 2024-10-01“…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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956
Legal Reform of Artificial Intelligence's Liability to Personal Data Perspectives of Progressive Legal Theory
Published 2024-04-01“…The research found that the use of Artificial Intelligence in collecting and analysing personal data can threaten individual privacy. …”
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957
Traffic concealed data detection method based on contrastive learning and pre-trained Transformer
Published 2025-03-01“…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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958
Ciphertext policy hidden access control scheme based on blockchain and supporting data sharing
Published 2022-06-01“…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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959
The impact of big data analytics on digital marketing decision-making: A comprehensive analysis
Published 2025-08-01“…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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960
Sense (and) the city: From Internet of Things sensors and open data platforms to urban observatories
Published 2024-12-01“…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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