Secure detection : performance metric and sensor deployment strategy
This paper studies how to deploy sensors in the context of detection in adversarial environments. A fusion center is performing a binary hypothesis testing based on measurements from remotely deployed heterogeneous sensors. An attacker may compromise some of the deployed sensors, which send arbitrar...
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sg-ntu-dr.10356-1394432020-05-19T08:24:53Z Secure detection : performance metric and sensor deployment strategy Ren, Xiaoqiang Mo, Yilin School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Secure Detection Byzantine Attacks This paper studies how to deploy sensors in the context of detection in adversarial environments. A fusion center is performing a binary hypothesis testing based on measurements from remotely deployed heterogeneous sensors. An attacker may compromise some of the deployed sensors, which send arbitrary measurements to the fusion center. The problems of interest are: to characterize the performance of the system under attack and, thus, develop a performance metric; and to deploy sensors within a cost budget, such that the proposed performance metric is maximized. In this paper, we first present a performance metric by formulating the detection in adversarial environments in a game theoretic way. A Nash equilibrium pair of the detection algorithm and attack strategy, with the deployed sensors given, is provided and the corresponding detection performance is adopted as the performance metric. We then show that the optimal sensor deployment can be determined approximately by solving a group of unbounded knapsack problems. We also show that the performance metric gap between the optimal sensor deployment and the optimal one with sensors being identical is within a fixed constant for any cost budget. The main results are illustrated by numerical examples. MOE (Min. of Education, S’pore) 2020-05-19T08:24:53Z 2020-05-19T08:24:53Z 2018 Journal Article Ren, X., & Mo, Y. (2018). Secure detection : performance metric and sensor deployment strategy. IEEE Transactions on Signal Processing, 66(17), 4450-4460. doi:10.1109/tsp.2018.285311 1053-587X https://hdl.handle.net/10356/139443 10.1109/TSP.2018.2853110 2-s2.0-85049444227 17 66 4450 4460 en IEEE Transactions on Signal Processing © 2018 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering Secure Detection Byzantine Attacks Ren, Xiaoqiang Mo, Yilin Secure detection : performance metric and sensor deployment strategy |
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This paper studies how to deploy sensors in the context of detection in adversarial environments. A fusion center is performing a binary hypothesis testing based on measurements from remotely deployed heterogeneous sensors. An attacker may compromise some of the deployed sensors, which send arbitrary measurements to the fusion center. The problems of interest are: to characterize the performance of the system under attack and, thus, develop a performance metric; and to deploy sensors within a cost budget, such that the proposed performance metric is maximized. In this paper, we first present a performance metric by formulating the detection in adversarial environments in a game theoretic way. A Nash equilibrium pair of the detection algorithm and attack strategy, with the deployed sensors given, is provided and the corresponding detection performance is adopted as the performance metric. We then show that the optimal sensor deployment can be determined approximately by solving a group of unbounded knapsack problems. We also show that the performance metric gap between the optimal sensor deployment and the optimal one with sensors being identical is within a fixed constant for any cost budget. The main results are illustrated by numerical examples. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Ren, Xiaoqiang Mo, Yilin |
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Article |
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Ren, Xiaoqiang Mo, Yilin |
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Ren, Xiaoqiang |
title |
Secure detection : performance metric and sensor deployment strategy |
title_short |
Secure detection : performance metric and sensor deployment strategy |
title_full |
Secure detection : performance metric and sensor deployment strategy |
title_fullStr |
Secure detection : performance metric and sensor deployment strategy |
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Secure detection : performance metric and sensor deployment strategy |
title_sort |
secure detection : performance metric and sensor deployment strategy |
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2020 |
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https://hdl.handle.net/10356/139443 |
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