Security Analysis of Quantized Bayesian Estimators
I Shames, Farhad Farokhi, Daniel Selvaratnam
23rd International Symposium on Mathematical Theory of Networks and Systems | Hong Kong University of Science and Technology | Published : 2018
Security of networked Bayesian source localization algorithms is analysed in this paper. The Bayesian estimators construct the probability density function of the location of the source from quantised measurements. Understanding fundamental limits in the performance of an adversary for manipulating the posterior of the Bayesian estimator is the main focus of the paper. The analysis is performed for cases where the estimator is not aware of the presence of the adversary. The results are then generalized to the case where the estimator is aware of the attacker.
The work of F. Farokhi was supported by the McKenzie Fellowship from the University of Melbourne, the VESKI Fellowship from the Victorian State Government, and a grant (MyIP: ID6874) from Defence Science and Technology Group (DSTG). The work of D. Selvaratnam and I. Shames was supported by a grant (MyIP: ID6874) from Defence Science and Technology Group (DSTG). D. Selvaratnam is further supported by a PhD scholarship from the University of Melbourne.