{"id":"https://openalex.org/W3007067381","doi":"https://doi.org/10.1109/bigdata47090.2019.9006562","title":"IoCMiner: Automatic Extraction of Indicators of Compromise from Twitter","display_name":"IoCMiner: Automatic Extraction of Indicators of Compromise from Twitter","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007067381","doi":"https://doi.org/10.1109/bigdata47090.2019.9006562","mag":"3007067381"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5011198056","display_name":"Amirreza Niakanlahiji","orcid":"https://orcid.org/0000-0002-7282-1575"},"institutions":[{"id":"https://openalex.org/I79884896","display_name":"University of Illinois at Springfield","ror":"https://ror.org/0126qma51","country_code":"US","type":"education","lineage":["https://openalex.org/I79884896"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Amirreza Niakanlahiji","raw_affiliation_strings":["University of Illinois at Springfield"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Springfield","institution_ids":["https://openalex.org/I79884896"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012118238","display_name":"Lida Safarnejad","orcid":"https://orcid.org/0000-0002-6377-7314"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lida Safarnejad","raw_affiliation_strings":["University of North Carolina at Charlotte"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082187860","display_name":"Reginald Harper","orcid":null},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reginald Harper","raw_affiliation_strings":["University of North Carolina at Charlotte"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111734614","display_name":"Bei-Tseng Chu","orcid":null},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bei-Tseng Chu","raw_affiliation_strings":["University of North Carolina at Charlotte"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte","institution_ids":["https://openalex.org/I102149020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011198056"],"corresponding_institution_ids":["https://openalex.org/I79884896"],"apc_list":null,"apc_paid":null,"fwci":3.1939,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.93372967,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2019","issue":null,"first_page":"4747","last_page":"4754"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12519","display_name":"Cybercrime and Law Enforcement Studies","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7736378312110901},{"id":"https://openalex.org/keywords/compromise","display_name":"Compromise","score":0.6333537697792053},{"id":"https://openalex.org/keywords/reputation","display_name":"Reputation","score":0.5425700545310974},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5097162127494812},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5044249296188354},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.4805603325366974},{"id":"https://openalex.org/keywords/haystack","display_name":"Haystack","score":0.4626823961734772},{"id":"https://openalex.org/keywords/sophistication","display_name":"Sophistication","score":0.45943304896354675},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.45898139476776123},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33325377106666565},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15495815873146057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7736378312110901},{"id":"https://openalex.org/C46355384","wikidata":"https://www.wikidata.org/wiki/Q726686","display_name":"Compromise","level":2,"score":0.6333537697792053},{"id":"https://openalex.org/C48798503","wikidata":"https://www.wikidata.org/wiki/Q877546","display_name":"Reputation","level":2,"score":0.5425700545310974},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5097162127494812},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5044249296188354},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4805603325366974},{"id":"https://openalex.org/C13424479","wikidata":"https://www.wikidata.org/wiki/Q5687237","display_name":"Haystack","level":2,"score":0.4626823961734772},{"id":"https://openalex.org/C168725872","wikidata":"https://www.wikidata.org/wiki/Q991663","display_name":"Sophistication","level":2,"score":0.45943304896354675},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.45898139476776123},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33325377106666565},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15495815873146057},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006562","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006562","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"mag:3041739266","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002245843452710","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.6200000047683716,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W9223698","https://openalex.org/W1594046544","https://openalex.org/W1707806712","https://openalex.org/W1968133322","https://openalex.org/W2076219102","https://openalex.org/W2084591134","https://openalex.org/W2130354913","https://openalex.org/W2397225306","https://openalex.org/W2767281261","https://openalex.org/W2896612858","https://openalex.org/W2908121058","https://openalex.org/W6637554470","https://openalex.org/W6755267338"],"related_works":["https://openalex.org/W4253878822","https://openalex.org/W1965563707","https://openalex.org/W4210692028","https://openalex.org/W1736550718","https://openalex.org/W2808729870","https://openalex.org/W2479343091","https://openalex.org/W2278064783","https://openalex.org/W2801622120","https://openalex.org/W3174858427","https://openalex.org/W1972480475"],"abstract_inverted_index":{"In":[0,124,232],"recent":[1],"years,":[2],"cyber":[3,30,45,73],"attacks":[4,17,36],"have":[5],"consistently":[6],"grown":[7],"in":[8,121,138,226,255,270],"terms":[9],"of":[10,20,102,141,149,181,207,224,235,249,262,266],"volume,":[11],"sophistication,":[12],"coordination,":[13],"and":[14,25,57,69,75,92,154,175],"pervasiveness.":[15],"Such":[16],"impose":[18],"billions":[19],"dollars":[21],"loss":[22],"to":[23,48,98,116,134,158,168,191,211,273],"companies":[24],"government":[26],"entities":[27],"annually.":[28],"Sharing":[29],"threat":[31],"intelligence":[32],"(CTI)":[33],"about":[34],"ongoing":[35],"can":[37],"significantly":[38],"improve":[39],"the":[40,81,99,178,198,215,222,233,250,260],"current":[41],"situation":[42],"as":[43,89],"many":[44,63],"attackers":[46],"tend":[47],"reuse":[49],"or":[50],"share":[51],"their":[52,67],"network":[53],"infrastructure,":[54],"techniques,":[55],"tactics,":[56],"procedures":[58],"across":[59],"multiple":[60],"attacks.":[61],"Therefore,":[62],"security":[64],"professionals":[65],"devote":[66],"time":[68,261],"effort":[70],"on":[71,108,164],"hunting":[72],"threats":[74],"sharing":[76,86,94],"such":[77,88,109,182],"valuable":[78],"information":[79,103,113],"with":[80],"public":[82,84,256],"through":[83],"data":[85,200],"platforms":[87],"social":[90],"media":[91],"text":[93,155],"websites.":[95],"However,":[96],"due":[97],"sheer":[100],"volume":[101],"that":[104,268],"is":[105,114],"being":[106],"shared":[107],"platforms;":[110],"finding":[111,227],"CTI":[112,189],"tantamount":[115],"looking":[117],"for":[118],"a":[119,122,129,147,165,188,205],"needle":[120],"haystack.":[123],"this":[125],"paper,":[126],"we":[127,220],"present":[128],"new":[130],"scalable":[131],"framework,":[132],"IoCMiner,":[133],"automatically":[135],"extract":[136,212],"CTI,":[137,174],"special":[139],"Indicators":[140],"Compromise,":[142],"from":[143,197,214,230],"Twitter.":[144,231],"It":[145],"utilizes":[146],"combination":[148],"graph":[150],"theory,":[151],"machine":[152],"learning,":[153],"mining":[156],"technique":[157],"achieve":[159],"its":[160],"goal.":[161],"IoCMiner":[162,225,238],"relies":[163],"reputation":[166],"model":[167],"discover":[169],"credible":[170],"twitterers":[171],"who":[172],"publish":[173],"only":[176],"tracks":[177],"tweet":[179],"stream":[180],"Twitter":[183],"handles.":[184],"Moreover,":[185],"it":[186],"employs":[187],"classifier":[190],"further":[192],"filter":[193],"out":[194],"non-CTI":[195],"tweets":[196],"observed":[199],"streams.":[201],"Finally,":[202],"IoCs":[203,213,229],"uses":[204],"set":[206],"regular":[208],"expression":[209],"rules":[210],"identifies":[216],"tweets.":[217],"Through":[218],"experimentation,":[219],"show":[221],"usefulness":[223],"fresh":[228],"course":[234],"four":[236],"weeks,":[237],"identified":[239],"more":[240],"than":[241],"1,200":[242],"IoCs,":[243],"including":[244],"malicious":[245],"URLs.":[246],"Only":[247],"10%":[248],"URLs":[251,267],"were":[252],"already":[253],"listed":[254],"blacklist":[257],"databases":[258],"at":[259],"extraction.":[263],"The":[264],"number":[265],"appeared":[269],"blacklists":[271],"increased":[272],"26%":[274],"after":[275],"one":[276],"week.":[277]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}