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Trajectory-aware privacy-preserving method with local differential privacy in crowdsourcing
In spatial crowdsourcing services, the trajectories of the workers are sent to a central server to provide more personalized services. However, for...
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Freedom from interference: Decisional privacy as a dimension of consumer privacy online
The introduction of AI-based technologies has dramatically altered the premises for consumer privacy, enabling the unprecedented manipulation of...
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A Pragmatic Privacy-Preserving Deep Learning Framework Satisfying Differential Privacy
With the increasing use of technology in our daily lives, data privacy has become a critical issue. It is essential to carefully design technologies...
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Privacy-preserving cloud-based secure digital locker with differential privacy-based deep learning technique
Practically in this modern era, data privacy preservation is somewhat a complex technique due to the development of advanced technologies. During...
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Thermal Imaging in Robotics as a Privacy-Enhancing or Privacy-Invasive Measure? Misconceptions of Privacy when Using Thermal Cameras in Robots
This article examines the use of thermal imaging in human–robot interactions and its implications for privacy. Thermal imaging is used in robotics...
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The rise of “security and privacy”: bibliometric analysis of computer privacy research
The study of security and computer privacy has become a significant focus in security and privacy research. To reflect a website's, service's, or...
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What is my privacy score? Measuring users’ privacy on social networking websites
Social networking websites usage is becoming popular these days among individuals and organizations. Several organizations and researchers started...
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CAPPAD: a privacy-preservation solution for autonomous vehicles using SDN, differential privacy and data aggregation
Autonomous Vehicles (AVs) and driverless cars which are equipped with communication capabilities, advanced sensing, and Intelligent Control Systems...
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Research on the cognitive neural mechanism of privacy empowerment illusion cues regarding comprehensibility and interpretability for privacy disclosures
In the era of artificial intelligence, privacy empowerment illusion has become a crucial means for digital enterprises and platforms to “manipulate”...
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A privacy-preserving word embedding text classification model based on privacy boundary constructed by deep belief network
To effectively extract and classify the information from reports or documents and protect the privacy of the extracted results, we propose a privacy...
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Have the cake and eat it too: Differential Privacy enables privacy and precise analytics
Existing research in differential privacy, whose applications have exploded across functional areas in the last few years, describes an intrinsic...
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Enhancing privacy protections in national identification systems: an examination of stakeholders’ knowledge, attitudes, and practices of privacy by design
Privacy by Design (PbD) is a well-known concept that aims to provide a high level of protection for privacy throughout the entire life cycle of...
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Privacy preservation in the internet of vehicles using local differential privacy and IOTA ledger
With the growth in Vehicular Ad Hoc Network (VANET) technology, many vehicular devices are communicating with each other and with the edge nodes,...
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Enhancing correlated big data privacy using differential privacy and machine learning
Data are often correlated in real-world datasets. Existing data privacy algorithms did not consider data correlation an inherent property of...
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Privacy regulation in asymmetric environments
Around the world, strict privacy regulations are gradually being implemented, with the intended purpose of facilitating consumers to protect their...
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Modelling user notification scenarios in privacy policies
The processing of personal data gives a rise to many privacy concerns, and one of them is to ensure the transparency of data processing to end users....
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Reconciling privacy and accuracy in AI for medical imaging
Artificial intelligence (AI) models are vulnerable to information leakage of their training data, which can be highly sensitive, for example, in...
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Exploring privacy measurement in federated learning
Federated learning (FL) is a collaborative artificial intelligence (AI) approach that enables distributed training of AI models without data sharing,...
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A Value-centered Exploration of Data Privacy and Personalized Privacy Assistants
In the current post-GDPR landscape, privacy notices have become ever more prevalent on our phones and online. However, these notices are not well...
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Guiding the implementation of data privacy with microservices
Privacy by design is nowadays recognized as essential in bringing data privacy into software systems. However, developers still face many challenges...
