乐胖代购免代理版

{"id":"https://openalex.org/W2082116341","doi":"https://doi.org/10.1109/trustcom.2013.71","title":"Word N-Gram Based Classification for Data Leakage Prevention","display_name":"Word N-Gram Based Classification for Data Leakage Prevention","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2082116341","doi":"https://doi.org/10.1109/trustcom.2013.71","mag":"2082116341"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/trustcom.2013.71","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://www98.griffith.edu.au/dspace/bitstream/handle/10072/58407/89894_1.pdf%3Bjsessionid%3D4E480DC1752F1D0FFCB24F7B947A3016?sequence%3D1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032385385","display_name":"Sultan Alneyadi","orcid":null},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sultan Alneyadi","raw_affiliation_strings":["Faculty of Science, Environment, Engineering and Technology, Griffith University, Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Science, Environment, Engineering and Technology, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052346190","display_name":"Elankayer Sithirasenan","orcid":null},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Elankayer Sithirasenan","raw_affiliation_strings":["Faculty of Science, Environment, Engineering and Technology, Griffith University, Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Science, Environment, Engineering and Technology, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016915945","display_name":"Vallipuram Muthukkumarasamy","orcid":"https://orcid.org/0000-0002-6787-6379"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Vallipuram Muthukkumarasamy","raw_affiliation_strings":["Faculty of Science, Environment, Engineering and Technology, Griffith University, Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Science, Environment, Engineering and Technology, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.367,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":13,"citation_normalized_percentile":{"value":0.774276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":88},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Detection and Prevention of Phishing Attacks","score":0.9997,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Detection and Prevention of Phishing Attacks","score":0.9997,"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/T12380","display_name":"Authorship Attribution and User Profiling in Text","score":0.9994,"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/T11598","display_name":"Machine Learning for Internet Traffic Classification","score":0.9989,"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/n-gram","display_name":"n-gram","score":0.61805964},{"id":"https://openalex.org/keywords/spam-detection","display_name":"Spam Detection","score":0.526727},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.52527153},{"id":"https://openalex.org/keywords/traffic-analysis","display_name":"Traffic Analysis","score":0.519323},{"id":"https://openalex.org/keywords/user-profiling","display_name":"User Profiling","score":0.514492},{"id":"https://openalex.org/keywords/data-classification","display_name":"Data classification","score":0.4304431}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71451813},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.61805964},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.604903},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5563944},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.52527153},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.44129536},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.4304431},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39685887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32664388},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08308399},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/trustcom.2013.71","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1022.4794","pdf_url":"http://www98.griffith.edu.au/dspace/bitstream/handle/10072/58407/89894_1.pdf%3Bjsessionid%3D4E480DC1752F1D0FFCB24F7B947A3016?sequence%3D1","source":{"id":"https://openalex.org/S4306400349","display_name":"CiteSeer X (The Pennsylvania State University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I130769515","host_organization_name":"Pennsylvania State University","host_organization_lineage":["https://openalex.org/I130769515"],"host_organization_lineage_names":["Pennsylvania State University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1022.4794","pdf_url":"http://www98.griffith.edu.au/dspace/bitstream/handle/10072/58407/89894_1.pdf%3Bjsessionid%3D4E480DC1752F1D0FFCB24F7B947A3016?sequence%3D1","source":{"id":"https://openalex.org/S4306400349","display_name":"CiteSeer X (The Pennsylvania State University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I130769515","host_organization_name":"Pennsylvania State University","host_organization_lineage":["https://openalex.org/I130769515"],"host_organization_lineage_names":["Pennsylvania State University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions","score":0.63}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":10,"referenced_works":["https://openalex.org/W123495503","https://openalex.org/W1451710050","https://openalex.org/W1500993918","https://openalex.org/W1533946607","https://openalex.org/W1848186183","https://openalex.org/W1868244547","https://openalex.org/W2079656678","https://openalex.org/W2103078852","https://openalex.org/W25636905","https://openalex.org/W31943548"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W4237719335","https://openalex.org/W4236073812","https://openalex.org/W3126081632","https://openalex.org/W3048777016","https://openalex.org/W2906970013","https://openalex.org/W2902593166","https://openalex.org/W2804364458","https://openalex.org/W2132641928","https://openalex.org/W2090259340"],"abstract_inverted_index":{"Revealing":[0],"sensitive":[1,60,66,96,161],"data":[2,22,47,61,67,88,138],"to":[3,10,16,35,55,150,155,170],"unauthorised":[4],"personal":[5],"is":[6,78,93,143],"a":[7],"serious":[8],"problem":[9],"many":[11],"organizations":[12],"that":[13],"can":[14,114],"lead":[15],"devastating":[17],"consequences.":[18],"Traditionally,":[19],"prevention":[20,49],"of":[21,37,70,84,99,135,160,168],"leak":[23],"was":[24],"achieved":[25],"through":[26],"firewalls,":[27],"VPNs":[28],"and":[29,58,64,107,125,157,177],"IDS,":[30],"but":[31],"without":[32],"much":[33],"consideration":[34],"sensitivity":[36],"the":[38,71,82,133,147,166,172],"data.":[39,97,162],"In":[40,128],"recent":[41],"years,":[42],"new":[43],"technologies":[44],"such":[45,119],"as":[46,120],"leakage":[48,159],"systems":[50],"(DLPs)":[51],"are":[52,101],"developed,":[53],"especially":[54],"either":[56],"identify":[57],"protect":[59],"or":[62,89],"monitor":[63],"detect":[65,156],"leakage.":[68],"One":[69],"most":[72],"popular":[73],"approaches":[74],"used":[75],"in":[76,153],"DLPs":[77],"content":[79,83],"analysis,":[80],"where":[81],"exchanged":[85],"documents,":[86],"stored":[87],"even":[90],"network":[91],"traffic":[92],"monitored":[94],"for":[95,137],"Contents":[98],"documents":[100,152,176],"examined":[102],"using":[103,117,146],"mainly":[104],"text":[105,108,112],"analysis":[106,113],"clustering":[109],"methods.":[110],"Moreover,":[111],"be":[115],"performed":[116],"methods":[118],"pattern":[121],"recognition,":[122],"style":[123],"variation":[124],"N-gram":[126],"frequency.":[127],"this":[129],"paper,":[130],"we":[131],"investigate":[132],"use":[134],"N-grams":[136,148,169],"classification":[139],"purposes.":[140],"Our":[141],"method":[142],"based":[144],"on":[145],"frequency":[149],"classify":[151],"order":[154],"prevent":[158],"We":[163],"have":[164],"studied":[165],"effectiveness":[167],"measure":[171],"similarity":[173],"between":[174],"regular":[175],"existing":[178],"classified":[179],"documents.":[180]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2082116341","counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1}],"updated_date":"2024-11-24T14:11:29.316053","created_date":"2016-06-24"}