{"id":"https://openalex.org/W4402526469","doi":"https://doi.org/10.1145/3679008.3685540","title":"Runtime Invariant Checking in Robotic Systems and Deep Learning Models (Keynote)","display_name":"Runtime Invariant Checking in Robotic Systems and Deep Learning Models (Keynote)","publication_year":2024,"publication_date":"2024-09-13","ids":{"openalex":"https://openalex.org/W4402526469","doi":"https://doi.org/10.1145/3679008.3685540"},"language":"en","primary_location":{"id":"doi:10.1145/3679008.3685540","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3679008.3685540","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Workshop on Verification and Monitoring at Runtime Execution","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107249133","display_name":"Xiangyu Zhang","orcid":"https://orcid.org/0000-0002-9544-2500"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiangyu Zhang","raw_affiliation_strings":["Purdue University, West Lafayette, USA"],"raw_orcid":"https://orcid.org/0000-0002-9544-2500","affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5107249133"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18095386,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10142","display_name":"Formal Methods in Verification","score":0.9733999967575073,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10142","display_name":"Formal Methods in Verification","score":0.9733999967575073,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9567999839782715,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9496999979019165,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6998319029808044},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6192858219146729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5721696019172668},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5297818183898926},{"id":"https://openalex.org/keywords/model-checking","display_name":"Model checking","score":0.487428218126297},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.2740268409252167},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10672172904014587}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6998319029808044},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6192858219146729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5721696019172668},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5297818183898926},{"id":"https://openalex.org/C110251889","wikidata":"https://www.wikidata.org/wiki/Q1569697","display_name":"Model checking","level":2,"score":0.487428218126297},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2740268409252167},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10672172904014587},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3679008.3685540","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3679008.3685540","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Workshop on Verification and Monitoring at Runtime Execution","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"Invariant":[0],"checking":[1,39],"is":[2],"an":[3],"important":[4],"runtime":[5,23,117,158,179],"verification":[6],"method.":[7],"While":[8],"it":[9],"was":[10],"invented":[11],"for":[12,27,116,168,182],"classic":[13],"software":[14],"systems,":[15],"the":[16,91,111,133],"concept":[17],"can":[18,40,104,136,165],"be":[19,41,106,166],"extended":[20,42],"to":[21,43,47,54,76],"identifying":[22,44],"failures":[24],"and":[25,51,64,90,108,128,151],"attacks":[26,46,53,143],"other":[28],"computation":[29],"systems.":[30,57],"In":[31,160],"this":[32],"talk,":[33],"I":[34],"will":[35],"discuss":[36],"how":[37],"invariant":[38,118,134],"physical":[45,85,142],"robotic":[48],"vehicles":[49],"(RVs)":[50],"adversarial":[52],"deep":[55,172],"learning":[56,173],"For":[58],"RV":[59],"attack":[60,153,180],"detection,":[61],"we":[62,72],"derive":[63],"monitor":[65],"so-called":[66],"Control":[67],"Invariants":[68],"(CI).":[69],"More":[70],"specifically,":[71],"propose":[73],"a":[74,83,100],"method":[75],"extract":[77],"such":[78,176,183],"invariants":[79,96,164,177],"by":[80],"jointly":[81],"modeling":[82],"vehicle\u2019s":[84,112],"properties,":[86],"its":[87],"control":[88,113],"algorithm":[89],"laws":[92],"of":[93,141,171],"physics.":[94],"These":[95],"are":[97],"represented":[98],"in":[99],"state-space":[101],"form,":[102],"which":[103],"then":[105],"implemented":[107],"inserted":[109],"into":[110],"program":[114],"binary":[115],"check.":[119],"Our":[120],"evaluation":[121],"on":[122],"eleven":[123],"RVs,":[124],"including":[125,145],"quadrotor,":[126],"hexarotor,":[127],"ground":[129],"rover,":[130],"show":[131],"that":[132],"check":[135],"detect":[137],"three":[138],"common":[139],"types":[140],"\u2013":[144,154],"sensor":[146],"attack,":[147,150],"actuation":[148],"signal":[149],"parameter":[152],"with":[155],"very":[156],"low":[157],"overhead.":[159],"addition,":[161],"statistical":[162],"distribution":[163],"derived":[167],"activation":[169],"values":[170],"models.":[174,184],"Checking":[175],"enables":[178],"detection":[181]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}