Neutrosophic Logic for Secure Hand-Based Biometrics: Quantifying Privacy-Security Tradeoffs in Remote Authentication Systems by A. A. Salama, Abdelnasser Mohamed, Huda E. Khalid, Ahmed K. Essa, Doaa E. Mossa

“…To address this gap, we propose a vulnerability assessment framework grounded in neutrosophic logic [11], which evaluates system robustness through truth (T), indeterminacy (I), and falsity (F) membership functions, and this approach quantifies the trade-offs between security and privacy, revealing that hand-based biometrics achieve 92% security effectiveness (T = 0.8) while retaining an 18% uncertainty factor ( 𝐼 = 0.4 ) concerning potential vulnerabilities, and added analysis further identifies deficiencies in template protection (F = 0.2) and data transmission protocols, and we, proposed framework advances us the evaluation of biometric systems by using integrating neutrosophic uncertainty modeling, and it provides actionable insights for designing secure remote authentication architectures. …”
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A New Distributed User-Demand-Driven Location Privacy Protection Scheme for Mobile Communication Network by Jin Wang, Hao Wu, Yudian Liu

“…While obtaining convenient services, the exploitation of mass location data is inevitably leading to a serious concern about location privacy security. …”
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Ethics of Artificial Intelligence and Robotics: Key Issues and Modern Ways to Solve Them by N. Yadav

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Artificial Intelligence and Politics: Legal Dilemmas and Risks to Democracy by Daniele Battista, Gabriele Uva

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Artificial Intelligence and Politics: Legal Dilemmas and Risks to Democracy by Daniele Battista, Gabriele Uva

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Dynamic selectout and voting-based federated learning for enhanced medical image analysis by Saeed Iqbal, Adnan N Qureshi, Musaed Alhussein, Khursheed Aurangzeb, Atif Mahmood, Saaidal Razalli Bin Azzuhri

“…This strategy has a lot of potential to improve FL across a range of applications, especially those that prioritize data privacy, diversity, and performance.…”
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Vehicle Trajectory Generation Based on Generation Adversarial Network by Zhonghe He, Renchi Shao, Sijia Xiang

“…In this paper, the vehicle travel time of sample trajectory data and virtual trajectory data is used as indicators for statistical analysis. …”
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Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter by Andrew Lowy, Meisam Razaviyayn

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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

“…The rapidly evolving field of cloud-based data sharing faces critical challenges in ensuring comprehensive privacy protection and trust for both data producers and seekers. …”
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Federated Mental Wellbeing Assessment Using Smartphone Sensors Under Unreliable Participation by Gavryel Martis, Ryan McConville

“…The findings suggested that given the widespread use of such devices, FL holds great potential in mood and depression detection while protecting data privacy. …”
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A novel federated learning approach for IoT botnet intrusion detection using SHAP-based knowledge distillation by Md. Alamgir Hossain, Sadman Saif, Md. Saiful Islam

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Exploring the future of privacy-preserving heart disease prediction: a fully homomorphic encryption-driven logistic regression approach by Vankamamidi S. Naresh, Sivaranjani Reddi

“…Abstract Homomorphic Encryption (HE) offers a revolutionary cryptographic approach to safeguarding privacy in machine learning (ML), especially in processing sensitive healthcare data. …”
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Automation of Daily Access Data Recap of Employee Data Tables Using Apps Script to Detect Illegal Activities: by Jong Jek Siang, Rio Rian Rivanka, Argo Wibowo

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Cross-Company Data Sharing Using Distributed Analytics by Soo-Yon Kim, Stefanie Berninger, Max Kocher, Martin Perau, Sandra Geisler

“…Furthermore, we find that the framework supports integration of data quality assessment and privacy preservation mechanisms. …”
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UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework by Biyao Che, Zixiao Wang, Ying Chen, Liang Guo, Yuan Liu, Yuan Tian, Jizhuang Zhao

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Identification of hazardous road locations using ambulance data by Anne Vingaard Olesen, Tim Alex Lindskou, Rasmus Øhlenschlæger, Torben Anders Kløjgaard, Anders Brogaard Tallaksen, Jens Lauritsen, Erika Frischknecht Christensen, Harry Lahrmann

“…Results: Compared to police data in the same study period, we found 3.2 times as many unique crash sites through the use of combined hospital patient and ambulance data. …”
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Security and privacy in online teaching during the COVID-19 pandemic: experiences and concerns of academics in Saudi higher education by Basmah Almekhled, Helen Petrie

“…The findings provide several key insights: Key aspects of online privacy and security for Saudi HEI academics: Saudi HEI academic’s notion of online privacy and security is about the protection of personal data, preventing unauthorized access to data and ensuring the confidentiality and integrity of data. …”
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Old MacDonald and His Hackable Smartphone Application: A Security and Privacy Analysis of Android Agriculture Applications by Logan Mears, Rachel Donner, George Grispos

“…Despite the widespread use of smartphones among farmers increasing from 77% in 2021 to 82% in 2023, minimal research has examined the security and privacy implications of agricultural smartphone applications, potentially used on these devices. …”
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Collaborative and privacy-preserving cross-vendor united diagnostic imaging via server-rotating federated machine learning by Hao Wang, Xiaoyu Zhang, Xuebin Ren, Zheng Zhang, Shusen Yang, Chunfeng Lian, Jianhua Ma, Dong Zeng

“…Abstract Federated Learning (FL) is a distributed framework that enables collaborative training of a server model across medical data vendors while preserving data privacy. However, conventional FL faces two key challenges: substantial data heterogeneity among vendors and limited flexibility from a fixed server, leading to suboptimal performance in diagnostic-imaging tasks. …”
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Biometrics, e-Identity, and the Balance between Security and Privacy: Case Study of the Passenger Name Record (PNR) System by G. Nouskalis

“…The implementation of biometrics entails either the establishment of an identity or tracing a person's identity. Biometric passport data (e.g., irises, fingers, faces) can be used in order to verify a passenger's identity. …”
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