Analysis of Cyber Security Attacks and Its Solutions for the Smart grid Using Machine Learning and Blockchain Methods
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receivin...
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| Vydáno v: | Future internet Ročník 15; číslo 2; s. 83 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Basel
MDPI AG
01.02.2023
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| ISSN: | 1999-5903, 1999-5903 |
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| Abstract | Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receiving data packets over the network. Cyberattacks can compromise the smart grid’s dependability, availability, and privacy. Users, the communication network of smart devices and sensors, and network administrators are the three layers of an innovative grid network vulnerable to cyberattacks. In this study, we look at the many risks and flaws that can affect the safety of critical, innovative grid network components. Then, to protect against these dangers, we offer security solutions using different methods. We also provide recommendations for reducing the chance that these three categories of cyberattacks may occur. |
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| AbstractList | Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receiving data packets over the network. Cyberattacks can compromise the smart grid’s dependability, availability, and privacy. Users, the communication network of smart devices and sensors, and network administrators are the three layers of an innovative grid network vulnerable to cyberattacks. In this study, we look at the many risks and flaws that can affect the safety of critical, innovative grid network components. Then, to protect against these dangers, we offer security solutions using different methods. We also provide recommendations for reducing the chance that these three categories of cyberattacks may occur. |
| Audience | Academic |
| Author | Irfan, Hafiz Muhammad Khan, Sunawar Iqbal, Muhammad Mazhar, Tehseen Haq, Inayatul Hamam, Habib Ullah, Inam |
| Author_xml | – sequence: 1 givenname: Tehseen orcidid: 0000-0002-4649-2376 surname: Mazhar fullname: Mazhar, Tehseen – sequence: 2 givenname: Hafiz Muhammad surname: Irfan fullname: Irfan, Hafiz Muhammad – sequence: 3 givenname: Sunawar surname: Khan fullname: Khan, Sunawar – sequence: 4 givenname: Inayatul orcidid: 0000-0001-7073-733X surname: Haq fullname: Haq, Inayatul – sequence: 5 givenname: Inam surname: Ullah fullname: Ullah, Inam – sequence: 6 givenname: Muhammad surname: Iqbal fullname: Iqbal, Muhammad – sequence: 7 givenname: Habib orcidid: 0000-0002-5320-1012 surname: Hamam fullname: Hamam, Habib |
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| Cites_doi | 10.1109/JSEN.2021.3055778 10.3390/s21238087 10.14236/ewic/icscsr19.16 10.1109/78.650098 10.1109/JIOT.2020.2993601 10.3390/bdcc4010001 10.1186/s40537-020-00379-6 10.1109/JIOT.2021.3128646 10.1007/s11227-020-03600-8 10.1109/TSG.2017.2786668 10.4236/cn.2022.144009 10.1109/TNSE.2021.3135565 10.1155/2022/3151249 10.1016/j.energy.2021.122713 10.1109/TII.2022.3149106 10.3390/electronics6010005 10.1109/ISGT-Europe47291.2020.9248779 10.1186/s40537-019-0211-6 10.1109/INFOCOM42981.2021.9488823 10.1016/j.ijcip.2022.100547 10.1109/BLOC.2019.8751268 10.1016/j.ijhydene.2021.10.027 10.3390/en16010347 10.1016/j.jobe.2022.104323 10.1016/j.rser.2021.111530 10.3390/sym13010004 10.1109/ACCESS.2021.3094024 10.1049/iet-cps.2016.0019 10.1016/j.energy.2020.117417 10.3390/en12173310 10.3390/en16020635 10.1109/AIIoT54504.2022.9817309 10.1109/RAIT.2018.8389037 10.1109/SoutheastCon45413.2021.9401940 10.1109/ACCESS.2020.3026180 10.1016/j.ijcip.2022.100542 10.1109/ACCESS.2018.2836950 10.23919/WAC55640.2022.9934344 10.1109/MSCPES.2019.8738801 10.1016/j.gltp.2022.03.017 10.1049/stg2.12090 10.3390/jcp1010011 10.1109/TSG.2012.2223766 10.1016/j.energy.2022.123927 10.1016/j.ijcip.2021.100457 10.3390/jcp2030027 10.3390/app12136498 10.3390/info11050279 10.1016/j.cam.2020.112723 10.1007/s00450-017-0360-9 10.1109/JSYST.2021.3136683 10.1016/j.compeleceng.2021.107211 10.3390/smartcities5020038 10.3390/app10103430 10.3390/su12166434 10.1007/978-3-030-05918-7_20 10.1109/ICCED.2018.00052 10.3390/app9153174 10.1109/TCNS.2022.3141026 10.1007/s00607-021-01047-0 10.1109/TIFS.2017.2676721 10.1109/CCC.2019.000-6 10.4236/jsea.2022.1512024 10.1038/s41597-022-01455-7 10.1109/TCOMM.2014.2346775 10.1049/stg2.12070 10.3390/electronics12010242 10.1007/978-981-15-1706-8 10.1109/CED.2017.8308116 10.5121/csit.2020.102004 10.1007/s11036-020-01634-z 10.1016/j.scs.2021.103116 10.3390/en15186799 10.1109/JESTPE.2020.2968243 10.1109/NAPS52732.2021.9654767 10.1016/j.comnet.2019.107094 10.1109/UEMCON54665.2022.9965631 10.1109/ACCESS.2018.2835527 10.1109/SMC42975.2020.9282837 10.3390/su141610230 10.1016/j.jnca.2020.102767 10.1109/SmartGridComm52983.2022.9961017 10.3390/en16010409 10.1002/widm.1306 10.1109/ICICCT.2018.8473340 10.1109/IECON.2019.8926992 10.1109/TSG.2022.3185764 10.1016/j.asoc.2018.06.017 10.3390/app11219972 10.1109/Innovate-Data.2018.00014 10.1109/LGRS.2022.3175836 10.1109/ACCESS.2019.2923640 10.1016/j.jfranklin.2019.02.011 10.3390/en13184907 10.1145/1390156.1390189 10.1109/ACCESS.2019.2894819 10.20944/preprints202107.0120.v1 10.1007/978-981-15-6318-8_42 10.1016/j.egypro.2018.12.075 10.1007/s11277-019-06274-5 10.1109/TSG.2018.2878570 10.3390/s19224862 10.1109/JESTIE.2022.3198504 10.1109/ICOSEC49089.2020.9215232 10.3390/en16010528 10.1155/2020/8890306 10.1016/j.jpdc.2021.03.011 10.1155/2022/7319010 10.1109/RWEEK.2017.8088642 10.1016/j.ijepes.2022.108798 10.3390/info11050243 10.1016/j.compeleceng.2021.107299 10.3390/s18010162 10.2139/ssrn.4074646 10.1145/3029806.3029823 10.3390/en11081973 10.1007/978-981-16-3607-3 10.1109/NAECON.2016.7856831 10.3390/s22134826 10.1016/j.future.2022.01.017 10.3390/math10162852 10.1109/WETICE49692.2020.00045 10.14569/IJACSA.2018.090354 10.1016/j.rser.2015.09.077 10.1109/ACCESS.2021.3058628 10.1109/WCNC.2018.8377010 10.1109/WPMC50192.2020.9309494 10.1016/j.epsr.2022.108975 10.1002/spy2.285 10.1109/TSG.2016.2521339 10.1145/3297156.3297230 10.1016/j.apenergy.2021.117129 10.1016/j.measurement.2019.107450 10.1007/s41635-018-0063-0 10.3390/app12157882 10.1145/3264888.3264896 10.1109/CYBER46603.2019.9066680 10.1016/j.asoc.2020.106658 10.17148/IJARCCE.2017.6497 10.3390/s20185305 10.1109/ACCESS.2019.2920682 10.1109/ICACCI.2017.8126031 10.3390/su14148801 10.1109/IECON.2017.8217069 10.1016/j.jisa.2020.102722 10.1016/j.rser.2019.03.002 10.1109/IECON.2018.8591401 10.1109/TSG.2021.3067896 10.1002/ett.4360 10.1016/j.ijepes.2019.105643 10.1109/EIT.2018.8500086 10.1109/ACCESS.2021.3049216 10.1109/TSG.2019.2928168 10.1109/TITS.2020.3025875 |
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| References | ref_137 ref_93 ref_136 ref_92 ref_139 ref_91 ref_138 Deepa (ref_29) 2022; 131 Ullah (ref_119) 2021; 9 Giraldo (ref_86) 2016; 8 ref_14 Mantas (ref_174) 2017; 238 ref_13 ref_12 ref_11 Huda (ref_115) 2018; 71 ref_98 ref_133 Kishore (ref_81) 2017; 6 Sun (ref_90) 2021; 9 ref_135 Long (ref_161) 2019; 159 ref_95 ref_134 Bertone (ref_28) 2020; 3 ref_19 ref_18 Ravipati (ref_128) 2019; 11 ref_17 Mohammadi (ref_36) 2022; 3 ref_16 ref_15 Musleh (ref_61) 2019; 7 Gao (ref_130) 2019; 7 Ahl (ref_66) 2019; 107 Chen (ref_94) 2022; 18 Lin (ref_118) 1997; 45 Tian (ref_143) 2021; 9 ref_126 ref_125 ref_127 ref_129 Sarker (ref_169) 2019; 6 ref_25 ref_24 ref_120 ref_22 Ahsan (ref_170) 2021; 1 ref_122 ref_20 ref_121 ref_124 ref_123 ref_27 ref_26 Zhang (ref_48) 2022; 27 ref_159 ref_71 ref_158 Cai (ref_153) 2022; 47 Morstyn (ref_162) 2018; 10 Siano (ref_3) 2016; 53 ref_79 ref_78 ref_77 ref_76 ref_155 ref_154 ref_74 ref_157 ref_156 Ahsan (ref_73) 2022; 2 Tan (ref_89) 2017; 12 ref_160 Moustafa (ref_97) 2022; 19 Ding (ref_83) 2014; 62 Kaur (ref_150) 2021; 77 ref_147 ref_80 ref_149 Zheng (ref_99) 2022; 9 ref_140 ref_142 ref_141 ref_144 Mollah (ref_9) 2020; 8 ref_85 Habibi (ref_117) 2020; 9 ref_84 ref_145 Fakiha (ref_75) 2021; 11 Zhang (ref_88) 2019; 11 Geetha (ref_82) 2016; 3 Kocher (ref_131) 2020; 10 Kjamilji (ref_177) 2021; 9 ref_50 Li (ref_34) 2022; 38 ref_58 ref_173 ref_57 ref_172 ref_56 ref_175 ref_55 ref_54 Acharya (ref_31) 2021; 12 ref_176 ref_52 ref_179 ref_51 ref_178 Zhang (ref_60) 2021; 9 ref_180 ref_59 Sheatsley (ref_111) 2021; 21 Kurt (ref_41) 2018; 10 Singh (ref_152) 2022; 12 Seven (ref_164) 2020; 8 Zamponi (ref_21) 2022; 5 Tran (ref_151) 2022; 104 Jaiswal (ref_6) 2022; 3 Takiddin (ref_10) 2022; 16 Mengelkamp (ref_72) 2018; 33 ref_68 ref_67 ref_163 ref_65 Saber (ref_96) 2022; 13 ref_166 ref_64 ref_165 ref_63 ref_168 Uludag (ref_23) 2021; 358 ref_62 ref_167 Mekni (ref_148) 2022; 15 ref_171 Ahmed (ref_42) 2018; 6 ref_114 Liu (ref_146) 2022; 9 Hossain (ref_69) 2019; 7 ref_35 ref_33 ref_32 ref_110 ref_30 ref_113 ref_112 Maharjan (ref_87) 2013; 4 ref_39 ref_38 Javed (ref_108) 2020; 22 ref_37 Starke (ref_53) 2022; 5 ref_104 He (ref_106) 2016; 1 ref_105 Prasad (ref_70) 2019; 106 ref_109 ref_47 ref_46 Xin (ref_107) 2018; 6 Nguyen (ref_116) 2021; 153 ref_45 ref_44 ref_43 ref_100 ref_102 Konstantinou (ref_103) 2019; 3 ref_40 ref_101 ref_1 ref_2 ref_49 ref_8 Kasongo (ref_132) 2020; 7 ref_5 ref_4 ref_7 |
| References_xml | – volume: 21 start-page: 9994 year: 2021 ident: ref_111 article-title: Improving radioactive material localization by leveraging cyber-security model optimizations publication-title: IEEE Sens. J. doi: 10.1109/JSEN.2021.3055778 – ident: ref_4 doi: 10.3390/s21238087 – volume: 19 start-page: 995 year: 2022 ident: ref_97 article-title: Privacy-Preserved Generative Network for Trustworthy Anomaly Detection in Smart Grids: A Federated Semisupervised Approach publication-title: IEEE Trans. Ind. Inform. – ident: ref_74 – ident: ref_138 doi: 10.14236/ewic/icscsr19.16 – volume: 45 start-page: 2719 year: 1997 ident: ref_118 article-title: A delay damage model selection algorithm for NARX neural networks publication-title: IEEE Trans. Signal Process. doi: 10.1109/78.650098 – volume: 8 start-page: 18 year: 2020 ident: ref_9 article-title: Blockchain for future smart grid: A comprehensive survey publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2020.2993601 – ident: ref_39 doi: 10.3390/bdcc4010001 – volume: 7 start-page: 105 year: 2020 ident: ref_132 article-title: Performance analysis of intrusion detection systems using a feature selection method on the UNSW-NB15 dataset publication-title: J. Big Data doi: 10.1186/s40537-020-00379-6 – volume: 9 start-page: 11365 year: 2021 ident: ref_90 article-title: Data poisoning attacks on federated machine learning publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2021.3128646 – volume: 77 start-page: 9202 year: 2021 ident: ref_150 article-title: A systematic study of load balancing approaches in the fog computing environment publication-title: J. Supercomput. doi: 10.1007/s11227-020-03600-8 – volume: 10 start-page: 2026 year: 2018 ident: ref_162 article-title: Bilateral contract networks for peer-to-peer energy trading publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2017.2786668 – ident: ref_175 – ident: ref_14 doi: 10.4236/cn.2022.144009 – volume: 9 start-page: 807 year: 2021 ident: ref_143 article-title: Adversarial attacks and defense for CNN based power quality recognition in smart grid publication-title: IEEE Trans. Netw. Sci. Eng. doi: 10.1109/TNSE.2021.3135565 – ident: ref_149 doi: 10.1155/2022/3151249 – volume: 3 start-page: 208 year: 2020 ident: ref_28 article-title: Artificial intelligence techniques to prevent cyber attacks on smart grids publication-title: Ann. Disaster Risk Sci. ADRS – ident: ref_168 doi: 10.1016/j.energy.2021.122713 – volume: 18 start-page: 8467 year: 2022 ident: ref_94 article-title: Data-driven detection of stealthy false data injection attack against power system state estimation publication-title: IEEE Trans. Ind. Inform. doi: 10.1109/TII.2022.3149106 – ident: ref_59 doi: 10.3390/electronics6010005 – ident: ref_54 doi: 10.1109/ISGT-Europe47291.2020.9248779 – volume: 6 start-page: 49 year: 2019 ident: ref_169 article-title: Recencyminer: Mining recency-based personalized behavior from contextual smartphone data publication-title: J. Big Data doi: 10.1186/s40537-019-0211-6 – ident: ref_147 doi: 10.1109/INFOCOM42981.2021.9488823 – ident: ref_16 doi: 10.1016/j.ijcip.2022.100547 – ident: ref_163 doi: 10.1109/BLOC.2019.8751268 – volume: 47 start-page: 443 year: 2022 ident: ref_153 article-title: Integration of hydrogen storage system and wind generation in power systems under demand response program: A novel p-robust stochastic programming publication-title: Int. J. Hydrog. Energy doi: 10.1016/j.ijhydene.2021.10.027 – ident: ref_20 doi: 10.3390/en16010347 – ident: ref_47 doi: 10.1016/j.jobe.2022.104323 – ident: ref_22 doi: 10.1016/j.rser.2021.111530 – ident: ref_127 doi: 10.3390/sym13010004 – ident: ref_114 – volume: 9 start-page: 103906 year: 2021 ident: ref_119 article-title: Design and development of a deep learning-based model for anomaly detection in IoT networks publication-title: IEEE Access doi: 10.1109/ACCESS.2021.3094024 – ident: ref_62 – volume: 1 start-page: 13 year: 2016 ident: ref_106 article-title: Cyber-physical attacks and defences in the smart grid: A survey publication-title: IET Cyber-Phys. Syst. Theory Appl. doi: 10.1049/iet-cps.2016.0019 – ident: ref_165 doi: 10.1016/j.energy.2020.117417 – ident: ref_142 doi: 10.3390/en12173310 – ident: ref_49 doi: 10.3390/en16020635 – ident: ref_37 doi: 10.1109/AIIoT54504.2022.9817309 – ident: ref_77 doi: 10.1109/RAIT.2018.8389037 – ident: ref_30 doi: 10.1109/SoutheastCon45413.2021.9401940 – volume: 8 start-page: 175713 year: 2020 ident: ref_164 article-title: Peer-to-peer energy trading in virtual power plant based on blockchain smart contracts publication-title: IEEE Access doi: 10.1109/ACCESS.2020.3026180 – ident: ref_38 doi: 10.1016/j.ijcip.2022.100542 – volume: 6 start-page: 35365 year: 2018 ident: ref_107 article-title: Machine learning and deep learning methods for cybersecurity publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2836950 – ident: ref_46 doi: 10.23919/WAC55640.2022.9934344 – ident: ref_84 doi: 10.1109/MSCPES.2019.8738801 – volume: 3 start-page: 311 year: 2022 ident: ref_6 article-title: Modeling & designing of smart energy meter for smart grid applications publication-title: Glob. Transit. Proc. doi: 10.1016/j.gltp.2022.03.017 – ident: ref_7 doi: 10.1049/stg2.12090 – volume: 1 start-page: 199 year: 2021 ident: ref_170 article-title: Enhancing machine learning prediction in cybersecurity using dynamic feature selector publication-title: J. Cybersecur. Priv. doi: 10.3390/jcp1010011 – volume: 4 start-page: 120 year: 2013 ident: ref_87 article-title: Dependable demand response management in the smart grid: A Stackelberg game approach publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2012.2223766 – ident: ref_154 doi: 10.1016/j.energy.2022.123927 – ident: ref_27 doi: 10.1016/j.ijcip.2021.100457 – volume: 2 start-page: 527 year: 2022 ident: ref_73 article-title: Cybersecurity threats and their mitigation approaches using Machine Learning—A Review publication-title: J. Cybersecur. Priv. doi: 10.3390/jcp2030027 – ident: ref_134 – ident: ref_100 doi: 10.3390/app12136498 – ident: ref_121 doi: 10.3390/info11050279 – ident: ref_157 doi: 10.1016/j.cam.2020.112723 – volume: 33 start-page: 207 year: 2018 ident: ref_72 article-title: A blockchain-based smart grid: Towards sustainable local energy markets publication-title: Comput. Sci.-Res. Dev. doi: 10.1007/s00450-017-0360-9 – ident: ref_92 – volume: 16 start-page: 4106 year: 2022 ident: ref_10 article-title: Deep autoencoder-based anomaly detection of electricity theft cyberattacks in smart grids publication-title: IEEE Syst. J. doi: 10.1109/JSYST.2021.3136683 – ident: ref_45 doi: 10.1016/j.compeleceng.2021.107211 – volume: 5 start-page: 728 year: 2022 ident: ref_21 article-title: The Dual Role of Artificial Intelligence in Developing Smart Cities publication-title: Smart Cities doi: 10.3390/smartcities5020038 – ident: ref_112 doi: 10.3390/app10103430 – ident: ref_91 doi: 10.3390/su12166434 – ident: ref_137 doi: 10.1007/978-3-030-05918-7_20 – ident: ref_78 doi: 10.1109/ICCED.2018.00052 – volume: 238 start-page: 80 year: 2017 ident: ref_174 article-title: The hazards of data mining in healthcare publication-title: Inform. Empower. Healthc. Transform. – ident: ref_109 doi: 10.3390/app9153174 – volume: 9 start-page: 1238 year: 2022 ident: ref_146 article-title: Relentless false data injection attacks against Kalman-filter-based detection in smart grid publication-title: IEEE Trans. Control Netw. Syst. doi: 10.1109/TCNS.2022.3141026 – ident: ref_25 – volume: 104 start-page: 1285 year: 2022 ident: ref_151 article-title: Virtual machine migration policy for multi-tier application in cloud computing based on Q-learning algorithm publication-title: Computing doi: 10.1007/s00607-021-01047-0 – volume: 12 start-page: 1609 year: 2017 ident: ref_89 article-title: Modeling and mitigating impact of false data injection attacks on automatic generation control publication-title: IEEE Trans. Inf. Secur. doi: 10.1109/TIFS.2017.2676721 – ident: ref_141 doi: 10.1109/CCC.2019.000-6 – volume: 15 start-page: 417 year: 2022 ident: ref_148 article-title: Reinforcement Learning Toolkits for Gaming: A Comparative Qualitative Analysis publication-title: J. Softw. Eng. Appl. doi: 10.4236/jsea.2022.1512024 – volume: 9 start-page: 359 year: 2022 ident: ref_99 article-title: A multi-scale time-series dataset with benchmark for machine learning in decarbonized energy grids publication-title: Sci. Data doi: 10.1038/s41597-022-01455-7 – volume: 62 start-page: 3129 year: 2014 ident: ref_83 article-title: Robust spectrum sensing with crowd sensors publication-title: IEEE Trans. Commun. doi: 10.1109/TCOMM.2014.2346775 – volume: 5 start-page: 398 year: 2022 ident: ref_53 article-title: Cross-layered distributed data-driven framework for enhanced smart grid cyber-physical security publication-title: IET Smart Grid doi: 10.1049/stg2.12070 – volume: 11 start-page: 1 year: 2019 ident: ref_128 article-title: Intrusion detection system classification using different machine learning algorithms on KDD-99 and NSL-KDD datasets-a review paper publication-title: Int. J. Comput. Sci. Inf. Technol. (IJCSIT) – ident: ref_19 doi: 10.3390/electronics12010242 – ident: ref_95 – ident: ref_179 doi: 10.1007/978-981-15-1706-8 – ident: ref_80 doi: 10.1109/CED.2017.8308116 – volume: 10 start-page: 31 year: 2020 ident: ref_131 article-title: Performance analysis of machine learning classifiers for intrusion detection using unsw-nb15 dataset publication-title: Comput. Sci. Inf. Technol.(CS IT) doi: 10.5121/csit.2020.102004 – volume: 12 start-page: 1 year: 2022 ident: ref_152 article-title: An adaptive mechanism for virtual machine migration in the cloud environment publication-title: Int. J. Cloud Appl. Comput. (IJCAC) – volume: 27 start-page: 329 year: 2022 ident: ref_48 article-title: Jamming-resilient backup nodes selection for RPL-based routing in smart grid AMI networks publication-title: Mob. Netw. Appl. doi: 10.1007/s11036-020-01634-z – ident: ref_55 doi: 10.1016/j.scs.2021.103116 – ident: ref_1 doi: 10.3390/en15186799 – volume: 9 start-page: 5294 year: 2020 ident: ref_117 article-title: Detection of false data injection cyber-attacks in DC microgrids based on recurrent neural networks publication-title: IEEE J. Emerg. Sel. Top. Power Electron. doi: 10.1109/JESTPE.2020.2968243 – ident: ref_24 doi: 10.1109/NAPS52732.2021.9654767 – ident: ref_57 doi: 10.1016/j.comnet.2019.107094 – ident: ref_113 – ident: ref_51 doi: 10.1109/UEMCON54665.2022.9965631 – volume: 6 start-page: 27518 year: 2018 ident: ref_42 article-title: Feature selection–based detection of covert cyber deception assaults in smart grid communications networks using machine learning publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2835527 – ident: ref_144 doi: 10.1109/SMC42975.2020.9282837 – ident: ref_18 doi: 10.3390/su141610230 – ident: ref_136 doi: 10.1016/j.jnca.2020.102767 – ident: ref_15 doi: 10.1109/SmartGridComm52983.2022.9961017 – ident: ref_5 doi: 10.3390/en16010409 – ident: ref_93 doi: 10.1002/widm.1306 – ident: ref_180 – ident: ref_125 doi: 10.1109/ICICCT.2018.8473340 – ident: ref_102 doi: 10.1109/IECON.2019.8926992 – volume: 13 start-page: 4787 year: 2022 ident: ref_96 article-title: Anomaly-Based Detection of Cyberattacks on Line Current Differential Relays publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2022.3185764 – volume: 71 start-page: 66 year: 2018 ident: ref_115 article-title: Securing the operations in SCADA-IoT platform based industrial control system using ensemble of deep belief networks publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2018.06.017 – ident: ref_58 doi: 10.3390/app11219972 – ident: ref_44 doi: 10.1109/Innovate-Data.2018.00014 – ident: ref_98 doi: 10.1109/LGRS.2022.3175836 – volume: 7 start-page: 82512 year: 2019 ident: ref_130 article-title: An adaptive ensemble machine learning model for intrusion detection publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2923640 – volume: 358 start-page: 172 year: 2021 ident: ref_23 article-title: Timely detection and mitigation of IoT-based cyberattacks in the smart grid publication-title: J. Frankl. Inst. doi: 10.1016/j.jfranklin.2019.02.011 – ident: ref_63 doi: 10.3390/en13184907 – ident: ref_145 doi: 10.1145/1390156.1390189 – volume: 3 start-page: 42 year: 2016 ident: ref_82 article-title: Byzantine attacks and its security measures in mobile adhoc networks publication-title: Int’l J. Comput. Commun. Instrum. Eng. (IJCCIE 2016) – volume: 7 start-page: 13960 year: 2019 ident: ref_69 article-title: Application of big data and machine learning in smart grid, and associated security concerns: A review publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2894819 – ident: ref_156 doi: 10.20944/preprints202107.0120.v1 – ident: ref_133 doi: 10.1007/978-981-15-6318-8_42 – volume: 159 start-page: 454 year: 2019 ident: ref_161 article-title: A game theoretic approach for peer to peer energy trading publication-title: Energy Procedia doi: 10.1016/j.egypro.2018.12.075 – volume: 106 start-page: 261 year: 2019 ident: ref_70 article-title: Security for smart grid in 5G and beyond networks publication-title: Wirel. Pers. Commun. doi: 10.1007/s11277-019-06274-5 – volume: 10 start-page: 5174 year: 2018 ident: ref_41 article-title: Online cyber-attack detection in smart grid: A reinforcement learning approach publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2018.2878570 – ident: ref_160 doi: 10.3390/s19224862 – volume: 3 start-page: 878 year: 2022 ident: ref_36 article-title: A review on application of artificial intelligence techniques in microgrids publication-title: IEEE J. Emerg. Sel. Top. Ind. Electron. doi: 10.1109/JESTIE.2022.3198504 – ident: ref_129 doi: 10.1109/ICOSEC49089.2020.9215232 – ident: ref_176 – ident: ref_2 doi: 10.3390/en16010528 – ident: ref_140 doi: 10.1155/2020/8890306 – volume: 153 start-page: 150 year: 2021 ident: ref_116 article-title: Secure blockchain enabled Cyber–physical systems in healthcare using deep belief network with ResNet model publication-title: J. Parallel Distrib. Comput. doi: 10.1016/j.jpdc.2021.03.011 – ident: ref_52 doi: 10.1155/2022/7319010 – ident: ref_67 doi: 10.1109/RWEEK.2017.8088642 – ident: ref_110 – ident: ref_50 doi: 10.1016/j.ijepes.2022.108798 – ident: ref_139 doi: 10.3390/info11050243 – ident: ref_166 doi: 10.1016/j.compeleceng.2021.107299 – ident: ref_68 doi: 10.3390/s18010162 – ident: ref_76 – ident: ref_101 doi: 10.2139/ssrn.4074646 – ident: ref_122 doi: 10.1145/3029806.3029823 – ident: ref_159 doi: 10.3390/en11081973 – volume: 38 start-page: 2364 year: 2022 ident: ref_34 article-title: Cybersecurity of smart inverters in the smart grid: A survey publication-title: IEEE Trans. Power Electron. – ident: ref_173 – ident: ref_172 doi: 10.1007/978-981-16-3607-3 – ident: ref_105 doi: 10.1109/NAECON.2016.7856831 – ident: ref_40 – ident: ref_155 doi: 10.3390/s22134826 – volume: 131 start-page: 209 year: 2022 ident: ref_29 article-title: A survey on blockchain for big data: Approaches, opportunities, and future directions publication-title: Future Gener. Comput. Syst. doi: 10.1016/j.future.2022.01.017 – ident: ref_32 doi: 10.3390/math10162852 – ident: ref_124 doi: 10.1109/WETICE49692.2020.00045 – ident: ref_178 doi: 10.14569/IJACSA.2018.090354 – volume: 53 start-page: 1611 year: 2016 ident: ref_3 article-title: Mobile social media for smart grids customer engagement: Emerging trends and challenges publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2015.09.077 – volume: 9 start-page: 29641 year: 2021 ident: ref_60 article-title: Smart grid cyber-physical attack and defense: A review publication-title: IEEE Access doi: 10.1109/ACCESS.2021.3058628 – ident: ref_64 doi: 10.1109/WCNC.2018.8377010 – ident: ref_35 doi: 10.1109/WPMC50192.2020.9309494 – ident: ref_13 doi: 10.1016/j.epsr.2022.108975 – ident: ref_79 – ident: ref_11 doi: 10.1002/spy2.285 – volume: 8 start-page: 2249 year: 2016 ident: ref_86 article-title: Integrity attacks on real-time pricing in smart grids: Impact and countermeasures publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2016.2521339 – ident: ref_135 doi: 10.1145/3297156.3297230 – ident: ref_167 doi: 10.1016/j.apenergy.2021.117129 – ident: ref_123 doi: 10.1016/j.measurement.2019.107450 – volume: 3 start-page: 132 year: 2019 ident: ref_103 article-title: Hardware-layer intelligence collection for smart grid embedded systems publication-title: J. Hardw. Syst. Secur. doi: 10.1007/s41635-018-0063-0 – ident: ref_17 doi: 10.3390/app12157882 – ident: ref_120 doi: 10.1145/3264888.3264896 – ident: ref_43 doi: 10.1109/CYBER46603.2019.9066680 – ident: ref_26 doi: 10.1016/j.asoc.2020.106658 – volume: 6 start-page: 505 year: 2017 ident: ref_81 article-title: Internet of things based low-cost real-time home automation and smart security system publication-title: Int. J. Adv. Res. Comput. Commun. Eng. doi: 10.17148/IJARCCE.2017.6497 – ident: ref_12 – ident: ref_85 – ident: ref_56 doi: 10.3390/s20185305 – volume: 7 start-page: 86746 year: 2019 ident: ref_61 article-title: Blockchain applications in smart grid–review and frameworks publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2920682 – ident: ref_126 doi: 10.1109/ICACCI.2017.8126031 – ident: ref_8 doi: 10.3390/su14148801 – ident: ref_65 doi: 10.1109/IECON.2017.8217069 – ident: ref_33 doi: 10.1016/j.jisa.2020.102722 – volume: 107 start-page: 200 year: 2019 ident: ref_66 article-title: Review of blockchain-based distributed energy: Implications for institutional development publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2019.03.002 – ident: ref_104 doi: 10.1109/IECON.2018.8591401 – volume: 12 start-page: 3548 year: 2021 ident: ref_31 article-title: Causative cyberattacks on online learning-based automated demand response systems publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2021.3067896 – volume: 11 start-page: 101 year: 2021 ident: ref_75 article-title: Business organization security strategies to cyber security threats publication-title: Int. J. Saf. Secur. Eng – ident: ref_158 doi: 10.1002/ett.4360 – ident: ref_71 doi: 10.1016/j.ijepes.2019.105643 – ident: ref_171 doi: 10.1109/EIT.2018.8500086 – volume: 9 start-page: 8324 year: 2021 ident: ref_177 article-title: Efficient secure building blocks with application to privacy preserving machine learning algorithms publication-title: IEEE Access doi: 10.1109/ACCESS.2021.3049216 – volume: 11 start-page: 931 year: 2019 ident: ref_88 article-title: Cyber physical security analytics for transactive energy systems publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2019.2928168 – volume: 22 start-page: 4291 year: 2020 ident: ref_108 article-title: Anomaly detection in automated vehicles using multistage attention-based convolutional neural network publication-title: IEEE Trans. Intell. Transp. Syst. doi: 10.1109/TITS.2020.3025875 |
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| SubjectTerms | Alternative energy sources Artificial intelligence Blockchain Cryptography cyber security cyberattacks Cybercrime Cybersecurity Cyberterrorism data mining Data security deep learning Electronic devices Energy consumption Genetic algorithms Internet Machine learning Methods Neural networks Packets (communication) Security software Sensors Smart grid Smart sensors |
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