A data‐based private learning framework for enhanced security against replay attacks in cyber‐physical systems
Summary This article develops a data‐based and private learning framework of the detection and mitigation against replay attacks for cyber‐physical systems. Optimal watermarking signals are added to assist in the detection of potential replay attacks. In order to improve the confidentiality of the o...
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| Published in | International journal of robust and nonlinear control Vol. 31; no. 6; pp. 1817 - 1833 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Bognor Regis
Wiley Subscription Services, Inc
01.04.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1049-8923 1099-1239 |
| DOI | 10.1002/rnc.5040 |
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| Abstract | Summary
This article develops a data‐based and private learning framework of the detection and mitigation against replay attacks for cyber‐physical systems. Optimal watermarking signals are added to assist in the detection of potential replay attacks. In order to improve the confidentiality of the output data, we first add a level of differential privacy. We then use a data‐based technique to learn the best defending strategy in the presence of worst case disturbances, stochastic noise, and replay attacks. A data‐based Neyman‐Pearson detector design is also proposed to identify replay attacks. Finally, simulation results show the efficacy of the proposed approach along with a comparison of our data‐based technique to a model‐based
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| AbstractList | Summary
This article develops a data‐based and private learning framework of the detection and mitigation against replay attacks for cyber‐physical systems. Optimal watermarking signals are added to assist in the detection of potential replay attacks. In order to improve the confidentiality of the output data, we first add a level of differential privacy. We then use a data‐based technique to learn the best defending strategy in the presence of worst case disturbances, stochastic noise, and replay attacks. A data‐based Neyman‐Pearson detector design is also proposed to identify replay attacks. Finally, simulation results show the efficacy of the proposed approach along with a comparison of our data‐based technique to a model‐based
one. This article develops a data‐based and private learning framework of the detection and mitigation against replay attacks for cyber‐physical systems. Optimal watermarking signals are added to assist in the detection of potential replay attacks. In order to improve the confidentiality of the output data, we first add a level of differential privacy. We then use a data‐based technique to learn the best defending strategy in the presence of worst case disturbances, stochastic noise, and replay attacks. A data‐based Neyman‐Pearson detector design is also proposed to identify replay attacks. Finally, simulation results show the efficacy of the proposed approach along with a comparison of our data‐based technique to a model‐based one. |
| Author | Zhai, Lijing Vamvoudakis, Kyriakos G. |
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| Cites_doi | 10.1109/SSCI.2017.8285298 10.1109/TAC.2013.2283096 10.1109/CDC.2017.8264421 10.1007/978-3-319-78384-0 10.1109/TAC.2014.2351671 10.1109/MCS.2012.2214134 10.1109/MSP.2011.67 10.1109/TDSC.2015.2509994 10.1109/ALLERTON.2009.5394956 10.1109/TSG.2017.2703842 10.1109/TCST.2013.2280899 10.1109/MCS.2014.2364724 10.1109/ComManTel.2013.6482409 10.1109/ACC.2015.7172127 10.1002/9781118122631 10.1109/MNET.2016.7437026 10.1109/CDC.1995.478953 10.1109/ACC.2016.7524930 10.1109/SmartGridComm.2017.8340720 10.1002/apmc.1988.051620106 10.1145/2976749.2978388 10.1049/PBCE081E 10.1145/2046684.2046692 10.23919/ACC.2018.8431397 10.1109/MCS.2016.2621461 10.1109/TAC.2013.2266831 10.1109/ARES.2016.2 10.1007/11761679_29 10.1109/ASCC.2017.8287297 10.1145/1128817.1128824 10.1109/CDC.2018.8619632 10.1109/IECON.2011.6120048 10.1016/j.ins.2018.12.091 10.1016/j.ifacol.2017.08.1502 10.1002/9781119174882 10.1109/JPROC.2016.2575064 10.1109/MCS.2014.2364709 10.1109/ACC.2015.7170734 10.1109/TSMCB.2006.880135 |
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| References | 2015; 35 2017; 8 2017; 4 2012 2011 2009 2016; 30 1974 1995 2006 1992; 15 1991 2019; 481 2012; 32 2014; 22 2018; 48 2006; 4052 2007; 37 2011; 9 2017; 50 2013; 58 2017; 37 2014; 59 2018 2017 2016 2015 2013 2018; 15 2017; 105 Werbos PJ (e_1_2_9_12_1) 1992; 15 e_1_2_9_30_1 e_1_2_9_31_1 e_1_2_9_11_1 Dwork C (e_1_2_9_32_1) 2006 e_1_2_9_34_1 e_1_2_9_10_1 e_1_2_9_35_1 e_1_2_9_13_1 e_1_2_9_33_1 Humayed A (e_1_2_9_19_1) 2017; 4 e_1_2_9_15_1 e_1_2_9_14_1 e_1_2_9_17_1 e_1_2_9_36_1 e_1_2_9_16_1 e_1_2_9_37_1 e_1_2_9_18_1 Scharf LL (e_1_2_9_39_1) 1991 e_1_2_9_41_1 e_1_2_9_42_1 e_1_2_9_20_1 e_1_2_9_40_1 e_1_2_9_22_1 e_1_2_9_45_1 e_1_2_9_21_1 e_1_2_9_46_1 e_1_2_9_24_1 e_1_2_9_43_1 e_1_2_9_23_1 e_1_2_9_44_1 e_1_2_9_8_1 e_1_2_9_7_1 e_1_2_9_6_1 Anderson BDO (e_1_2_9_38_1) 2012 e_1_2_9_5_1 e_1_2_9_4_1 e_1_2_9_3_1 e_1_2_9_2_1 Liu H (e_1_2_9_27_1) 2018; 48 e_1_2_9_9_1 e_1_2_9_26_1 e_1_2_9_25_1 e_1_2_9_28_1 e_1_2_9_47_1 e_1_2_9_29_1 |
| References_xml | – year: 2011 – volume: 50 start-page: 7363 issue: 1 year: 2017 end-page: 7368 article-title: Detection and isolation of replay attacks through sensor watermarking publication-title: IFAC‐PapersOnLine – year: 2009 – volume: 37 start-page: 33 issue: 1 year: 2017 end-page: 52 article-title: Game theory‐based control system algorithms with real‐time reinforcement learning: how to solve multiplayer games online publication-title: IEEE Control Syst Mag – volume: 4 start-page: 1802 issue: 6 year: 2017 end-page: 1831 article-title: Cyber‐physical systems security–a survey publication-title: IEEE IoT J – volume: 35 start-page: 93 issue: 1 year: 2015 end-page: 109 article-title: Physical authentication of control systems: Designing watermarked control inputs to detect counterfeit sensor outputs publication-title: IEEE Control Syst Mag – volume: 32 start-page: 76 issue: 6 year: 2012 end-page: 105 article-title: Reinforcement learning and feedback control: using natural decision methods to design optimal adaptive controllers publication-title: IEEE Control Syst – volume: 35 start-page: 24 issue: 1 year: 2015 end-page: 45 article-title: Secure control systems: a quantitative risk management approach publication-title: IEEE Control Syst Mag – volume: 48 start-page: 1977 issue: 7 year: 2018 end-page: 1988 article-title: An on‐line design of physical watermarks publication-title: IEEE Trans Cybern – volume: 4052 start-page: 1 year: 2006 end-page: 12 – volume: 59 start-page: 341 issue: 2 year: 2014 end-page: 354 article-title: Differentially private filtering publication-title: IEEE Trans Automat Control – volume: 22 start-page: 1396 issue: 4 year: 2014 end-page: 1407 article-title: Detecting integrity attacks on SCADA systems publication-title: IEEE Trans Control Syst Tech – year: 2016 – year: 2018 – year: 2012 – volume: 105 start-page: 219 issue: 2 year: 2017 end-page: 240 article-title: Dynamic watermarking: active defense of networked cyber–physical systems publication-title: Proc IEEE – volume: 15 start-page: 493 year: 1992 end-page: 525 article-title: Approximate dynamic programming for real‐time control and neural modeling publication-title: Handbook Intell Control Neural fuzzy Adapt Approach – year: 2006 – volume: 9 start-page: 49 issue: 3 year: 2011 end-page: 51 article-title: Stuxnet: dissecting a cyberwarfare weapon publication-title: IEEE Sec Privacy – year: 1995 – year: 1974 – volume: 37 start-page: 240 issue: 1 year: 2007 end-page: 247 article-title: Adaptive critic designs for discrete‐time zero‐sum games with application to control publication-title: IEEE Trans Syst Man Cybern Part B (Cybern) – volume: 59 start-page: 3209 issue: 12 year: 2014 end-page: 3223 article-title: Detection in adversarial environments publication-title: IEEE Trans Automat Control – volume: 58 start-page: 2715 issue: 11 year: 2013 end-page: 2729 article-title: Attack detection and identification in cyber‐physical systems publication-title: IEEE Trans Automat Control – volume: 8 start-page: 2505 issue: 5 year: 2017 end-page: 2516 article-title: Real‐time detection of false data injection attacks in smart grid: a deep learning‐based intelligent mechanism publication-title: IEEE Trans Smart Grid – volume: 30 start-page: 62 issue: 2 year: 2016 end-page: 66 article-title: Privacy and performance trade‐off in cyber‐physical systems publication-title: IEEE Netw – year: 2017 – year: 1991 – year: 2015 – volume: 481 start-page: 432 year: 2019 end-page: 444 article-title: Stochastic coding detection scheme in cyber‐physical systems against replay attack publication-title: Inf Sci – volume: 15 start-page: 2 issue: 1 year: 2018 end-page: 13 article-title: A systems theoretic approach to the security threats in cyber physical systems applied to stuxnet publication-title: IEEE Trans Depend Sec Comput – year: 2013 – ident: e_1_2_9_17_1 doi: 10.1109/SSCI.2017.8285298 – ident: e_1_2_9_34_1 doi: 10.1109/TAC.2013.2283096 – ident: e_1_2_9_28_1 doi: 10.1109/CDC.2017.8264421 – ident: e_1_2_9_15_1 doi: 10.1007/978-3-319-78384-0 – ident: e_1_2_9_4_1 doi: 10.1109/TAC.2014.2351671 – ident: e_1_2_9_13_1 doi: 10.1109/MCS.2012.2214134 – ident: e_1_2_9_7_1 doi: 10.1109/MSP.2011.67 – ident: e_1_2_9_6_1 doi: 10.1109/TDSC.2015.2509994 – ident: e_1_2_9_24_1 doi: 10.1109/ALLERTON.2009.5394956 – ident: e_1_2_9_18_1 doi: 10.1109/TSG.2017.2703842 – ident: e_1_2_9_25_1 doi: 10.1109/TCST.2013.2280899 – ident: e_1_2_9_45_1 doi: 10.1109/MCS.2014.2364724 – ident: e_1_2_9_41_1 doi: 10.1109/ComManTel.2013.6482409 – ident: e_1_2_9_11_1 doi: 10.1109/ACC.2015.7172127 – volume: 15 start-page: 493 year: 1992 ident: e_1_2_9_12_1 article-title: Approximate dynamic programming for real‐time control and neural modeling publication-title: Handbook Intell Control Neural fuzzy Adapt Approach – ident: e_1_2_9_9_1 doi: 10.1002/9781118122631 – ident: e_1_2_9_2_1 doi: 10.1109/MNET.2016.7437026 – ident: e_1_2_9_10_1 doi: 10.1109/CDC.1995.478953 – ident: e_1_2_9_29_1 doi: 10.1109/ACC.2016.7524930 – ident: e_1_2_9_31_1 doi: 10.1109/SmartGridComm.2017.8340720 – ident: e_1_2_9_36_1 doi: 10.1002/apmc.1988.051620106 – ident: e_1_2_9_5_1 doi: 10.1145/2976749.2978388 – ident: e_1_2_9_14_1 doi: 10.1049/PBCE081E – ident: e_1_2_9_20_1 doi: 10.1145/2046684.2046692 – ident: e_1_2_9_35_1 doi: 10.23919/ACC.2018.8431397 – ident: e_1_2_9_16_1 doi: 10.1109/MCS.2016.2621461 – ident: e_1_2_9_22_1 doi: 10.1109/TAC.2013.2266831 – volume-title: Statistical Signal Processing: Detection, Estimation, and Time Series Analysis year: 1991 ident: e_1_2_9_39_1 – start-page: 1 volume-title: Differential Privacy. In: Lecture Notes in Computer Science year: 2006 ident: e_1_2_9_32_1 – ident: e_1_2_9_26_1 doi: 10.1109/ARES.2016.2 – ident: e_1_2_9_33_1 doi: 10.1007/11761679_29 – ident: e_1_2_9_44_1 doi: 10.1109/ASCC.2017.8287297 – ident: e_1_2_9_21_1 doi: 10.1145/1128817.1128824 – volume-title: Optimal Filtering year: 2012 ident: e_1_2_9_38_1 – ident: e_1_2_9_40_1 doi: 10.1109/CDC.2018.8619632 – ident: e_1_2_9_8_1 doi: 10.1109/IECON.2011.6120048 – ident: e_1_2_9_43_1 doi: 10.1016/j.ins.2018.12.091 – volume: 48 start-page: 1977 issue: 7 year: 2018 ident: e_1_2_9_27_1 article-title: An on‐line design of physical watermarks publication-title: IEEE Trans Cybern – ident: e_1_2_9_42_1 doi: 10.1016/j.ifacol.2017.08.1502 – ident: e_1_2_9_37_1 – ident: e_1_2_9_47_1 doi: 10.1002/9781119174882 – ident: e_1_2_9_30_1 doi: 10.1109/JPROC.2016.2575064 – ident: e_1_2_9_3_1 doi: 10.1109/MCS.2014.2364709 – ident: e_1_2_9_23_1 doi: 10.1109/ACC.2015.7170734 – volume: 4 start-page: 1802 issue: 6 year: 2017 ident: e_1_2_9_19_1 article-title: Cyber‐physical systems security–a survey publication-title: IEEE IoT J – ident: e_1_2_9_46_1 doi: 10.1109/TSMCB.2006.880135 |
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This article develops a data‐based and private learning framework of the detection and mitigation against replay attacks for cyber‐physical systems.... This article develops a data‐based and private learning framework of the detection and mitigation against replay attacks for cyber‐physical systems. Optimal... |
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| Title | A data‐based private learning framework for enhanced security against replay attacks in cyber‐physical systems |
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