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Compressive sensing: From "Compressing while Sampling" to "Compressing and Securing while Sampling"
2010
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
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In this work, information theoretic analysis of real EEG signals is presented that shows the additional benefits of compressive sensing in preserving data privacy. ...
The sampled signal can subsequently be subjected to further processing leading to, for example, encryption and compression. ...
ACKNOWLEDGMENTS The authors would like to thank the National Society of Epilepsy UK for providing the EEG data. Authors would also like to thank Alexander J. Casson for his positive feedback. ...
doi:10.1109/iembs.2010.5627119
pmid:21096322
fatcat:2wfw2rscn5auhk6lavcmmbbpyu
Differential privacy with compression
2009
2009 IEEE International Symposium on Information Theory
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This work studies formal utility and privacy guarantees for a simple multiplicative database transformation, where the data are compressed by a random linear or affine transformation, reducing the number ...
of data records substantially, while preserving the number of original input variables. ...
In particular, we show how this randomized procedure can achieve a form of "differential privacy" [9, 8] , while at the same time showing that the compressed data can be used for Principal Component Analysis ...
doi:10.1109/isit.2009.5205863
dblp:conf/isit/ZhouLW09
fatcat:jdhe6tjs5vdbpnxjvlhr4fhlfm
Compressive analysis and the Future of Privacy
[article]
2020
arXiv
pre-print
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Compressive analysis is the name given to the family of techniques that map raw data to their smaller representation. ...
We examine the current technologies being implemented, and suggest the crucial advantages of compressive analysis. ...
For example, a set of monte carlo linear measurements (apropos to compressive sensing) from a wireless sensor network can be used instead of continuous values to ensure privacy preservation. ...
arXiv:2006.03835v1
fatcat:5cz2bvskdre5ngnq3untfxnw7i
Robust Digital Watermarking Scheme for Jpeg Images
2015
International Journal of Engineering Research and
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Index Terms-Compressive sensing, secure watermark detection, secure signal processing, secure multiparty computation, privacy preserving. I. ...
Privacy is one of the critical issue when the data storage are outsource by the data owners to a cloud, which is one of the third party computing service. ...
For privacy preserving datamining has also been proposed by using random matrix transformation, which proposed a technique for privacy preserving collaborative data-mining, which is a random projection ...
doi:10.17577/ijertv4is030205
fatcat:faq4idu3w5btlhsfdbv36vls5i
Differentially Private Data Publication with Multi-level Data Utility
[article]
2021
arXiv
pre-print
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Specifically, we resort to compressive sensing (CS) method to project a n-dimensional vector representation of users' data to a lower m-dimensional space, and then add deliberately designed noise to satisfy ...
In this paper, we address this challenge in proposing a novel framework of data publication with compressive sensing supporting multi-level utility-privacy tradeoffs, which provides differential privacy ...
sensing for different level of privacy preservation. ...
arXiv:2112.07061v1
fatcat:aek6c23ptbg53ckuk3zpcjdd7i
Compressed and Privacy-Sensitive Sparse Regression
2009
IEEE Transactions on Information Theory
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We characterize the number of projections that are required for -regularized compressed regression to identify the nonzero coefficients in the true model with probability approaching one, a property called ...
A primary motivation for this compression procedure is to anonymize the data and preserve privacy by revealing little information about the original data. ...
ACKNOWLEDGMENT The authors wish to thank Avrim Blum, Steve Fienberg, and Pradeep Ravikumar for helpful comments on this work. ...
doi:10.1109/tit.2008.2009605
fatcat:qqb4j5rtpfaltbxuhel3puy7au
A compressive multi-kernel method for privacy-preserving machine learning
[article]
2021
arXiv
pre-print
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Each kernel matrix is compressed with a lossy projection matrix derived from the Discriminant Component Analysis (DCA). ...
The results show that the compression regime is successful in privacy preservation as the privacy classification accuracies are almost at the random-guess level in all experiments. ...
CONCLUSION In addressing the challenge problem of privacy-preserving machine learning, this work is built upon two regimes -Compressive Privacy for privacy protection, and multi-kernel method for utility ...
arXiv:2106.10671v1
fatcat:lhvq7yz6jvdk3dnaked46uvur4
Compressive mechanism
2011
Proceedings of the 10th annual ACM workshop on Privacy in the electronic society - WPES '11
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2011 pre-print arXiv:1107.3350v1 fatcat:tualgs5i4ngsziip55vwwbqiaa
Compressive sensing is a decent theoretical tool for compact synopsis construction, using random projections. ...
This paper proposes the compressive mechanism, a novel solution on the basis of state-of-the-art compression technique, called compressive sensing. ...
To the best of our knowledge, we are the first to apply compressive sensing to sensitive data analysis. [48, 47, 32] apply random projections to differential privacy. ...
doi:10.1145/2046556.2046581
dblp:conf/wpes/LiZWY11
fatcat:omm6gloayrf37nl6caz3wprqe4
A Compressive Sensing Based Secure Watermark Detection and Privacy Preserving Storage Framework
2014
IEEE Transactions on Image Processing
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We then propose a compressive sensing (CS)-based framework using secure multiparty computation (MPC) protocols to address such a requirement. ...
In our framework, the multimedia data and secret watermark pattern are presented to the cloud for secure watermark detection in a CS domain to protect the privacy. ...
Earlier than the birth of the compressive sensing theory, random projection using the Johnson-Lindenstrauss Lemma [11] was also used for privacy preserving data-mining. ...
doi:10.1109/tip.2014.2298980
pmid:24723529
fatcat:u4r4dpv2sjh45lqfslkj4t6zlu
Random Projection and Its Applications
[article]
2017
arXiv
pre-print
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Random Projection is a foundational research topic that connects a bunch of machine learning algorithms under a similar mathematical basis. ...
It is used to reduce the dimensionality of the dataset by projecting the data points efficiently to a smaller dimensions while preserving the original relative distance between the data points. ...
For privacy analysis. two types of attacks are considered 1) The adversary tries to retrieve the exact values of the projected matrix X or Y, the authors proved that when m ≥ 2k − 1, even if matrix R is ...
arXiv:1710.03163v1
fatcat:jhzz6mkynjczhcwt4va67efpru
Differential Privacy with Compression
[article]
2009
arXiv
pre-print
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This work studies formal utility and privacy guarantees for a simple multiplicative database transformation, where the data are compressed by a random linear or affine transformation, reducing the number ...
of data records substantially, while preserving the number of original input variables. ...
We thank Avrim Blum and John Lafferty for helpful discussions. KL is supported in part by an NSF Graduate Research Fellowship. ...
arXiv:0901.1365v1
fatcat:f3rstm6vd5azdh4ntjigyqhfby
Compressive sensing based privacy for fall detection
[article]
2020
arXiv
pre-print
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Fall detection holds immense importance in the field of healthcare, where timely detection allows for instant medical assistance. ...
Ten action classes randomly selected from Kinetics-400 with no fall examples, are employed to train our 3D ConvNet post compressive sensing with different types of sensing matrices on the original video ...
In contrast to the aforementioned approaches, compressive sensing field suggests that a small group of linear projections of a compressible signal contains enough information for reconstruction, classification ...
arXiv:2001.03463v1
fatcat:hvgu32hipvau3b5bymtd3nuia4
Differential privacy in data publication and analysis
2012
Proceedings of the 2012 international conference on Management of Data - SIGMOD '12
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Since its proposal, differential privacy had been gaining attention in many fields of computer science, and is considered among the most promising paradigms for privacy-preserving data publication and ...
analysis. ...
Xiao [27] employ compressive sensing techniques to improve the accuracy of point queries on sparse data. ...
doi:10.1145/2213836.2213910
dblp:conf/sigmod/YangZMWX12
fatcat:uqrf46mpd5fqlgpmkjr3tp5g5y
Multi-level Reversible Data Anonymization via Compressive Sensing and Data Hiding
2020
IEEE Transactions on Information Forensics and Security
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The proposed privacy-preserving approach offers a low-cost multi-tier encryption system that provides different levels of reconstruction quality for different classes of users, e.g., semi-authorized, full-authorized ...
We propose a Compressive Sensing (CS) based data encryption that is capable of both obfuscating selected sensitive parts of documents and compressively sampling, hence encrypting both sensitive and non-sensitive ...
CONCLUSION We have presented a two-tiered (potentially, multi-tiered) privacy-preserving scheme based on compressive sensing theory. ...
doi:10.1109/tifs.2020.3026467
fatcat:rkkpewgtejgczmftznpltxkjju
A Perturbed Compressed Sensing Protocol for Crowd Sensing
2016
Mobile Information Systems
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Recently, Compressed Sensing (CS) is a booming theory which employs nonadaptive linear projections to reduce data quantity and then reconstructs the original signal. ...
Formally, we prove that our protocol is CPA-secure on the basis of a theorem. ...
Acknowledgments This work is supported by National Natural Science Foundation of China no. 61272512 and no. 61300177 and Beijing Natural Science Foundation no. 4132054. ...
doi:10.1155/2016/1763416
fatcat:hdhath4xcfhufnqvfgli7bjjqm
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