A Correlated Noise-assisted Decentralized Differentially Private Estimation Protocol, and its application to fMRI Source Separation.
A Correlated Noise-assisted Decentralized Differentially Private Estimation Protocol, and its application to fMRI Source Separation.
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DOI：
10.1109/tsp.2021.3126546
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发表时间：
2021
影响因子：
5.4
通讯作者：
Calhoun, Vince D.
中科院分区：
文献类型：
--
作者：
Imtiaz, Hafiz;Mohammadi, Jafar;Silva, Rogers;Baker, Bradley;Plis, Sergey M.;Sarwate, Anand D.;Calhoun, Vince D.
关键词：
Blind source separation algorithms such as independent component analysis (ICA) are widely used in the analysis of neuroimaging data. To leverage larger sample sizes, different data holders/sites may wish to collaboratively learn feature representations. However, such datasets are often privacy-sensitive, precluding centralized analyses that pool the data at one site. In this work, we propose a differentially private algorithm for performing ICA in a decentralized data setting. Due to the high dimension and small sample size, conventional approaches to decentralized differentially private algorithms suffer in terms of utility. When centralizing the data is not possible, we investigate the benefit of enabling limited collaboration in the form of generating jointly distributed random noise. We show that such (anti) correlated noise improves the privacy-utility trade-off, and can reach the same level of utility as the corresponding non-private algorithm for certain parameter choices. We validate this benefit using synthetic and real neuroimaging datasets. We conclude that it is possible to achieve meaningful utility while preserving privacy, even in complex signal processing systems.
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影响因子：
17.6
作者：
Calhoun VD;Adalı T
通讯作者：
Adalı T
影响因子：
4.8
作者：
Calhoun, VD;Adali, T;Pearlson, GD
通讯作者：
Pearlson, GD
影响因子：
7.7
作者：
Carter KW;Francis RW;Carter KW;Francis RW;Bresnahan M;Gissler M;Grønborg TK;Gross R;Gunnes N;Hammond G;Hornig M;Hultman CM;Huttunen J;Langridge A;Leonard H;Newman S;Parner ET;Petersson G;Reichenberg A;Sandin S;Schendel DE;Schalkwyk L;Sourander A;Steadman C;Stoltenberg C;Suominen A;Surén P;Susser E;Sylvester Vethanayagam A;Yusof Z;International Collaboration for Autism Registry Epidemiology
通讯作者：
International Collaboration for Autism Registry Epidemiology
影响因子：
6.3
作者：
BOLLERSLEV, T
通讯作者：
BOLLERSLEV, T
影响因子：
3.7
作者：
Calhoun VD;Potluru VK;Phlypo R;Silva RF;Pearlmutter BA;Caprihan A;Plis SM;Adalı T
通讯作者：
Adalı T