Do Cookie Banners Respect My Browsing Privacy? Measuring the Effectiveness of Cookie Rejection for Limiting Behavioral Advertising by Mateo Ormeno, Ha Dao, Valeria Herskovic, Kensuke Fukuda

“…Online behavioral advertising (OBA) is a method within digital advertising that exploits web users’ interests to tailor ads. Its use has raised privacy concerns among researchers, regulators, and the media, emphasizing the need for a reliable mechanism to measure its prevalence. …”
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Investigating the Relationship between Social Skills and Social Acceptance with Academic Performance, Considering the Mediating Role of Ethical Privacy by Taghreed Radhi Abdol Mohsin, Hassan Ghalavandi

“…Four standard questionnaires of social skills, social acceptance, respect for moral privacy, and academic performance were used for gathering data. …”
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Evaluation of privacy protection methods of public service advertising visual design in the perspective of artificial intelligence internet of things. by Xujun Tang

“…The digital watermark privacy protection method and the public service advertising work push privacy protection method are used to provide an innovative solution for public service advertising privacy protection. …”
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Federated Deep Learning for Scalable and Privacy-Preserving Distributed Denial-of-Service Attack Detection in Internet of Things Networks by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei, Riad Alharbey

“…ResNet improves feature extraction, VGGNet optimises feature refining, and Swin-Transformer captures contextual dependencies, making the model sensitive to complicated attack patterns across varied network circumstances. Using the FL framework, decentralised training protects data privacy and scales and adapts across diverse IoT contexts. …”
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Harnessing Artificial Intelligence to Transform Education: Challenges and Opportunities by Ahma Greta, Kadriu Arbana

“…These include worries about algorithmic unfairness, data privacy, and teachers’ or students’ resistance to using AI-based solutions. …”
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Optimizing malicious website prediction: An advanced XGBoost-based machine learning model by Hussain Sumaira, Zada Islam, Alazab Moutaz, Alfraihi Hessa, Aldhayan Manal, Ullah Inam, Khan Mohammad Asmat Ullah

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Online fashion consumerism among women: The interplay of digital experiences and decision-making – a mediated moderated analysis by Madhura K., Niyaz Panakaje, S. M. Riha Parvin, Shakira Irfana, Mural Henrita Cutinha, Yatheen A, Rovina Sharon Soans

“…However, challenges like concerns over data privacy and difficulties in verifying review authenticity negatively affect the attitude-behavior relationship, with a moderating effect of β = -0.092. …”
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The Adoption of Virtual Fitting Rooms in Iranian Sportswear Industries: A Mixed-Methods Study Based on TAM Model by Seyyed Iman Ghaffarisadr, Farzad Nobakht Sareban

“…Structural equation modelling was used to test the hypotheses. SMART PLS and SPSS 23 software were used for data analysis.Findings: The results supported the positive effect of the factors perceived ease of use, perceived usefulness, perceived enjoyment, and fashion leadership, as well as the negative impact of technology anxiety on adopting this technology. …”
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Federated Learning for Surface Roughness by Kai-Lun Cheng, Yu-Hung Ting, Wen-Ren Jong, Shia-Chung Chen, Zhe-Wei Zhou

“…A custom data acquisition system collected discharge current and spindle current signals, which were solely used as input features to train the deep learning model. …”
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Financial equality through technology: Do perceived risks deter Indian women from sustained use of mobile payment services? by Priyanka Yadav, Abhishek Kumar, Saroj Kumar Mishra, Khyati Kochhar

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QBPP: Quality of services–based location privacy protection method for location-based services in cloud-enabled Internet of vehicles by Ji-ming Chen, Ting-ting Li, Liang-jun Wang

“…To guarantee secure data transmission in Internet of vehicles, the batch validation technique is used to address data integrity. …”
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Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response by Yan Yan, Pengbin Yan, Adnan Mahmood, Yang Zhang, Quan Z. Sheng

“…The widespread use of spatial location-based services not only provides considerable convenience, but also exposes the downsides of location privacy leakage. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Federated Learning (FL) offers an encouraging solution to address these challenges by providing a privacy-preserving solution for investigating and detecting cyberattacks in IoT systems without negotiating data privacy. …”
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Ethical and privacy challenges of integrating generative AI into EHR systems in Tanzania: A scoping review with a policy perspective by Augustino Mwogosi

“…Results The review identified six key ethical and privacy challenges associated with generative AI in EHR systems: data privacy and security risks, algorithmic bias and fairness concerns, transparency and accountability issues, consent and autonomy challenges, human oversight gaps and risks of data re-identification. …”
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Enhancing accuracy through ensemble based machine learning for intrusion detection and privacy preservation over the network of smart cities by Mudita Uppal, Yonis Gulzar, Deepali Gupta, Jayant Uppal, Mukesh Kumar, Shilpa Saini

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Smart Grid Intrusion Detection for IEC 60870-5-104 With Feature Optimization, Privacy Protection, and Honeypot-Firewall Integration by Pedamallu Sai Mrudula, Rayappa David Amar Raj, Archana Pallakonda, Yanamala Rama Muni Reddy, K. Krishna Prakasha, V. Anandkumar

“…Furthermore, the proposed framework includes a federated learning-based scheme that utilizes differential privacy and homomorphic encryption to ensure the privacy and integrity of the data to enhance model interpretability and efficiency with feature ranking to provide insights into attack patterns and anomaly characteristics. …”
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Privacy-Preserving Glycemic Management in Type 1 Diabetes: Development and Validation of a Multiobjective Federated Reinforcement Learning Framework by Fatemeh Sarani Rad, Juan Li

“…Furthermore, these approaches typically rely on centralized data processing, which raises privacy concerns due to the sensitive nature of health care data. …”
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NN-QuPiD Attack: Neural Network-Based Privacy Quantification Model for Private Information Retrieval Protocols by Rafiullah Khan, Mohib Ullah, Atif Khan, Muhammad Irfan Uddin, Maha Al-Yahya

“…Numerous techniques are available to address privacy infringement, including Private Information Retrieval (PIR) protocols that use peer nodes to preserve privacy. …”
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A federated learning-based privacy-preserving image processing framework for brain tumor detection from CT scans by Abdullah Al-Saleh, Ghanshyam G. Tejani, Shailendra Mishra, Sunil Kumar Sharma, Seyed Jalaleddin Mousavirad

“…Because traditional deep learning models store all their data together, they raise questions about privacy, complying with regulations and the different types of data used by various institutions. …”
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A novel end-to-end privacy preserving deep Aquila feed forward networks on healthcare 4.0 environment by Ponugoti Kalpana, Sunitha Tappari, L. Smitha, Dasari Madhavi, K. Naresh, Maddala Vijayalakshmi

“…Though sensor-driven devices have largely eased everyday lives, these healthcare systems have been suffering from various security breaches and data privacy problems. This evokes a need for designing intelligent systems to eradicate data breaches and privacy problems. …”
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