Privacy in Internet of Things: From Principles to Technologies
Open accessAbstract
Ubiquitous deployment of low-cost smart devices and widespread use of high-speed wireless networks have led to the rapid development of the Internet of Things (IoT). IoT embraces countless physical objects that have not been involved in the traditional Internet and enables their interaction and cooperation to provide a wide range of IoT applications. Many services in the IoT may require a comprehensive understanding and analysis of data collected through a large number of physical devices that challenges both personal information privacy and the development of IoT. Information privacy in IoT is a broad and complex concept as its understanding and perception differ among individuals and its enforcement requires efforts from both legislation as well as technologies. In this paper, we review the state-of-the-art principles of privacy laws, the architectures for IoT and the representative privacy enhancing technologies (PETs). We analyze how legal principles can be supported through a careful implementation of PETs at various layers of a layered IoT architecture model to meet the privacy requirements of the individuals interacting with IoT systems. We demonstrate how privacy legislation maps to privacy principles which in turn drives the design of necessary PETs to be employed in the IoT architecture stack.
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The personal information protection law is not specific and systematic, and the legal constraints are loose.
“The personal information protection law is not specific and systematic, and the legal constraints are loose [114].”
From A Survey of IoT Privacy Security: Architecture, Technology, Challenges, and Trends (2024) · cites this paper as [114]
The Legislation section (p. 2) says the United States lacks general information-privacy legislation covering all states and areas, and that OECD privacy guidelines were nonbinding. Those points support a narrower concern about gaps and weak constraints, but the paper does not characterize personal-information protection law generally as unspecific or unsystematic; it also describes comprehensive, enforceable EU privacy laws. (LLM, conf=0.83)
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IoT Privacy Protection: JPEG-TPE With Lower File Size Expansion and Lossless Decryption
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A survey on security issues of 5G NR: Perspective of artificial dust and artificial rain
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Exploiting Size-Compatible-Match Block Technique for Arbitrary-Size Thumbnail-Preserving Encryption
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Privacy-Enhanced MQTT Protocol for Massive IoT
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A Review on Malware Analysis for IoT and Android System
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Few-Shot Class-Incremental Learning With Non-IID Decentralized Data
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Design of SW Framework for Trustworthy AI-Data Commons
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On Convergence Probability of Direct Acyclic Graph-Based Ledgers in Forking Blockchain Systems
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Lattice-Based Semantic-Aware Searchable Encryption for Internet of Things
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Novel authentication framework for securing communication in internet-of-things
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Reference Architectures for Security-by-Design IoT: Comparative Study
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Design and Implementation of a Mobile-Controlled IoT Smart Pet Feeder for Busy Pet Owners
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A Novel User Behavior Modeling Scheme for Edge Devices with Dynamic Privacy Budget Allocation
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Privacy Concerns In IoT A Deeper Insight into Privacy Concerns in IoT Based Healthcare
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Privacy Design Strategies and the GDPR: A Systematic Literature Review
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Enhancing Privacy Preservation in Speech Data Publishing
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What are your privacy risks? Privacy risk assessment based on privacy policies analysis
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Enabling privacy by anonymization in the collection of similar data in multi-domain IoT
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On State Transition Probability and Performance of Direct Acyclic Graph Based Ledgers
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Performance Analysis of Direct Acyclic Graph-Based Ledgers in Low-to-High Load Regime
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Open Challenges in Internet of Things Security
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Blockchain With the Internet of Things
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- Authors
- Li, C., & Palanisamy, B.
- Affiliations
- University of Pittsburgh (US)
- Venue
- IEEE Internet of Things Journal
- Published
- 2019-02
- Volume
- 6
- Issue
- 1
- Pages
- 488-505
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W2885623796
- Cited by
- 130
- References
- 175
- Citations by year
- 2026: 6 · 2025: 14 · 2024: 20 · 2023: 20 · 2022: 15 · 2021: 24 · 2020: 21 · 2019: 10
- FWCI
- 7.74
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- D-Scholarship@Pitt (University of Pittsburgh) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- Internet of Things, privacy, privacy-enhancing technologies, privacy law, privacy principles, IoT architecture, data privacy, data protection
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