Information Fusion in Distributed Sensor Networks with Byzantines

2021 ◽  
Author(s):  
Andrea Abrardo ◽  
Mauro Barni ◽  
Kassem Kallas ◽  
Benedetta Tondi
2013 ◽  
Vol 433-435 ◽  
pp. 503-509
Author(s):  
Deok Jin Lee ◽  
Kil To Chong ◽  
Dong Pyo Hong

This paper represents a new multiple sensor information fusion algorithm in distributed sensor networks using an additive divided difference information filter for nonlinear estimation and tracking applications. The newly proposed multi-sensor fusion algorithm is derived by utilizing an efficient new additive divided difference filtering algorithm with embedding statistical error propagation method into an information filtering architecture. The new additive divided difference information filter achieves not only the accurate nonlinear estimation solution, but also the flexibility of multiple information fusion in distributed sensor networks. Performance comparison of the proposed filter with the nonlinear information filters is demonstrated through a target-tracking application.


2015 ◽  
Vol 11 (3) ◽  
pp. 231073 ◽  
Author(s):  
Javier Bajo ◽  
Juan F. De Paz ◽  
Gabriel Villarrubia ◽  
Juan M. Corchado

2005 ◽  
Vol 1 (3-4) ◽  
pp. 345-354 ◽  
Author(s):  
Dibyendu Chakrabarti ◽  
Subhamoy Maitra ◽  
Bimal Roy

Key pre-distribution is an important area of research in Distributed Sensor Networks (DSN). Two sensor nodes are considered connected for secure communication if they share one or more common secret key(s). It is important to analyse the largest subset of nodes in a DSN where each node is connected to every other node in that subset (i.e., the largest clique). This parameter (largest clique size) is important in terms of resiliency and capability towards efficient distributed computing in a DSN. In this paper, we concentrate on the schemes where the key pre-distribution strategies are based on transversal design and study the largest clique sizes. We show that merging of blocks to construct a node provides larger clique sizes than considering a block itself as a node in a transversal design.


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