Ordinal Data Stream Collection with Condensed Local Differential Privacy

He, Yuanyuan; Wang, Fayao; Deng, Xianjun; Ni, Jianbing; Feng, Jun; Liu, Shenghao

doi:10.1109/hpcc-dss-smartcity-dependsys57074.2022.00102

2022 IEEE 24th Int Conf on High Performance Computing &Amp; Communications; 8th Int Conf on Data Science &Amp; Systems; 20th In 2022

DOI: 10.1109/hpcc-dss-smartcity-dependsys57074.2022.00102

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Ordinal Data Stream Collection with Condensed Local Differential Privacy

Yuanyuan He

Fayao Wang

Xianjun Deng

et al.

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Cited by 2 publications

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Continuous release of temporal correlation location statistics with local differential privacy

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Pervasive User Data Collection from Cyberspace: Privacy Concerns and Countermeasures

Jiang,

Rezazadeh Baee,

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et al. 2024

Cryptography

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The increasing use of technologies, particularly computing and communication paradigms, has significantly influenced our daily lives. Interconnecting devices and networks provides convenient platforms for information exchange and facilitates pervasive user data collection. This new environment presents serious privacy challenges. User activities can be continuously monitored in both digital and physical realms. Gathered data can be aggregated and analysed, revealing aspects of user behaviour that may not be apparent from a single data point. The very items that facilitate connectivity simultaneously increase the risk of privacy breaches. The data gathered to provide services can also be used for monitoring and surveillance. This paper discerns three novel categories of privacy concerns relating to pervasive user data collection: privacy and user activity in cyberspace, privacy in personal cyber–physical systems, and privacy in proactive user-driven data collection. We emphasise the primary challenges, ranging from identity tracking in browsing histories to intricate issues in opportunistic networks, situating each within practical, real-world scenarios. Furthermore, we assess the effectiveness of current countermeasures, investigating their strengths and limitations. This paper explores the challenges in preserving privacy in user interactions with dynamic interconnected systems and suggests countermeasures to mitigate identified privacy risks.

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Ordinal Data Stream Collection with Condensed Local Differential Privacy

Cited by 2 publications

References 31 publications

Continuous release of temporal correlation location statistics with local differential privacy

Continuous release of temporal correlation location statistics with local differential privacy

Pervasive User Data Collection from Cyberspace: Privacy Concerns and Countermeasures

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