Exact(14)
Sorias-Comas and DomingoFerrer in "Big Data Privacy: Challenges to Privacy Principles and Models," after a comprehensive overview of data privacy techniques, discuss the challenges that need to be addressed in order to apply and/or extend such techniques to address key challenges in big data privacy, namely composability, linkability, and low computational costs.
However, IoT presents several unique challenges that make the application of existing security and privacy techniques difficult.
The privacy techniques used in the surveyed systems are discussed and compared based on their effects on the performance and precision of the IDS.
However, such data may reveal sensitive information if no privacy techniques are applied.
In this section, several related works on cloud architectures, privacy techniques and cryptography are discussed.
In terms of healthcare services [59, 64 67] as well, more efficient privacy techniques need to be developed.
Similar(46)
Jiang, X. et al. A community assessment of privacy preserving techniques for human genomes.
It remains unclear how well existing privacy protection techniques can be effectively applied to large-scale human genomic data.
The proposed privacy preservation techniques utilise multiple IoT cloud data stores to protect the privacy of data collected from IoT.
This research proposes a multi-agent architecture coupled with privacy preserving techniques to facilitate data sharing while preserving privacy.
Experimental evaluations are also provided to validate the efficiency and performance outcomes of the proposed privacy preserving techniques and architecture.
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