{"id":"https://openalex.org/W3155862922","doi":"https://doi.org/10.1145/3442381.3449823","title":"Robust Network Alignment via Attack Signal Scaling and Adversarial Perturbation Elimination","display_name":"Robust Network Alignment via Attack Signal Scaling and Adversarial Perturbation Elimination","publication_year":2021,"publication_date":"2021-04-19","ids":{"openalex":"https://openalex.org/W3155862922","doi":"https://doi.org/10.1145/3442381.3449823","mag":"3155862922"},"language":"en","primary_location":{"id":"doi:10.1145/3442381.3449823","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449823","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3442381.3449823","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044123636","display_name":"Yang Zhou","orcid":"https://orcid.org/0000-0001-7839-4933"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yang Zhou","raw_affiliation_strings":["Auburn University, USA"],"affiliations":[{"raw_affiliation_string":"Auburn University, USA","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013305611","display_name":"Zeru Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zeru Zhang","raw_affiliation_strings":["Auburn University, USA"],"affiliations":[{"raw_affiliation_string":"Auburn University, USA","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103185340","display_name":"Sixing Wu","orcid":"https://orcid.org/0000-0001-7278-8720"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sixing Wu","raw_affiliation_strings":["Peking University, China"],"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051706630","display_name":"Victor S. Sheng","orcid":"https://orcid.org/0000-0003-4960-174X"},"institutions":[{"id":"https://openalex.org/I12315562","display_name":"Texas Tech University","ror":"https://ror.org/0405mnx93","country_code":"US","type":"education","lineage":["https://openalex.org/I12315562"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Victor Sheng","raw_affiliation_strings":["Texas Tech University, USA"],"affiliations":[{"raw_affiliation_string":"Texas Tech University, USA","institution_ids":["https://openalex.org/I12315562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079447591","display_name":"Xiaoying Han","orcid":"https://orcid.org/0000-0002-4586-3534"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoying Han","raw_affiliation_strings":["Auburn University, USA"],"affiliations":[{"raw_affiliation_string":"Auburn University, USA","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673890","display_name":"Zijie Zhang","orcid":"https://orcid.org/0000-0003-1254-098X"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zijie Zhang","raw_affiliation_strings":["Auburn University, USA"],"affiliations":[{"raw_affiliation_string":"Auburn University, USA","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103270436","display_name":"Ruoming Jin","orcid":"https://orcid.org/0000-0003-1895-4243"},"institutions":[{"id":"https://openalex.org/I149910238","display_name":"Kent State University","ror":"https://ror.org/049pfb863","country_code":"US","type":"education","lineage":["https://openalex.org/I149910238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruoming Jin","raw_affiliation_strings":["Kent State University, USA"],"affiliations":[{"raw_affiliation_string":"Kent State University, USA","institution_ids":["https://openalex.org/I149910238"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5044123636"],"corresponding_institution_ids":["https://openalex.org/I82497590"],"apc_list":null,"apc_paid":null,"fwci":1.6277,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.85627031,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3884","last_page":"3895"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9674999713897705,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9674999713897705,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9559999704360962,"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":0.8383933901786804},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6889488697052002},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5832457542419434},{"id":"https://openalex.org/keywords/threat-model","display_name":"Threat model","score":0.4569154381752014},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37845146656036377},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3369855284690857},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33191123604774475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32674479484558105},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.21869120001792908},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21300062537193298}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8383933901786804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6889488697052002},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5832457542419434},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.4569154381752014},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37845146656036377},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3369855284690857},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33191123604774475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32674479484558105},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.21869120001792908},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21300062537193298},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3442381.3449823","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449823","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3442381.3449823","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449823","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1987600084","https://openalex.org/W1993591232","https://openalex.org/W2027024265","https://openalex.org/W2058036501","https://openalex.org/W2078434063","https://openalex.org/W2106202847","https://openalex.org/W2145878380","https://openalex.org/W2165515835","https://openalex.org/W2251117138","https://openalex.org/W2254361149","https://openalex.org/W2261028762","https://openalex.org/W2293836743","https://openalex.org/W2774127592","https://openalex.org/W2777398797","https://openalex.org/W2783171635","https://openalex.org/W2788259657","https://openalex.org/W2792704806","https://openalex.org/W2793022729","https://openalex.org/W2914681971","https://openalex.org/W2949854114","https://openalex.org/W2953054275","https://openalex.org/W2964418074","https://openalex.org/W2964583308","https://openalex.org/W2964971928","https://openalex.org/W2984482968","https://openalex.org/W2985312488","https://openalex.org/W2993563049","https://openalex.org/W2997404190","https://openalex.org/W2998122931","https://openalex.org/W3002259362","https://openalex.org/W3007075380","https://openalex.org/W3007657110","https://openalex.org/W3008280430","https://openalex.org/W3008467772","https://openalex.org/W3012631161","https://openalex.org/W3012737746","https://openalex.org/W3012742206","https://openalex.org/W3026160437","https://openalex.org/W3034425924","https://openalex.org/W3036202927","https://openalex.org/W3081300507","https://openalex.org/W3081325717","https://openalex.org/W3101871847","https://openalex.org/W3127922526","https://openalex.org/W3138576342","https://openalex.org/W4313458796","https://openalex.org/W6711444580","https://openalex.org/W6758708736","https://openalex.org/W6785720548"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W2482350142","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4293790771"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"have":[2],"shown":[3],"that":[4,207],"graph":[5],"learning":[6],"models":[7],"are":[8,18],"highly":[9],"vulnerable":[10,141],"to":[11,22,109,136,143,166,170,192,211,216],"adversarial":[12,30,63,72,117,131,138,176,224],"attacks,":[13],"and":[14,80,156],"network":[15,27,44,54,125,172,218],"alignment":[16,28,45,55,173,219],"methods":[17,220],"no":[19],"exception.":[20],"How":[21],"enhance":[23],"the":[24,59,111,121,157,182,189,213],"robustness":[25],"of":[26,52,61,85,103,124,184],"against":[29,175,221],"attacks":[31,118],"remains":[32],"an":[33,93,130,185],"open":[34],"research":[35],"problem.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,66,128],"propose":[41],"a":[42,82,194],"robust":[43],"solution,":[46],"RNA,":[47],"for":[48,115,188],"offering":[49],"preemptive":[50,214],"protection":[51,169,215],"existing":[53,171],"algorithms,":[56],"enhanced":[57],"with":[58,99],"guidance":[60],"effective":[62,116],"attacks.":[64,177],"First,":[65],"analyze":[67],"how":[68],"popular":[69,223],"iterative":[70],"gradient-based":[71],"attack":[73,86,94,225],"techniques":[74,155],"suffer":[75],"from":[76],"gradient":[77,112],"vanishing":[78,113],"issues":[79,114],"show":[81],"fake":[83],"sense":[84],"effectiveness.":[87],"Based":[88],"on":[89,203],"dynamical":[90],"isometry":[91],"theory,":[92],"signal":[95,105],"scaling":[96,106],"(ASS)":[97],"method":[98,163],"established":[100],"upper":[101],"bound":[102],"feasible":[104],"is":[107,164,209],"introduced":[108],"alleviate":[110],"while":[119],"maintaining":[120],"decision":[122],"boundary":[123],"alignment.":[126],"Second,":[127],"develop":[129],"perturbation":[132],"elimination":[133],"(APE)":[134],"model":[135,191],"neutralize":[137],"nodes":[139,145],"in":[140,146],"space":[142],"adversarial-free":[144],"safe":[147],"area,":[148],"by":[149],"integrating":[150],"Dirac":[151],"delta":[152],"approximation":[153],"(DDA)":[154],"LSTM":[158],"models.":[159,226],"Our":[160],"proposed":[161],"APE":[162,190],"able":[165,210],"provide":[167],"proactive":[168],"algorithms":[174],"The":[178],"theoretical":[179],"analysis":[180],"demonstrates":[181],"existence":[183],"optimal":[186],"distribution":[187],"reach":[193],"lower":[195],"bound.":[196],"Last":[197],"but":[198],"not":[199],"least,":[200],"extensive":[201],"evaluation":[202],"real":[204],"datasets":[205],"presents":[206],"RNA":[208],"offer":[212],"trained":[217],"three":[222]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}