Belief Consensus and Distributed Hypothesis Testing in Sensor Networks

2006 ◽  
pp. 169-182 ◽  
Author(s):  
Reza Olfati-Saber ◽  
Elisa Franco ◽  
Emilio Frazzoli ◽  
Je. S. Shamma
Keyword(s):  
Sensor Networks ◽  
Hypothesis Testing ◽  
Distributed Hypothesis Testing

scholarly journals Distributed Hypothesis Testing with Privacy Constraints

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 478 ◽  
Author(s):  
Atefeh Gilani ◽  
Selma Belhadj Amor ◽  
Sadaf Salehkalaibar ◽  
Vincent Y. F. Tan
Keyword(s):  
Information Theory ◽  
Hypothesis Testing ◽  
Alternative Hypothesis ◽  
Side Information ◽  
Approximate Expression ◽  
Type Ii ◽  
Strong Converse ◽  
Privacy Constraints ◽  
Distributed Hypothesis Testing ◽  
Privacy Level

We revisit the distributed hypothesis testing (or hypothesis testing with communication constraints) problem from the viewpoint of privacy. Instead of observing the raw data directly, the transmitter observes a sanitized or randomized version of it. We impose an upper bound on the mutual information between the raw and randomized data. Under this scenario, the receiver, which is also provided with side information, is required to make a decision on whether the null or alternative hypothesis is in effect. We first provide a general lower bound on the type-II exponent for an arbitrary pair of hypotheses. Next, we show that if the distribution under the alternative hypothesis is the product of the marginals of the distribution under the null (i.e., testing against independence), then the exponent is known exactly. Moreover, we show that the strong converse property holds. Using ideas from Euclidean information theory, we also provide an approximate expression for the exponent when the communication rate is low and the privacy level is high. Finally, we illustrate our results with a binary and a Gaussian example.

scholarly journals Social Learning and Distributed Hypothesis Testing

2018 ◽  
Vol 64 (9) ◽  
pp. 6161-6179 ◽  
Author(s):  
Anusha Lalitha ◽  
Tara Javidi ◽  
Anand D. Sarwate
Keyword(s):  
Social Learning ◽  
Hypothesis Testing ◽  
Distributed Hypothesis Testing
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