{"id":"https://openalex.org/W7082991005","doi":"https://doi.org/10.1109/tdsc.2025.3613425","title":"Meet Trick With Trick: Revealing Collusion Intentions in Highly Concealed Poisoning Behavior","display_name":"Meet Trick With Trick: Revealing Collusion Intentions in Highly Concealed Poisoning Behavior","publication_year":2025,"publication_date":"2025-09-23","ids":{"openalex":"https://openalex.org/W7082991005","doi":"https://doi.org/10.1109/tdsc.2025.3613425"},"language":"en","primary_location":{"id":"doi:10.1109/tdsc.2025.3613425","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tdsc.2025.3613425","pdf_url":null,"source":{"id":"https://openalex.org/S133795288","display_name":"IEEE Transactions on Dependable and Secure Computing","issn_l":"1545-5971","issn":["1545-5971","1941-0018","2160-9209"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Dependable and Secure Computing","raw_type":"journal-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":null,"display_name":"Zhihai Yang","orcid":"https://orcid.org/0000-0003-1590-2587"},"institutions":[{"id":"https://openalex.org/I4210115513","display_name":"Xi\u2019an University","ror":"https://ror.org/01zzmf129","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115513"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihai Yang","raw_affiliation_strings":["School of Data Science and Artificial Intelligence, Chang&#x2019;an University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-1590-2587","affiliations":[{"raw_affiliation_string":"School of Data Science and Artificial Intelligence, Chang&#x2019;an University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I4210115513"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yan Feng","orcid":"https://orcid.org/0009-0008-5399-2716"},"institutions":[{"id":"https://openalex.org/I4210115513","display_name":"Xi\u2019an University","ror":"https://ror.org/01zzmf129","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115513"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Feng","raw_affiliation_strings":["School of Data Science and Artificial Intelligence, Chang&#x2019;an University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0008-5399-2716","affiliations":[{"raw_affiliation_string":"School of Data Science and Artificial Intelligence, Chang&#x2019;an University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I4210115513"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jianxin Li","orcid":"https://orcid.org/0000-0002-9059-330X"},"institutions":[{"id":"https://openalex.org/I12079687","display_name":"Edith Cowan University","ror":"https://ror.org/05jhnwe22","country_code":"AU","type":"education","lineage":["https://openalex.org/I12079687"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jianxin Li","raw_affiliation_strings":["School of Business and Law, Edith Cowan University, Joondalup, WA, Australia"],"raw_orcid":"https://orcid.org/0000-0002-9059-330X","affiliations":[{"raw_affiliation_string":"School of Business and Law, Edith Cowan University, Joondalup, WA, Australia","institution_ids":["https://openalex.org/I12079687"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pinghui Wang","orcid":"https://orcid.org/0000-0001-5779-6108"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pinghui Wang","raw_affiliation_strings":["School of Cyber Science and Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-5779-6108","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhiquan Liu","orcid":"https://orcid.org/0000-0002-3934-2177"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiquan Liu","raw_affiliation_strings":["College of Cyber Security, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3934-2177","affiliations":[{"raw_affiliation_string":"College of Cyber Security, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210115513"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68873813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":"1","first_page":"997","last_page":"1015"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.2825999855995178,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.2825999855995178,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.0502999983727932,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13067","display_name":"Geological Modeling and Analysis","score":0.03909999877214432,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6680999994277954},{"id":"https://openalex.org/keywords/collusion","display_name":"Collusion","score":0.5903000235557556},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.558899998664856},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5486000180244446},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.5472999811172485},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.4887000024318695},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44179999828338623},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.4237000048160553},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.38089999556541443}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8529999852180481},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6680999994277954},{"id":"https://openalex.org/C2781198186","wikidata":"https://www.wikidata.org/wiki/Q701521","display_name":"Collusion","level":2,"score":0.5903000235557556},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.558899998664856},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5486000180244446},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.5472999811172485},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.5428000092506409},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4887000024318695},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44179999828338623},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43950000405311584},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.373199999332428},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3675000071525574},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C174839445","wikidata":"https://www.wikidata.org/wiki/Q1134386","display_name":"Lock (firearm)","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C84418412","wikidata":"https://www.wikidata.org/wiki/Q3246940","display_name":"Digital forensics","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C84976871","wikidata":"https://www.wikidata.org/wiki/Q2015673","display_name":"Openness to experience","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tdsc.2025.3613425","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tdsc.2025.3613425","pdf_url":null,"source":{"id":"https://openalex.org/S133795288","display_name":"IEEE Transactions on Dependable and Secure Computing","issn_l":"1545-5971","issn":["1545-5971","1941-0018","2160-9209"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Dependable and Secure Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.4772610664367676,"display_name":"Gender equality"}],"awards":[{"id":"https://openalex.org/G2574068435","display_name":null,"funder_award_id":"62172331","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8261579268","display_name":null,"funder_award_id":"300102404301","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1607114662","https://openalex.org/W1965667542","https://openalex.org/W1977290284","https://openalex.org/W1994042154","https://openalex.org/W2021487565","https://openalex.org/W2021644234","https://openalex.org/W2029424893","https://openalex.org/W2079466849","https://openalex.org/W2090679992","https://openalex.org/W2348679751","https://openalex.org/W2522690881","https://openalex.org/W2740792888","https://openalex.org/W2892160417","https://openalex.org/W2963305780","https://openalex.org/W2965683718","https://openalex.org/W3009800446","https://openalex.org/W3012794253","https://openalex.org/W3020878875","https://openalex.org/W3035523484","https://openalex.org/W3049662176","https://openalex.org/W3075585526","https://openalex.org/W3084442666","https://openalex.org/W3124264680","https://openalex.org/W3153182568","https://openalex.org/W3214009246","https://openalex.org/W3217255646","https://openalex.org/W4210377507","https://openalex.org/W4310731004","https://openalex.org/W4313730950","https://openalex.org/W4320148019","https://openalex.org/W4376132596","https://openalex.org/W4384891029","https://openalex.org/W4386728819","https://openalex.org/W4387342870","https://openalex.org/W4387618416","https://openalex.org/W4388208112","https://openalex.org/W4390904873","https://openalex.org/W4394785778","https://openalex.org/W4396736341","https://openalex.org/W4396757545","https://openalex.org/W4399891590","https://openalex.org/W4400984349","https://openalex.org/W4404811019","https://openalex.org/W4405778744"],"related_works":[],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"(RSs),":[2],"as":[3,291],"a":[4,119,156,176,324],"high":[5],"data-driven":[6],"application,":[7],"have":[8,41],"been":[9],"extensively":[10],"developed":[11],"and":[12,37,93,141,190,240,262,270,300],"widely":[13],"deployed":[14],"in":[15,19,103,180,199,264,317],"various":[16],"web":[17],"services,":[18],"order":[20],"to":[21,44,74,85,110,133,145,275],"help":[22],"users":[23,296],"locate":[24],"products":[25],"or":[26,64,314],"services":[27],"that":[28,123,194,307],"they":[29],"may":[30],"be":[31,86],"interested":[32],"in.":[33],"Meanwhile,":[34],"the":[35,45,68,77,95,147,206,308],"openness":[36],"vulnerability":[38],"of":[39,47,80,149,162,183,214,225,234,243,260,310],"RSs":[40],"given":[42],"rise":[43],"development":[46],"data":[48,66,192,311],"poisoning":[49,312],"attacks.":[50],"However,":[51],"defending":[52],"these":[53,125],"evolving":[54],"threats":[55],"presents":[56],"potential":[57],"challenges:":[58],"(a)":[59],"faced":[60],"with":[61,250,297],"highly":[62,89],"concealed":[63,90],"small-scale":[65],"poisoning,":[67],"attack":[69,81,163],"behavior":[70],"is":[71,83,106],"very":[72,107],"difficult":[73,84],"characterize;":[75],"(b)":[76],"identification":[78],"area":[79],"target":[82],"determined":[87],"for":[88,98,159,216,227,236,245,266],"injection":[91,101,230],"attacks;":[92],"(c)":[94],"prior":[96,276],"knowledge":[97,277],"detecting":[99,217,228,237,246],"fake":[100,173,315],"attacks":[102,248,313],"real":[104,191,288],"scenarios":[105,319],"limited.":[108],"Complementary":[109],"existing":[111],"works,":[112],"this":[113],"paper":[114],"proposes":[115],"<italic":[116,166],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[117,167,219],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">METT</i>,":[118],"divide-and-conquer":[120],"detection":[121,161],"method":[122,158],"addresses":[124],"fundamental":[126],"yet":[127],"underexplored":[128],"issues.":[129],"We":[130,153],"first":[131],"propose":[132],"exploit":[134],"causality":[135],"inference":[136],"based":[137,187],"on":[138,188,287],"both":[139],"group-level":[140],"individual-level":[142],"unfairness":[143],"sequences":[144],"enhance":[146],"reliability":[148],"user-item":[150],"symbiotic":[151],"associations.":[152],"then":[154],"develop":[155],"novel":[157],"early":[160],"target,":[164],"named":[165],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">ideaT</i>.":[168],"Finally,":[169],"we":[170,283,305],"further":[171],"discriminate":[172],"injections":[174,316],"using":[175],"disturbance":[177],"tolerance":[178],"mechanism":[179],"ambiguous":[181],"boundaries":[182],"behavior.":[184,303],"Extensive":[185],"experiments":[186],"synthetic":[189,280],"demonstrate":[193],"METT":[195,203,254],"outperforms":[196],"competing":[197,251],"baselines":[198],"different":[200],"cases.":[201],"Specifically,":[202],"can":[204],"reduce":[205],"false":[207],"alarm":[208],"rate":[209],"(FAR)":[210],"by":[211],"an":[212,223,232,241,257],"average":[213,224,233,242,258],"21%":[215],"<inline-formula":[218],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[220],"notation=\"LaTeX\">$\\mathcal":[221],"{S}$</tex-math></inline-formula>-attacks,":[222],"18%":[226],"profile":[229],"attacks,":[231,239,272],"26%":[235],"reverse":[238],"17%":[244],"optimal-injection":[247],"compared":[249],"benchmarks.":[252],"Moreover,":[253],"also":[255],"has":[256],"advantage":[259],"10%":[261],"20%":[263],"FARs":[265],"spotting":[267],"hybrid":[268],"promotion":[269],"demotion":[271],"respectively.":[273],"According":[274],"learned":[278],"from":[279,323],"data,":[281,289],"additionally,":[282],"discover":[284],"interesting":[285],"findings":[286],"such":[290],"suspicious":[292],"duplicate":[293,298],"behavior,":[294,299],"benign":[295],"identified":[301],"shilling":[302],"Importantly,":[304],"reveal":[306],"specificities":[309],"real-world":[318],"entail":[320],"important":[321],"implications":[322],"defense":[325],"perspective.":[326]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
