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541
A Reliable Application of MPC for Securing the Tri-Training Algorithm
Published 2023-01-01“…Due to the widespread use of distributed data mining techniques in a variety of areas, the issue of protecting the privacy of sensitive data has received increasing attention in recent years. …”
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542
Improved Denclue Outlier Detection Algorithm With Differential Privacy and Attribute Fuzzy Priority Relation Ordering
Published 2023-01-01“…Firstly, the differential privacy technology is used to add the Laplacian noise to the density to realize the sensitive information hiding among the data objects. …”
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543
How Service Quality and Perceived Privacy Can Affect the Customer Satisfaction in Generations Y and Z?
Published 2025-01-01“…Data were collected by distributing questionnaires using the purposive sampling method to 190 generation Y and Z participants who used online food delivery. …”
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544
Explainable Federated Framework for Enhanced Security and Privacy in Connected Vehicles Against Advanced Persistent Threats
Published 2025-01-01“…The critical need for vehicular data privacy restricts traditional centralized Machine Learning (ML) approaches. …”
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545
An Easily Scalable Docker-Based Privacy-Preserving Malicious Traffic Detection Architecture for IoT Environments
Published 2024-01-01“…The model is then trained using federated learning/edge computing to ensure data privacy. …”
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546
Privacy-Preserving U-Net Variants with pseudo-labeling for radiolucent lesion segmentation in dental CBCT
Published 2025-05-01“…To safeguard sensitive information, Differential Privacy Stochastic Gradient Descent (DP-SGD) is integrated using TensorFlow-Privacy, achieving a privacy budget of ε ≈ 1.5 with minimal performance degradation. …”
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547
Shape similarity differential privacy trajectory protection mechanism based on relative entropy and K-means
Published 2021-02-01“…To solve the problem that most studies had not fully considered the sensitivity of location to privacy budget and the influence of trajectory shape, which made the usability of published trajectory poor, a shape similarity differential privacy trajectory protection mechanism based on relative entropy and K-means was proposed.Firstly, according to the topological relationship of geographic space, relative entropy was used to calculate the sensitivity of real location to privacy budget, a real-time calculation method of location sensitive privacy level was designed, and a new privacy model was built in combination with differential privacy budget.Secondly, K-means algorithm was used to cluster the release position to obtain the release position set that was most similar to the real position direction, and Fréchet distance was introduced to measure the similarity between the release track and the real track, so as to improve the availability of the release track.Experiments on real data sets show that the proposed trajectory protection mechanism has obvious advantages in trajectory availability compared with others.…”
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548
Sharenting in Asunción, Paraguay: Parental Behavior, Risk Perception, and Child Privacy Awareness on Social Media
Published 2025-05-01“…A survey of 73 parents analysed posting habits, knowledge of risks, and possible influencing factors on parental digital behaviour. Data analysis techniques such as descriptive statistics and correlation analysis were used to examine the associations between the key variables. …”
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549
PP-PQB: Privacy-Preserving in Post-Quantum Blockchain-Based Systems: A Systematization of Knowledge
Published 2025-01-01“…To the best of our knowledge, there is no comprehensive review or taxonomy that provides a complete picture of post-quantum secure structures with privacy-preserving techniques that have the potential to be used in blockchain. …”
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550
A Blockchain-Based Privacy Protection Model Under Quality Consideration in Spatial Crowdsourcing Platforms
Published 2024-01-01“…This innovative model combines the strengths of centralized efficiency and decentralized privacy, and introduces a unique mechanism that significantly enhances privacy protection and ensures data integrity. …”
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551
Physically secure and fog-enabled lightweight authentication scheme for WBAN
Published 2025-08-01“…Abstract Wireless Body Area Networks (WBANs) are vital for healthcare, fitness monitoring, and remote patient care by means of combining sensors and wearable technologies for data collection and transmission. However, ensuring secure communication in WBANs remains a critical challenge and is generally insecure against the manipulation of data, breaches of privacy, and unauthorized access. …”
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552
Goalie: Defending Against Correlated Value and Sign Encoding Attacks
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553
Time‐specific encrypted range query with minimum leakage disclosure
Published 2021-01-01“…Abstract A time‐specific encrypted range query scheme that has the following properties is proposed. (1) The proposed scheme has trapdoor privacy and data privacy so that a semi‐honest cloud is not able to get any useful information from given ciphertexts and given tokens that are used for searching ranges. (2) Unlike most of the other studies which report that the cloud server stores single encrypted keyword/element in the database, in our solution, the cloud server stores encrypted multi‐keywords/ranges in the database. …”
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554
Can human rights law bend mass surveillance?
Published 2014-02-01“…This paper provides a brief introduction to PRISM, continues with an outline of the right to privacy as stipulated in the International Covenant on Civil and Political Rights (ICCPR), the European Convention on Human Rights and the EU Directive on Data Protection, and moves on to discuss whether international human rights law may be used to bend mass surveillance.…”
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555
A Comparative Study of Privacy-Preserving Techniques in Federated Learning: A Performance and Security Analysis
Published 2025-03-01“…Federated learning (FL) is a machine learning technique where clients exchange only local model updates with a central server that combines them to create a global model after local training. While FL offers privacy benefits through local training, privacy-preserving strategies are needed since model updates can leak training data information due to various attacks. …”
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556
A privacy preserving machine learning framework for medical image analysis using quantized fully connected neural networks with TFHE based inference
Published 2025-07-01“…However, sharing sensitive raw medical data with third parties for analysis raises significant privacy concerns. …”
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557
On the research for big data uses for public good purposes
Published 2016-12-01“…Finally, aside from the opportunities, the mass production and use of data has also brought many challenges, such as evaluating the representativity of the data or handling threats to the privacy of users, that we will discuss in the last section of this article.…”
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558
Differential Private POI Queries via Johnson-Lindenstrauss Transform
Published 2018-01-01“…In addition, the proposed perturbation method based on the Johnson Lindenstrauss transform satisfies the differential privacy. Two popular point of interest queries, <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-NN and Range, are used to evaluate the method on two real-world data sets. …”
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559
Behavioural Economics and Consumer Decision-Making in the Age of Artificial Intelligence (AI), Data Science, Business Analytics, and Internet of Things (IoT)
Published 2024-05-01“…However, while AI and IoT facilitate more efficient and engaging consumer experiences, they introduce complex ethical and practical concerns, particularly around data privacy, algorithmic fairness, and maintenance of consumer trust. …”
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560
A Systematic Review on the Use of Big Data in Tourism
Published 2024-09-01“…Limitations: Although the use of big data in academic research has made significant progress, there are still challenges regarding data quality, data cost, and user privacy concerns. …”
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