FedeAMR-CFF: A Federated Automatic Modulation Recognition Method Based on Characteristic Feature Fine-Tuning by Meng Zhang, Jiankun Ma, Zhenxi Zhang, Feng Zhou

“…Existing DL-AMR schemes primarily adopt a centralized training architecture, where a unified model is trained on a central server using local data from terminal devices. Although such methods achieve high recognition accuracy, they carry substantial privacy leakage risks. …”
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Stable federated learning method for low-altitude IoT networks based on election strategy by SHEN Lingfeng, WANG Guanghui, BAI Tianshui, ZHU Zhengyu, ZHANG Qiankun

“…The deep integration of UAV and Internet of things (IoT) transmits a large amount of sensitive data in the air-to-ground intelligent network, posing a serious risk of privacy leakage. …”
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Personalizing the Marketing with Artificial Intelligence (AI) by Rozhko Viktor I., Pletnova Yelyzaveta S.

“…One of the biggest risks is the issue of data privacy. For personalization and targeting, it is necessary to collect a large amount of information about consumers, which can raise concerns about violating their privacy. …”
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The Legal Challenges of Implementing AI in Emergency Departments by Shaghayegh Rahmani, Sahar Azamghasemzadeh

“…Additionally, AI systems used in healthcare must be designed with robust security measures to prevent data breaches and ensure the integrity of patient information (1). …”
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Greening the justice system: assessing the legality, feasibility, and potential of artificial intelligence in advancing environmental sustainability within the Indian judiciary by Anbarasi G, Sankar D

“…While AI integration shows significant promise in reducing environmental impact and improving judicial efficiency, the study identifies key challenges including the need for comprehensive legislation governing AI use in judiciary, substantial infrastructure requirements, and data privacy concerns. …”
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Federated Learning for Grading Oil Palm Fruit Ripeness in the Oil Palm Industry by Patchanee Laddawong, Yutthapong Pianroj, Piyanart Chotikawanid, Teerasak Punvichai, Saysunee Jumrat, Atitaya Kham-Ouam, Jirapond Muangprathub

“…Current trends focus on computer vision techniques based on image processing and machine learning to improve grading of oil palm fruit bunches at an individual factory, resulting in limited diversity of the data used for evaluation. Collecting data from all factories offers informational advantages but raises privacy concerns. …”
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Empowering Public Health: AI‐Powered Security Solutions for AI‐Driven Challenges by Shahrukh Mushtaq, Qurra‐Tul‐Ain Hameeda

“…These discrepancies are linked to the data used to train these models, implying that incorporating more specialised healthcare data could enhance performance; however, such data usage must align with ethical guidelines. …”
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Balancing tech and humanity by Linda Cottone

“…While technology can enhance efficiency, as shown in Lebanon's response to the Tripoli bomb attack, it must adhere to international legal standards, especially privacy protections in the ICCPR and UDHR. The use of AI in identification processes raises concerns about wrongful identification, privacy breaches, and discrimination, especially when sensitive data is processed without human oversight. …”
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Challenges and opportunities of artificial intelligence in African health space by Muslim A. Alaran, Salim Kamaludeen Lawal, Mustapha Husseini Jiya, Salihu Alhassan Egya, Mohamed Mustaf Ahmed, Abdullateef Abdulsalam, Usman Abubakar Haruna, Muhammad Kabir Musa, Don Eliseo Lucero-Prisno

“…However, to fully realize its benefits, it is necessary to consider issues concerning data privacy, equity, infrastructure integration, and ethical policy development. …”
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Toward Culturally and Linguistically Responsive E-Learning in Post-COVID-19 Higher Education: Perspectives from the United Arab Emirates by Sarah Hopkyns

“…In the Gulf, cultural, religious, and sociolinguistic dynamics can present additional challenges for teaching and learning online. Reluctance to use cameras due to modesty, privacy, and E-safety concerns, amongst others, affects interaction and rapport. …”
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Qualitative Investigation of Digital Technologies, Social Media, and AI on Human Behaviour, Identity, Communication, and Social Relations in Australia by Isla Davis

“…Additionally, the research identifies societal concerns about AI, including privacy, data exploitation, and the blending of human and machine interactions, which impact decision-making and personal boundaries. …”
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Federated learning system on autonomous vehicles for lane segmentation by Mohab M. Eid Kishawy, Mohamed T. Abd El-Hafez, Retaj Yousri, M. Saeed Darweesh

“…However, one of the bottlenecks of this evolution is providing data that contains different scenarios and scenes to improve the models without exposing the privacy and security of the edge vehicles. …”
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Application of federated learning in predicting breast cancer by Chai Jiarui

“…Federated learning provides a framework to protect data privacy, allowing multiple institutions to share model training without sharing the original data. …”
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Examine frameworks policies and strategies for effective information governance in healthcare organizations. by Richard Okyere Boadu, Victor Wireko Adu, Kwame Adu Okyere Boadu, Baishatu Ibrahim, Prince Akey, Amponsah Amishadas Mensah, Godwin Adzakpah, Nathan Kumasenu Mensah

“…The majority of healthcare professionals were familiar with and advocated for adherence to regulatory requirements such as HIPAA (33.7%), GDPR (21.3%) and HITECH Act (14.4%), in making data governance much robust. Efforts were also identified in ensuring privacy and confidentiality during the storage, processing and transmission of patient data mostly by deploying methods such as authentication (58.9%), use of secured computers and software (71.2%) and using secure electronic platforms (66.0%) respectively indicating a keen attention for data stewardship and governance. …”
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Federated and ensemble learning framework with optimized feature selection for heart disease detection by Olfa Hrizi, Karim Gasmi, Abdulrahman Alyami, Adel Alkhalil, Ibrahim Alrashdi, Ali Alqazzaz, Lassaad Ben Ammar, Manel Mrabet, Alameen E.M. Abdalrahman, Samia Yahyaoui

“…To improve classification performance while protecting data privacy, this study investigated a combined method that uses ensemble learning, feature selection, and federated learning (FL). …”
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Addressing the Ethical, Legal, and Social Issues of Healthtech in Education: Insights From Japan by Motofumi Sumiya, Tomoko Nishimura, Kyoko Aizaki, Ikue Hirata, Nobuaki Tsukui, Yuko Osuka, Manabu Wakuta, Atsushi Senju

“…The study underscores the need for a multifaceted approach to mitigate risks such as data misuse, inequitable access, and algorithmic bias, ensuring the ethical and effective use of healthtech in education. …”
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Secure Federated Matrix Factorization via Device-to-Device Model Shuffling by Taisho Sasada, Md. Delwar Hossain, Yuzo Taenaka, Md. Mahbubur Rahman, Youki Kadobayashi

“…Location-Based Recommendation Systems (LBRS) use device location data to suggest nearby hotels, restaurants, and points of interest. …”
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Spatial-Temporal Cooperative In-Vehicle Network Intrusion Detection Method Based on Federated Learning by Liu Tao, Zhao Xiyang

“…This paper proposes a spatial-temporal collaborative intrusion detection method for IVN based on federated learning (FL), aiming to address the limitations of traditional intrusion detection methods in data privacy protection, temporal modeling, and computational efficiency. …”
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