{"id":"https://openalex.org/W3091441586","doi":"https://doi.org/10.1145/3377811.3380379","title":"Dissector","display_name":"Dissector","publication_year":2020,"publication_date":"2020-06-27","ids":{"openalex":"https://openalex.org/W3091441586","doi":"https://doi.org/10.1145/3377811.3380379","mag":"3091441586"},"language":"en","primary_location":{"id":"doi:10.1145/3377811.3380379","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377811.3380379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering","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/A5014346076","display_name":"Huiyan Wang","orcid":"https://orcid.org/0000-0002-7942-605X"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huiyan Wang","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101817758","display_name":"Jingwei Xu","orcid":"https://orcid.org/0000-0003-0407-0797"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingwei Xu","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052203980","display_name":"Chang Xu","orcid":"https://orcid.org/0000-0002-6299-4704"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Xu","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041674680","display_name":"Xiaoxing Ma","orcid":"https://orcid.org/0000-0001-7970-1384"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxing Ma","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103122917","display_name":"Jian L\u00fc","orcid":"https://orcid.org/0000-0002-2857-153X"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Lu","raw_affiliation_strings":["Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5014346076"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":5.1698,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.96244711,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"727","last_page":"738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9932000041007996,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7678682208061218},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6762402057647705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6140719652175903},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5356665849685669},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4977004826068878},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48198193311691284},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4798666834831238},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4714950919151306},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32368946075439453}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7678682208061218},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6762402057647705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6140719652175903},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5356665849685669},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4977004826068878},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48198193311691284},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4798666834831238},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4714950919151306},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32368946075439453},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3377811.3380379","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3377811.3380379","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W251835054","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1992479406","https://openalex.org/W2081739138","https://openalex.org/W2097117768","https://openalex.org/W2099419573","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2156387975","https://openalex.org/W2165073069","https://openalex.org/W2180612164","https://openalex.org/W2194775991","https://openalex.org/W2243397390","https://openalex.org/W2257979135","https://openalex.org/W2342840547","https://openalex.org/W2401231614","https://openalex.org/W2402007731","https://openalex.org/W2437990191","https://openalex.org/W2504108613","https://openalex.org/W2531327146","https://openalex.org/W2533523411","https://openalex.org/W2543296129","https://openalex.org/W2543927648","https://openalex.org/W2546302380","https://openalex.org/W2549139847","https://openalex.org/W2565186948","https://openalex.org/W2594867206","https://openalex.org/W2594877703","https://openalex.org/W2612866063","https://openalex.org/W2614635052","https://openalex.org/W2616028256","https://openalex.org/W2624172162","https://openalex.org/W2759465730","https://openalex.org/W2775273147","https://openalex.org/W2799640043","https://openalex.org/W2800040198","https://openalex.org/W2804337238","https://openalex.org/W2809182766","https://openalex.org/W2867167548","https://openalex.org/W2888307014","https://openalex.org/W2888824816","https://openalex.org/W2896556344","https://openalex.org/W2898868990","https://openalex.org/W2941345940","https://openalex.org/W2953466973","https://openalex.org/W2954629067","https://openalex.org/W2954678575","https://openalex.org/W2962700793","https://openalex.org/W2963077879","https://openalex.org/W2963207607","https://openalex.org/W2963249138","https://openalex.org/W2963327228","https://openalex.org/W2963341057","https://openalex.org/W2963389226","https://openalex.org/W2963446712","https://openalex.org/W2963693742","https://openalex.org/W2963735478","https://openalex.org/W2963857521","https://openalex.org/W2964082701","https://openalex.org/W2964137095","https://openalex.org/W2964153729","https://openalex.org/W2964164993","https://openalex.org/W2978329087","https://openalex.org/W3099444373","https://openalex.org/W3104371626","https://openalex.org/W3105599650","https://openalex.org/W3118608800","https://openalex.org/W3142239405","https://openalex.org/W4285071988","https://openalex.org/W4300435436"],"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/W4310988119"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"(DL)":[2],"applications":[3,21,39,84],"are":[4,73],"becoming":[5],"increasingly":[6],"popular.":[7],"Their":[8],"reliabilities":[9],"largely":[10],"depend":[11],"on":[12],"the":[13,32,38,46,76,83,116,152],"performance":[14],"of":[15,93],"DL":[16,98,127,185],"models":[17,33,128],"integrated":[18],"in":[19,115,121,130,151,174,189],"these":[20],"as":[22],"a":[23,55,97,102,108,184],"central":[24],"classifying":[25],"module.":[26],"Traditional":[27],"techniques":[28,150],"need":[29],"to":[30,60,126,136,159,192],"retrain":[31],"or":[34],"rebuild":[35],"and":[36,132,157,161,182,196],"redeploy":[37],"for":[40,194,198],"coping":[41],"with":[42,87,104],"unexpected":[43,66],"conditions":[44,67],"beyond":[45],"models'":[47,77],"handling":[48,78],"capabilities.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"take":[54],"fault":[56],"tolerance":[57],"approach,":[58],"Dissector,":[59],"distinguishing":[61],"those":[62],"inputs":[63,71,178],"that":[64,72,96,146],"represent":[65],"(beyond-inputs)":[68],"from":[69,139],"normal":[70],"still":[74,85],"within":[75],"capabilities":[79],"(within-inputs),":[80],"thus":[81],"keeping":[82],"function":[86],"expected":[88],"reliabilities.":[89],"The":[90,142],"key":[91],"insight":[92],"Dissector":[94,119,147],"is":[95],"model":[99],"should":[100],"interpret":[101],"within-input":[103],"increasing":[105],"confidence,":[106],"while":[107],"beyond-input":[109],"would":[110],"probably":[111],"cause":[112],"confused":[113],"guesses":[114],"prediction":[117],"process.":[118],"works":[120],"an":[122],"application-specific":[123],"way,":[124],"adaptive":[125],"used":[129],"applications,":[131],"extremely":[133],"efficiently,":[134],"scalable":[135],"large-size":[137],"datasets":[138],"complex":[140],"scenarios.":[141],"experimental":[143],"evaluation":[144],"shows":[145],"outperformed":[148],"state-of-the-art":[149],"effectiveness":[153],"(AUC:":[154,179],"avg.":[155,180],"0.8935":[156],"up":[158],"0.9894)":[160],"efficiency":[162],"(runtime":[163],"overhead:":[164],"only":[165],"3.3--5.8":[166],"milliseconds).":[167],"Besides,":[168],"it":[169],"also":[170],"exhibited":[171],"encouraging":[172],"usefulness":[173],"defensing":[175],"against":[176],"adversarial":[177],"0.9983)":[181],"improving":[183],"model's":[186],"actual":[187],"accuracy":[188],"use":[190],"(up":[191],"16%":[193],"CIFAR-100":[195],"20%":[197],"ImageNet).":[199]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2020-10-08T00:00:00"}