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@article{177583,
        author = {Ramander Singh and Anshika Gupta and Vanshika Vashisth and Hemant Bhardawaj},
        title = {Theoretical Challenges in Privacy-Preserving Ubiquitous Computing Systems},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {823-826},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177583},
        abstract = {In today’s world, smart devices and interconnected systems constantlycollect and process personal data, making privacy a growing concern.Ubiquitous computing where technology seamlessly integrates into our surroundings raises critical questions about who controls this data and how it is protected. This research explores the theoretical challenges in ensuring privacy within these systems, focusing on data ownership, trust models, secure data sharing, and anonymization techniques. While methods like differential privacy, federated learning, and homomorphic encryption aim to safeguard user data, they come with challenges such as high computational costs, scalability issues, and regulatory complexities. Striking a balance between strong privacy measures and system efficiency remains a major hurdle. To bridge these gaps, future research must focus on hybrid privacy models, decentralized architectures, and AIdriven security solutions. Ethical and legal frameworks, such as GDPR and CCPA, also play a crucial role in shaping privacy standards. This study highlights the urgent need for scalable, real-time privacy solutions that protect users without compromising the functionality of ubiquitous computing systems[1].},
        keywords = {IoT, Privacy-preserving, Edge computing, Quantum computing, Artificial Intelligence},
        month = {May},
        }