Resilient sampled-data control of networked control systems against cyber attacks
The object of this article is to propose novel resilient control strategies for networked control systems (NCS) against cyber-attacks. At first it is assumed system is under no attack. For stabilization of healthy NCS, a state feedback sampled-data controller is offered. Then, it is assumed system i...
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Veröffentlicht in: | International journal of dynamics and control 2020-03, Vol.8 (1), p.205-217 |
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description | The object of this article is to propose novel resilient control strategies for networked control systems (NCS) against cyber-attacks. At first it is assumed system is under no attack. For stabilization of healthy NCS, a state feedback sampled-data controller is offered. Then, it is assumed system is under cyber-attacks that occurred in different parts of NCS. In cyber-attack conditions, at first it is assumed attacker can access to the control block channel and consequently injects false data to controller. Then, it is assumed cyber-attack is occurred in the communication link between sensor–controller and consequently in some intervals instead of the correct data from sensor, false data from attacker is injected to controller. Finally, it is assumed attacker can access to the operator’s computer that adjusts the controller gain and consequently gain fluctuation is occurred. In such conditions novel resilient control strategies are proposed to keep the performance of the attacked system up to a reasonable security bound. To achieve resilience in such conditions, Lyapunov–Krasovskii functional method is applied and delay dependent resilient criteria are established to show the uniformly ultimately bounded behavior of system in each attack scenario. Finally, for evaluating results, a practical example will be discussed. |
doi_str_mv | 10.1007/s40435-018-0495-y |
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At first it is assumed system is under no attack. For stabilization of healthy NCS, a state feedback sampled-data controller is offered. Then, it is assumed system is under cyber-attacks that occurred in different parts of NCS. In cyber-attack conditions, at first it is assumed attacker can access to the control block channel and consequently injects false data to controller. Then, it is assumed cyber-attack is occurred in the communication link between sensor–controller and consequently in some intervals instead of the correct data from sensor, false data from attacker is injected to controller. Finally, it is assumed attacker can access to the operator’s computer that adjusts the controller gain and consequently gain fluctuation is occurred. In such conditions novel resilient control strategies are proposed to keep the performance of the attacked system up to a reasonable security bound. To achieve resilience in such conditions, Lyapunov–Krasovskii functional method is applied and delay dependent resilient criteria are established to show the uniformly ultimately bounded behavior of system in each attack scenario. Finally, for evaluating results, a practical example will be discussed.</description><identifier>ISSN: 2195-268X</identifier><identifier>EISSN: 2195-2698</identifier><identifier>DOI: 10.1007/s40435-018-0495-y</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Access control ; Complexity ; Control ; Control and Systems Theory ; Control systems ; Controllers ; Cybersecurity ; Dynamical Systems ; Engineering ; State feedback ; Variation ; Vibration</subject><ispartof>International journal of dynamics and control, 2020-03, Vol.8 (1), p.205-217</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>2018© Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c231y-2781ac441365ad1dc85dded8c66b903bd2782db536b203876362dc8c60f360de3</citedby><cites>FETCH-LOGICAL-c231y-2781ac441365ad1dc85dded8c66b903bd2782db536b203876362dc8c60f360de3</cites><orcidid>0000-0001-7486-2146</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40435-018-0495-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s40435-018-0495-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Fattahi, Maryam</creatorcontrib><creatorcontrib>Afshar, Ahmad</creatorcontrib><title>Resilient sampled-data control of networked control systems against cyber attacks</title><title>International journal of dynamics and control</title><addtitle>Int. J. Dynam. Control</addtitle><description>The object of this article is to propose novel resilient control strategies for networked control systems (NCS) against cyber-attacks. At first it is assumed system is under no attack. For stabilization of healthy NCS, a state feedback sampled-data controller is offered. Then, it is assumed system is under cyber-attacks that occurred in different parts of NCS. In cyber-attack conditions, at first it is assumed attacker can access to the control block channel and consequently injects false data to controller. Then, it is assumed cyber-attack is occurred in the communication link between sensor–controller and consequently in some intervals instead of the correct data from sensor, false data from attacker is injected to controller. Finally, it is assumed attacker can access to the operator’s computer that adjusts the controller gain and consequently gain fluctuation is occurred. In such conditions novel resilient control strategies are proposed to keep the performance of the attacked system up to a reasonable security bound. To achieve resilience in such conditions, Lyapunov–Krasovskii functional method is applied and delay dependent resilient criteria are established to show the uniformly ultimately bounded behavior of system in each attack scenario. Finally, for evaluating results, a practical example will be discussed.</description><subject>Access control</subject><subject>Complexity</subject><subject>Control</subject><subject>Control and Systems Theory</subject><subject>Control systems</subject><subject>Controllers</subject><subject>Cybersecurity</subject><subject>Dynamical Systems</subject><subject>Engineering</subject><subject>State feedback</subject><subject>Variation</subject><subject>Vibration</subject><issn>2195-268X</issn><issn>2195-2698</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp1kE1LxDAQhoMouOj-AG8Fz9FJ0qbpURa_YEEUBW8hTdKlu912zWSR_nuzVNaTp3kZnncGHkKuGNwwgPIWc8hFQYEpCnlV0PGEzDhLgctKnR6z-jwnc8Q1AHCWA8-rGXl989h2re9jhma767yjzkST2aGPYeiyocl6H7-HsPHuuMQRo99iZlam7TFmdqx9yEyMxm7wkpw1pkM__50X5OPh_n3xRJcvj8-LuyW1XLCR8lIxY_OcCVkYx5xVhXPeKStlXYGoXQK4qwshaw5ClVJIniAroRESnBcX5Hq6uwvD195j1OthH_r0UnNRqJIxXkKi2ETZMCAG3-hdaLcmjJqBPsjTkzyd5OmDPD2mDp86mNh-5cPf5f9LP8wpcuU</recordid><startdate>20200301</startdate><enddate>20200301</enddate><creator>Fattahi, Maryam</creator><creator>Afshar, Ahmad</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-7486-2146</orcidid></search><sort><creationdate>20200301</creationdate><title>Resilient sampled-data control of networked control systems against cyber attacks</title><author>Fattahi, Maryam ; Afshar, Ahmad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c231y-2781ac441365ad1dc85dded8c66b903bd2782db536b203876362dc8c60f360de3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Access control</topic><topic>Complexity</topic><topic>Control</topic><topic>Control and Systems Theory</topic><topic>Control systems</topic><topic>Controllers</topic><topic>Cybersecurity</topic><topic>Dynamical Systems</topic><topic>Engineering</topic><topic>State feedback</topic><topic>Variation</topic><topic>Vibration</topic><toplevel>online_resources</toplevel><creatorcontrib>Fattahi, Maryam</creatorcontrib><creatorcontrib>Afshar, Ahmad</creatorcontrib><collection>CrossRef</collection><jtitle>International journal of dynamics and control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fattahi, Maryam</au><au>Afshar, Ahmad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Resilient sampled-data control of networked control systems against cyber attacks</atitle><jtitle>International journal of dynamics and control</jtitle><stitle>Int. J. Dynam. Control</stitle><date>2020-03-01</date><risdate>2020</risdate><volume>8</volume><issue>1</issue><spage>205</spage><epage>217</epage><pages>205-217</pages><issn>2195-268X</issn><eissn>2195-2698</eissn><abstract>The object of this article is to propose novel resilient control strategies for networked control systems (NCS) against cyber-attacks. At first it is assumed system is under no attack. For stabilization of healthy NCS, a state feedback sampled-data controller is offered. Then, it is assumed system is under cyber-attacks that occurred in different parts of NCS. In cyber-attack conditions, at first it is assumed attacker can access to the control block channel and consequently injects false data to controller. Then, it is assumed cyber-attack is occurred in the communication link between sensor–controller and consequently in some intervals instead of the correct data from sensor, false data from attacker is injected to controller. Finally, it is assumed attacker can access to the operator’s computer that adjusts the controller gain and consequently gain fluctuation is occurred. In such conditions novel resilient control strategies are proposed to keep the performance of the attacked system up to a reasonable security bound. To achieve resilience in such conditions, Lyapunov–Krasovskii functional method is applied and delay dependent resilient criteria are established to show the uniformly ultimately bounded behavior of system in each attack scenario. Finally, for evaluating results, a practical example will be discussed.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s40435-018-0495-y</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-7486-2146</orcidid></addata></record> |
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subjects | Access control Complexity Control Control and Systems Theory Control systems Controllers Cybersecurity Dynamical Systems Engineering State feedback Variation Vibration |
title | Resilient sampled-data control of networked control systems against cyber attacks |
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