{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/101372"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/101372","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Secure integration of electric vehicles with the power grid","abstract":"A wide variety of distributed energy resources (DERs) such as pluggable electric vehicles (EVs), solar arrays, smart buildings, etc. are now being connected to the power grid. Malicious adversaries can use these as entry mechanisms to gain access to the grid with the intention of creating instability in the system. This work focuses on secure integration of DERs with the power grid. To this end, we propose techniques to detect malicious activity when either the DERs or the communication channels between the DERs and the smart grid components are compromised. We propose a cyber-physical anomaly detection engine to ensure that critical grid components remain secure, and hence, safe. Specifically, we have focused on the vehicle-to-grid (V2G) system. In this system, aggregators are the critical components through which DERs such as EVs are connected to the grid. We have developed a prototype anomaly detection engine for aggregators that manage/communicate with the EVs. Since the V2G system is time-sensitive, the anomaly detection engine also monitors the timing requirements of the system by checking the frequency constraints on messages at the aggregator apart from monitoring the cyber and physical data constraints to ensure safety of the aggregator.","abstract_html":"A wide variety of distributed energy resources (DERs) such as pluggable electric vehicles (EVs), solar arrays, smart buildings, etc. are now being connected to the power grid. Malicious adversaries can use these as entry mechanisms to gain access to the grid with the intention of creating instability in the system. This work focuses on secure integration of DERs with the power grid. To this end, we propose techniques to detect malicious activity when either the DERs or the communication channels between the DERs and the smart grid components are compromised. We propose a cyber-physical anomaly detection engine to ensure that critical grid components remain secure, and hence, safe. Specifically, we have focused on the vehicle-to-grid (V2G) system. In this system, aggregators are the critical components through which DERs such as EVs are connected to the grid. We have developed a prototype anomaly detection engine for aggregators that manage/communicate with the EVs. Since the V2G system is time-sensitive, the anomaly detection engine also monitors the timing requirements of the system by checking the frequency constraints on messages at the aggregator apart from monitoring the cyber and physical data constraints to ensure safety of the aggregator.","abstract_has_math":false,"creators":["Niddodi, Chaitra Prasad"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Mohan, Sibin"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-09-04T20:47:30Z","date_published":"2018-09-04T20:47:30Z","updated_at":"2026-07-22T22:24:40Z","subjects":["Cyber-Physical Systems"],"languages":["en"],"rights":["Copyright 2018 Chaitra Niddodi"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/101372","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Mohan, Sibin"]},{"key":"dc:creator","label":"Author","values":["Niddodi, Chaitra Prasad"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-09-04T20:47:30Z","2020-09-05T09:15:20Z","2018-04-25","2018-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Cyber-Physical Systems"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2018 Chaitra Niddodi"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/101372"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["A wide variety of distributed energy resources (DERs) such as pluggable electric vehicles (EVs), solar arrays, smart buildings, etc. are now being connected to the power grid. Malicious adversaries can use these as entry mechanisms to gain access to the grid with the intention of creating instability in the system. This work focuses on secure integration of DERs with the power grid. To this end, we propose techniques to detect malicious activity when either the DERs or the communication channels between the DERs and the smart grid components are compromised. We propose a cyber-physical anomaly detection engine to ensure that critical grid components remain secure, and hence, safe. Specifically, we have focused on the vehicle-to-grid (V2G) system. In this system, aggregators are the critical components through which DERs such as EVs are connected to the grid. We have developed a prototype anomaly detection engine for aggregators that manage/communicate with the EVs. Since the V2G system is time-sensitive, the anomaly detection engine also monitors the timing requirements of the system by checking the frequency constraints on messages at the aggregator apart from monitoring the cyber and physical data constraints to ensure safety of the aggregator.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Chaitra Niddodi, accepted the attached license on 2018-04-24 at 17:28.","The student, Chaitra Niddodi, submitted this Thesis for approval on 2018-04-24 at 17:33.","This Thesis was approved for publication on 2018-04-25 at 12:48.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12462 on 2018-08-31 at 17:30:23","Made available in DSpace on 2018-09-04T20:47:30Z (GMT). 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Malicious adversaries can use these as entry mechanisms to gain access to the grid with the intention of creating instability in the system. This work focuses on secure integration of DERs with the power grid. To this end, we propose techniques to detect malicious activity when either the DERs or the communication channels between the DERs and the smart grid components are compromised. We propose a cyber-physical anomaly detection engine to ensure that critical grid components remain secure, and hence, safe. Specifically, we have focused on the vehicle-to-grid (V2G) system. In this system, aggregators are the critical components through which DERs such as EVs are connected to the grid. We have developed a prototype anomaly detection engine for aggregators that manage/communicate with the EVs. Since the V2G system is time-sensitive, the anomaly detection engine also monitors the timing requirements of the system by checking the frequency constraints on messages at the aggregator apart from monitoring the cyber and physical data constraints to ensure safety of the aggregator.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Chaitra Niddodi, accepted the attached license on 2018-04-24 at 17:28.","The student, Chaitra Niddodi, submitted this Thesis for approval on 2018-04-24 at 17:33.","This Thesis was approved for publication on 2018-04-25 at 12:48.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12462 on 2018-08-31 at 17:30:23","Made available in DSpace on 2018-09-04T20:47:30Z (GMT). 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