{"id":"https://openalex.org/W4387635128","doi":"https://doi.org/10.48550/arxiv.2310.07980","title":"GRASP: Accelerating Shortest Path Attacks via Graph Attention","display_name":"GRASP: Accelerating Shortest Path Attacks via Graph Attention","publication_year":2023,"publication_date":"2023-10-12","ids":{"openalex":"https://openalex.org/W4387635128","doi":"https://doi.org/10.48550/arxiv.2310.07980"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2310.07980","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.07980","pdf_url":"https://arxiv.org/pdf/2310.07980","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2310.07980","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shafi, Zohair","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shafi, Zohair","raw_affiliation_strings":["Northeastern University , Boston , MA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Boston , MA USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102934256","display_name":"Benjamin A. Miller","orcid":"https://orcid.org/0000-0002-1649-1401","observed_orcids":["https://orcid.org/0000-0002-1649-1401"]},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Miller, Benjamin A.","raw_affiliation_strings":["Northeastern University , Boston , MA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Boston , MA USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008184102","display_name":"Ayan Chatterjee","orcid":"https://orcid.org/0000-0002-8016-0965","observed_orcids":["https://orcid.org/0000-0002-8016-0965"]},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chatterjee, Ayan","raw_affiliation_strings":["Northeastern University , Boston , MA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Boston , MA USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080731595","display_name":"Tina Eliassi\u2010Rad","orcid":"https://orcid.org/0000-0002-1892-1188","observed_orcids":["https://orcid.org/0000-0002-1892-1188"]},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eliassi-Rad, Tina","raw_affiliation_strings":["Northeastern University , Boston , MA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Boston , MA USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007510609","display_name":"Rajmonda S. Caceres","orcid":"https://orcid.org/0000-0003-2236-4406","observed_orcids":["https://orcid.org/0000-0003-2236-4406"]},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Caceres, Rajmonda S.","raw_affiliation_strings":["MIT Lincoln Laboratory , Lexington MA , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratory , Lexington MA , USA","institution_ids":["https://openalex.org/I4210122954"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.513700008392334,"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.513700008392334,"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":0.16040000319480896,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.08540000021457672,"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/edge-deletion","display_name":"edge deletion","score":0.7599999904632568},{"id":"https://openalex.org/keywords/graph-attention-networks","display_name":"graph attention networks","score":0.8069999814033508},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.6050000190734863},{"id":"https://openalex.org/keywords/node-attributes","display_name":"node attributes","score":0.5230000019073486}],"concepts":[{"id":"https://openalex.org/C22590252","wikidata":"https://www.wikidata.org/wiki/Q1058754","display_name":"Shortest path problem","level":3,"score":0.7646234631538391},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.6988322734832764},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6852281093597412},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5859560966491699},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.48091384768486023},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4659579396247864},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3758239150047302},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3412816524505615},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1967407464981079},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2310.07980","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.07980","pdf_url":"https://arxiv.org/pdf/2310.07980","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2310.07980","doi":"https://doi.org/10.48550/arxiv.2310.07980","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2310.07980","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2310.07980","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.07980","pdf_url":"https://arxiv.org/pdf/2310.07980","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4694536500","display_name":null,"funder_award_id":"FA8702-15-D-0001","funder_id":"https://openalex.org/F4320309369","funder_display_name":"Massachusetts Institute of Technology"}],"funders":[{"id":"https://openalex.org/F4320309369","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387635128.pdf","grobid_xml":"https://content.openalex.org/works/W4387635128.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W4386607418"],"related_works":["https://openalex.org/W4386811795","https://openalex.org/W7167556979","https://openalex.org/W4411745419","https://openalex.org/W3033107996","https://openalex.org/W7169521611","https://openalex.org/W4414938953","https://openalex.org/W7135636953","https://openalex.org/W2922429874","https://openalex.org/W3106318401","https://openalex.org/W4393161244"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,9,24,75,162],"machine":[3],"learning":[4],"(ML)":[5],"have":[6],"shown":[7],"promise":[8],"aiding":[10],"and":[11],"accelerating":[12],"classical":[13],"combinatorial":[14,129],"optimization":[15,99,156,164],"algorithms.":[16],"ML-based":[17],"speed":[18],"ups":[19],"that":[20,46,101,151],"aim":[21],"to":[22,27,36,49,71,106,122],"learn":[23],"an":[25,64,68,96],"end":[26,28],"manner":[29],"(i.e.,":[30],"directly":[31],"output":[32],"the":[33,80,87,111,128,134,145,155,163],"solution)":[34],"tend":[35],"trade":[37],"off":[38],"run":[39,103],"time":[40],"with":[41,154],"solution":[42,114],"quality.":[43],"Therefore,":[44],"solutions":[45],"are":[47,58],"able":[48],"accelerate":[50],"existing":[51],"solvers":[52],"while":[53,109],"maintaining":[54,110],"their":[55],"performance":[56],"guarantees,":[57],"of":[59,83,113,144],"great":[60],"interest.":[61],"We":[62,85],"consider":[63],"APX-hard":[65],"problem,":[66],"where":[67],"adversary":[69],"aims":[70],"attack":[72],"shortest":[73],"paths":[74],"a":[76,118,124],"graph":[77,119],"by":[78],"removing":[79],"minimum":[81],"number":[82],"edges.":[84],"propose":[86],"GRASP":[88,116],"algorithm:":[89],"Graph":[90],"Attention":[91],"Accelerated":[92],"Shortest":[93],"Path":[94],"Attack,":[95],"ML":[97],"aided":[98],"algorithm":[100],"achieves":[102],"times":[104],"up":[105],"10x":[107],"faster,":[108],"quality":[112],"generated.":[115],"uses":[117],"attention":[120],"network":[121],"identify":[123],"smaller":[125],"subgraph":[126],"containing":[127],"solution,":[130],"thus":[131],"effectively":[132],"reducing":[133],"input":[135,146],"problem":[136],"size.":[137],"Additionally,":[138],"we":[139],"demonstrate":[140],"how":[141],"careful":[142],"representation":[143],"graph,":[147],"including":[148],"node":[149],"features":[150],"correlate":[152],"well":[153],"task,":[157],"can":[158],"highlight":[159],"important":[160],"structure":[161],"solution.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2023-10-14T00:00:00"}