{"id":"https://openalex.org/W4390189950","doi":"https://doi.org/10.1109/milcom58377.2023.10356250","title":"Data-Driven Constraint Mining for Realizable Adversarial Samples","display_name":"Data-Driven Constraint Mining for Realizable Adversarial Samples","publication_year":2023,"publication_date":"2023-10-30","ids":{"openalex":"https://openalex.org/W4390189950","doi":"https://doi.org/10.1109/milcom58377.2023.10356250"},"language":"en","primary_location":{"id":"doi:10.1109/milcom58377.2023.10356250","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/milcom58377.2023.10356250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM)","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/A5083337940","display_name":"Bleema Rosenfeld","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bleema Rosenfeld","raw_affiliation_strings":["Peraton Labs Inc.,NJ,USA","Peraton Labs Inc., NJ, USA"],"affiliations":[{"raw_affiliation_string":"Peraton Labs Inc.,NJ,USA","institution_ids":[]},{"raw_affiliation_string":"Peraton Labs Inc., NJ, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109412228","display_name":"Sridhar Venkatesan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sridhar Venkatesan","raw_affiliation_strings":["Peraton Labs Inc.,NJ,USA","Peraton Labs Inc., NJ, USA"],"affiliations":[{"raw_affiliation_string":"Peraton Labs Inc.,NJ,USA","institution_ids":[]},{"raw_affiliation_string":"Peraton Labs Inc., NJ, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078482977","display_name":"Rauf Izmailov","orcid":"https://orcid.org/0000-0002-7326-669X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rauf Izmailov","raw_affiliation_strings":["Peraton Labs Inc.,NJ,USA","Peraton Labs Inc., NJ, USA"],"affiliations":[{"raw_affiliation_string":"Peraton Labs Inc.,NJ,USA","institution_ids":[]},{"raw_affiliation_string":"Peraton Labs Inc., NJ, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104219519","display_name":"Matthew Yudin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matthew Yudin","raw_affiliation_strings":["Peraton Labs Inc.,NJ,USA","Peraton Labs Inc., NJ, USA"],"affiliations":[{"raw_affiliation_string":"Peraton Labs Inc.,NJ,USA","institution_ids":[]},{"raw_affiliation_string":"Peraton Labs Inc., NJ, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006514612","display_name":"Constantin Serban","orcid":"https://orcid.org/0009-0000-7259-9460"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Constantin Serban","raw_affiliation_strings":["Peraton Labs Inc.,NJ,USA","Peraton Labs Inc., NJ, USA"],"affiliations":[{"raw_affiliation_string":"Peraton Labs Inc.,NJ,USA","institution_ids":[]},{"raw_affiliation_string":"Peraton Labs Inc., NJ, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103911831","display_name":"Ritu Chadha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ritu Chadha","raw_affiliation_strings":["Peraton Labs Inc.,NJ,USA","Peraton Labs Inc., NJ, USA"],"affiliations":[{"raw_affiliation_string":"Peraton Labs Inc.,NJ,USA","institution_ids":[]},{"raw_affiliation_string":"Peraton Labs Inc., NJ, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5083337940"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17994846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":null,"first_page":"7","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9990000128746033,"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":0.9970999956130981,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9943000078201294,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8134085536003113},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.7955628633499146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6580471992492676},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4264335632324219},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23124730587005615},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15477868914604187},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.06466025114059448}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8134085536003113},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.7955628633499146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6580471992492676},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4264335632324219},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23124730587005615},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15477868914604187},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.06466025114059448}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/milcom58377.2023.10356250","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/milcom58377.2023.10356250","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W9657784","https://openalex.org/W141304919","https://openalex.org/W1945616565","https://openalex.org/W2038296020","https://openalex.org/W2082190528","https://openalex.org/W2584957963","https://openalex.org/W2622074531","https://openalex.org/W2806039192","https://openalex.org/W2888328957","https://openalex.org/W3006800307","https://openalex.org/W3007481080","https://openalex.org/W3015481738","https://openalex.org/W3102844060","https://openalex.org/W3103836116","https://openalex.org/W3212419298","https://openalex.org/W4238893454","https://openalex.org/W4283825910","https://openalex.org/W4287615768","https://openalex.org/W6640425456","https://openalex.org/W6753850420","https://openalex.org/W6786190841","https://openalex.org/W6787959460"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119"],"abstract_inverted_index":{"Machine":[0],"learning":[1,53],"based":[2],"malware":[3,10,91],"detectors":[4,92],"can":[5,94],"identify":[6,158,209],"new":[7],"patterns":[8],"in":[9,50,82,97,133,146],"not":[11],"considered":[12],"by":[13,19,39],"classic":[14],"signature":[15],"matching":[16],"antivirus":[17],"software,":[18],"processing":[20],"features":[21,129,190],"extracted":[22],"from":[23,136],"cyber":[24,69],"artifacts.":[25],"However,":[26],"they":[27],"must":[28],"be":[29,95,104],"evaluated":[30],"for":[31,90,214],"robustness":[32],"against":[33],"adversarial":[34,88,205],"attacks":[35],"that":[36,93,118,130,221,229],"cause":[37],"mis-classifications":[38],"making":[40],"small":[41],"modifications":[42],"to":[43,47,76,103,106,111,157,184,208,226],"the":[44,51,63,67,77,98,112,134,137,141,147,162,187,194,210,224,235],"feature":[45,60,78,121,142,163,195],"values":[46,143],"exploit":[48],"weaknesses":[49],"machine":[52],"model\u2019s":[54],"decision":[55],"surface.":[56],"The":[57],"process":[58],"of":[59,193],"extraction":[61],"maps":[62],"problem":[64,114,138,148],"space,":[65,79],"or":[66],"actual":[68],"artifact":[70],"(e.g.":[71],"file,":[72],"network":[73],"flow":[74],"data),":[75],"often":[80],"resulting":[81],"dependencies":[83,127,188],"between":[84,128,189],"features.":[85],"To":[86],"learn":[87],"examples":[89],"realized":[96],"real":[99],"world,":[100],"we":[101],"need":[102],"able":[105],"map":[107],"feature-value":[108],"perturbations":[109],"back":[110],"original":[113],"space.":[115,149],"This":[116,174],"requires":[117],"1)":[119],"all":[120],"value":[122],"changes":[123],"are":[124,131,144,230],"consistent":[125],"with":[126],"inherent":[132],"mapping":[135],"space":[139,196,213],"2)":[140],"realizable":[145],"While":[150],"most":[151],"current":[152],"methods":[153],"require":[154],"expert":[155],"knowledge":[156],"these":[159],"constraints":[160],"on":[161],"values,":[164],"data-driven":[165],"constraint":[166,203],"mining":[167],"is":[168,199],"an":[169],"automatic":[170],"and":[171],"generalized":[172],"alternative.":[173],"work":[175],"identifies":[176],"Tabular":[177],"Constraint":[178],"Learning":[179],"(TaCLe)":[180],"as":[181],"a":[182,202,215],"method":[183],"automatically":[185],"mine":[186],"via":[191],"analysis":[192],"data.":[197],"TaCLe":[198],"incorporated":[200],"into":[201],"aware":[204],"attack":[206,225],"strategy":[207],"watermark":[211],"selection":[212],"backdoor":[216],"poisoning":[217],"attack.":[218],"We":[219],"find":[220,227],"it":[222],"enables":[223],"watermarks":[228],"70%":[231],"more":[232],"evasive":[233],"than":[234],"state-of-the-art":[236],"baseline.":[237]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}