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Articles 1 - 3 of 3
Full-Text Articles in Computer Engineering
Boundary Regulation Processes And Privacy Concerns With (Non-)Use Of Voice-Based Assistants, Jessica Vitak, Priya C. Kumar, Yuting Liao, Michael Zimmer
Boundary Regulation Processes And Privacy Concerns With (Non-)Use Of Voice-Based Assistants, Jessica Vitak, Priya C. Kumar, Yuting Liao, Michael Zimmer
Human-Machine Communication
An exemplar of human-machine communication, voice-based assistants (VBAs) embedded in smartphones and smart speakers simplify everyday tasks while collecting significant data about users and their environment. In recent years, devices using VBAs have continued to add new features and collect more data—in potentially invasive ways. Using Communication Privacy Management theory as a guiding framework, we analyze data from 11 focus groups with 65 US adult VBA users and nonusers. Findings highlight differences in attitudes and concerns toward VBAs broadly and provide insights into how attitudes are influenced by device features. We conclude with considerations for how to address boundary regulation …
Domain Specific Analysis Of Privacy Practices And Concerns In The Mobile Application Market, Fahimeh Ebrahimi Meymand
Domain Specific Analysis Of Privacy Practices And Concerns In The Mobile Application Market, Fahimeh Ebrahimi Meymand
LSU Doctoral Dissertations
Mobile applications (apps) constantly demand access to sensitive user information in exchange for more personalized services. These-mostly unjustified-data collection tactics have raised major privacy concerns among mobile app users. Existing research on mobile app privacy aims to identify these concerns, expose apps with malicious data collection practices, assess the quality of apps' privacy policies, and propose automated solutions for privacy leak detection and prevention. However, existing solutions are generic, frequently missing the contextual characteristics of different application domains. To address these limitations, in this dissertation, we study privacy in the app store at a domain level. Our objective is to …
An Optimized And Scalable Blockchain-Based Distributed Learning Platform For Consumer Iot, Zhaocheng Wang, Xueying Liu, Xinming Shao, Abdullah Alghamdi, Md. Shirajum Munir, Sujit Biswas
An Optimized And Scalable Blockchain-Based Distributed Learning Platform For Consumer Iot, Zhaocheng Wang, Xueying Liu, Xinming Shao, Abdullah Alghamdi, Md. Shirajum Munir, Sujit Biswas
School of Cybersecurity Faculty Publications
Consumer Internet of Things (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem, like a smart home. Due to security and privacy concerns, blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their machine learning (ML) models using end-user data. Federated learning (FL) uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralized aggregator to safeguard the ecosystem. However, blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research introduces a novel architecture, emphasizing …