Social Media Suicide Watch by Katherine Prothro

“…There was an immediate backlash due to concerns over privacy and the potential for stalkers and bullies to misuse this data and encourage suicide or self-harm, like Roy’s girlfriend did. …”
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Redefining customer connections in the UAE’s digital era: A study on emerging technological synergies by Hussam Ali, Ehab Haikal

“…This study investigates the socio-technical implications of IoT integration, particularly its effects on operational efficiency, customer engagement, digital inclusivity, ethical data practices, and sustainability. The research used a quantitative cross-sectional survey conducted from February to April 2024 across the UAE. …”
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Democratic Oversight of Government Hacking by Intelligence Agencies by André Ramiro

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Optimization of machine learning methods for de-anonymization in social networks by Nurzhigit Smailov, Fatima Uralova, Rashida Kadyrova, Raiymbek Magazov, Akezhan Sabibolda

“…Anonymity features are widely used to help individuals maintain their privacy, but they can also be exploited for malicious purposes. …”
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Social Implications of Technological Advancements in Sentiment Analysis: A Literature Review on Potential and Consequences over the Next 20 Years by Daryanto, Ika Safitri Windiarti, Bagus Setya Rintyarna

“…It enables more responsive policy design by understanding public emotions in political and social contexts. However, data privacy, misinformation, and diminished critical thinking persist. …”
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Artificial Intelligence-Driven Facial Image Analysis for the Early Detection of Rare Diseases: Legal, Ethical, Forensic, and Cybersecurity Considerations by Peter Kováč, Peter Jackuliak, Alexandra Bražinová, Ivan Varga, Michal Aláč, Martin Smatana, Dušan Lovich, Andrej Thurzo

“…Current and future developments must focus on securing AI models against attacks, ensuring data integrity, and safeguarding the privacy of individuals within this technological landscape.…”
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Blockchain-powered wireless sensor networks: enhancing security and privacy in the IoT era by Ibrahim Mekawy

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A multimodal differential privacy framework based on fusion representation learning by Chaoxin Cai, Yingpeng Sang, Hui Tian

“…Then based on this representation, we use the Local Differential Privacy (LDP) mechanism to protect data. …”
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Children's digital privacy on fast-food and dine-in restaurant mobile applications. by Christine Mulligan, Grace Gillis, Lauren Remedios, Christopher Parsons, Laura Vergeer, Monique Potvin Kent

“…Restaurant mobile applications are powerful platforms for collecting users' data and are popular among children. This study aimed to provide insight into the privacy policies of top dine-in and fast-food mobile apps in Canada and data collected on child users. …”
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A Verifiable, Privacy-Preserving, and Poisoning Attack-Resilient Federated Learning Framework by Washington Enyinna Mbonu, Carsten Maple, Gregory Epiphaniou, Christo Panchev

“…Federated learning is the on-device, collaborative training of a global model that can be utilized to support the privacy preservation of participants’ local data. …”
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Jointly Achieving Smart Homes Security and Privacy through Bidirectional Trust by Osman Abul, Melike Burakgazi Bilgen

“…Once approved, users are primarily concerned about privacy protection (i.e., user-to-system trust) when utilizing system services that require sensitive data for their functionality. …”
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Challenges in IoMT Adoption in Healthcare: Focus on Ethics, Security, and Privacy by Alton Mabina, Neo Rafifing, Boago Seropola, Thapelo Monageng, Pulafela Majoo

“…This study highlights ethical, security, and privacy barriers to IoMT adoption in developing countries and proposes strategies like regulatory frameworks, data encryption, AI transparency, and professional training to address these challenges. …”
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PRIVocular: Enhancing User Privacy Through Air-Gapped Communication Channels by Anastasios N. Bikos

“…PRIVocular (i.e., PRIV(acy)-ocular) is a VR-ready hardware–software integrated system that is capable of visually transmitting user data over three versatile modes of encapsulation, encrypted—without loss of generality—using an asymmetric-key cryptosystem. …”
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Location Privacy-Preserving Channel Allocation Scheme in Cognitive Radio Networks by Hongning Li, Qingqi Pei, Wenjing Zhang

“…In this paper, to make full use of idle spectrum with low probability of location leakage, we propose a Location Privacy-Preserving Channel Allocation (LP-p CA) scheme. …”
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GuardianML: Anatomy of Privacy-Preserving Machine Learning Techniques and Frameworks by Nges Brian Njungle, Eric Jahns, Zhenqi Wu, Luigi Mastromauro, Milan Stojkov, Michel A. Kinsy

“…Machine learning has become integral to our lives, finding applications in nearly every aspect of our daily routines. However, using personal information in machine learning applications has raised concerns about user data privacy and security. …”
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A Privacy-Preserving Querying Mechanism with High Utility for Electric Vehicles by Ugur Ilker Atmaca, Sayan Biswas, Carsten Maple, Catuscia Palamidessi

“…Simultaneously, personal data use for analytics is growing at an unprecedented rate, raising concerns for privacy. …”
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PPSC: High-Precision and Scalable Encrypted Privacy-Preserving Speech Classification by WANG Leilei, SONG Kao, ZHANG Yuanyuan, BI Renwan, XIONG Jinbo

“…Secondly, the PPSC scheme securely implements the fundamental modules such as the convolutional layer, ReLU layer, average pooling layer, fully connected layer, and Softmax layer. This ensures the privacy of speech data, speech classification models, and intermediate computing results. …”
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Transparent and Privacy-Preserving Mobile Crowd-Sensing System with Truth Discovery by Ruijuan Jia, Juan Ma, Ziyin You, Mingyue Zhang

“…This scheme enables data requesters to effectively verify the correctness of the truth discovery service while ensuring data privacy. …”
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An Exact Top- Query Algorithm with Privacy Protection in Wireless Sensor Networks by Huang Haiping, Feng Juan, Wang Ruchuan, Qin XiaoLin

“…The algorithm does the query exactly and meanwhile uses conic section privacy function to prevent the disclosure of the real data and then to promise the security of nodes in network. …”
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Enhanced Privacy-Preserving Architecture for Fundus Disease Diagnosis with Federated Learning by Raymond Jiang, Yulia Kumar, Dov Kruger

“…However, due to the many privacy regulations regarding personal data, pooling together data from multiple sources and storing them in a single (centralized) location for traditional ML model training are often infeasible. …”
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