互联网青少年网络犯罪外文翻译文献（英文+中文）

文献信息文献标题：JuvenileDelinquencyintheVirtualWorld:SimilaritiesandDifferencesbetweenCyber-Enabled,Cyber-DependentandOfflineDelinquentsintheNetherlands（虚拟世界中的青少年犯罪:荷兰使用网络犯罪、依赖网络犯罪和线下犯罪的异同）文献作者：JosjaJ.Rokven等文献出处：《InternationalJournalofCyberCriminology》,2018.12(1):27–46.字数统计：英文3172单词，18497字符；中文5758汉字外文文献　JuvenileDelinquencyintheVirtualWorld:SimilaritiesandDifferencesbetweenCyber-Enabled,Cyber-DependentandOfflineDelinquentsintheNetherlandsAbstractThisstudyexaminessimilaritiesanddifferencesbetweenjuveniledelinquentsofself-reportedcyber-enabledoffenses,cyber-dependentoffenses,andofflineoffenses.ThestudybuildsonpaststudiesbyexaminingabroadrangeofonlineandofflineoffensesamonganationalprobabilitysampleofDutchjuvenilesaged12-17yearsold.Resultsshowthatjuvenileswhoreportbothofflineandonlineoffenseshavethemosthigh-riskprofile.Withinthegrouponlinedelinquents,juvenileswhocommitbothcyber-dependentandcyber-enabledoffenseshavethehighestriskprofile.Theresultsfurtherindicatethatcyber-dependentdelinquentsareadistinctgroupfromonlinedelinquents.Keywords:Onlineoffending,cybercrime,cyber-dependentcrime,cyber-enabledcrime,riskandpromotivefactors.IntroductionSince2007policecensusdatahaveshownasharpdeclineinjuvenilecrimeintheNetherlands(VanderLaan&Goudriaan,2016).Becauseofthiscrimedrop,theurgencytodealwithjuvenilecrimeseemstohavedecreased,andthefocushasshiftedtomorespecificformsofcrime,suchashighimpactcrimes.However,officialstatisticsrelateprimarilytotraditionalofflineoffenses.Onepossibleexplanationfortheobservedcrimedropisthatjuvenileshaveshiftedfromcommittingtraditionalofflineoffensestoonlineoffenses(Tchernietal.,2016).Withthedigitalizationofsociety,newwaystocommittraditionalofflineoffenseshaveemerged,aswellasopportunitiestocommitnewtypesofoffensesonline.Thisraisesthequestionastowhether‘streetcriminals’havegoneonline,orwhetherwearedealingwithanewtypeofdelinquent.Previousresearchdistinguishestwotypesofonlinedelinquency:cyber-enabledandcyber-dependentdelinquency(Holt&Bossler,2016;McGuire&Dowling,2013).Cyber-enableddelinquencyrefersto‘traditional’offensesthatarecommittedusingInformationCommunicationTechnology(ICT),andincludesactssuchasonlinefraud,extortion,andonlinestalking.Cyber-dependentdelinquencyreferstooffensesthatcanonlybecommittedusingICTandthatareprimarilydirectedagainstcomputerornetworkresources.Thisincludesactssuchashacking,distributingviruses,andorchestratingDDoS-attacks.Inanattempttobetterunderstandwhatkindofindividualisinvolvedinonlinedelinquency,scholarshavenowstartedtoexaminecorrelatesofonlinedelinquencyandtheirdifferencesandcommunalitieswithcorrelatesofofflinedelinquency.Themajorityofpreviousstudieshavelimitedtheirfocustoeitheroneor,atmost,asmallnumberofonlineoffenses.Regardingcyber-enableddelinquency,researchhasfocusedonoffensessuchasbullyingandonlineharassment(e.g.,Kerstens&Veenstra,2015;Raskauskas&Stolz,2007;Ybarra&Mitchell,2004),onlinechildpornography(foranoverview,seeBabchishin,Hanson&Hermann,2010),anddigitalpiracy(e.g.,Brunton-Smith&McCarthy,2016;Higgins,2005;Higgins,Fell&Wilson,2006;Wolfe&Higgins,2009).Withregardtocyber-dependentoffenses,moststudieshavefocusedonhacking(e.g.,Bossler&Burruss,2011;Kheyetal.,2009;Yar,2005a).Tothebestofourknowledge,onlyonestudyhasfocusedonabroaderrangeofonlineoffenses,whilstalsoincludingofflineoffenses(Donner,Jennings&Banfield,2015).Donnerandcolleaguesfoundthatonlinedelinquentswereoftenpronetoofflinedelinquencyaswell.However,thesefindingsarebasedonasamplefromaspecificpopulation,namelyundergraduatecollegestudentsintheUS.Thequestioniswhethertheirresultscanbegeneralizedtoanationalprobabilitysampleofjuveniles.Inthecurrentstudy,webuildonpreviousresearchbyfirstinvestigatingtheextenttowhichcyber-enabledandcyber-dependentdelinquentsdifferfromeachother,andsecondlytheextenttowhichtheydifferfromofflinedelinquents.Studyingtypesofonlinedelinquentsandtheirsimilaritiesanddifferenceswithtraditionalofflinedelinquentsisimportant,becauseifonlinedelinquentsaresimilartoofflinedelinquents,thesamepreventionmethodscouldbeusedforboth.However,ifdifferencesemergewithinandbetweengroups,differentapproachesregardingpreventionandforensictreatmentmayberequired.Tostudypotentialdifferencesbetweencyber-enabled,cyber-dependent,andofflinedelinquents,weusedtheYouthDelinquencySurvey(YDS),across-sectionalself-reportedstudyonanationalprobabilitysampleofjuvenilesfromtheNetherlands(seeVanderLaan,Blom&Kleemans,2009).TheYDScontainsdetailedinformationonbothself-reportedonlineandofflinedelinquency,andonriskandpromotivefactorsthatarerelatedtotraditionalofflinedelinquency.Riskfactorsincreasethelikelihoodofdelinquency,whereaspromotivefactorsdecreasethislikelihood.Determiningthedifferencesbetweencyber-enabledandcyber-dependentdelinquents,anddeterminingtheextenttowhichonlinedelinquentsdifferfromofflinedelinquents,isdonebyexaminingtheseriskandpromotivefactors.Themainresearchquestionsofthisstudyare:Whatdistinguishesjuveniledelinquentsofcyber-enabledoffensesfromjuveniledelinquentsofcyber-dependentoffenses?Whatdistinguishesjuveniledelinquentsofonlineoffensesfromjuveniledelinquentsofofflineoffenses?1.Theory1.1.RiskFactorModelTheriskfactormodelisbasedonthe(bio)socialecologicalmodelofBronfenbrenner(1979).Thegeneralideabehindthismodelisthatdifferentdomainsinfluencethelikelihoodofantisocialanddelinquentbehavior(Farrington,2003;Lipsey&Derzon,1998;Loeberetal.,2008).Thedomainsaregenerallyorganizedintofivebroadercategories:theindividual,family,school,peers,andthecommunitydomain.Avarietyoffactorshavebeenfoundtoincreasethelikelihoodofdelinquentbehavior.Individualriskfactorsincludeimpulsivityordefectivemoralbeliefs(Agnew,2003;Farrington,2003),unstructuredroutineactivitieswithoutthesupervisionofparents(Osgood&Anderson2004;Osgoodetal.,1996),and(excessive)substanceuse(Felson,1998).Anotherimportantriskfactorisself-control.Self-controlhasbeendemonstratedtobeoneofthemostinfluentialcorrelatesoftraditionalcrime,andhasalsofrequentlybeenappliedtovariousformsofcybercrime(e.g.,Bossler&Burrus,2011;Higgins,2005).Next,certainonlineactivitiesmayplaceindividualsatriskforonlinedelinquency.Paststudiessuggestthatmoreadvancedformsofcyber-dependentcrimes,suchashacking,mayrequirehigherlevelsofcomputerskills(Bossler&Burrus,2011;Xu,Hu&Zhang,2013).Afactorthatmayfavorthedevelopmentoftheseskillsisgaming;juveniles,whofrequentlyplayonlinegames,maydevelopmoreonlineskills,whicharenecessaryforthe(successful)pursuitofcyber-crimes(Xu,Hu&Zhang,2013).Inthefamilydomain,poorparentalbonding,littleopennesstoparents,andthelackofparentalsupervisionhavebeenfoundtopredictdelinquency(Rutter,Giller&Hagell,1998;Stattin&Kerr,2000).Intheschooldomain,pooracademicperformanceandlowattachmenttoschoolareexamplesofriskfactors(Junger&HaenMarshall,1997;Mason&Windle,2002).Thedelinquentbehavioroffriendsisconsideredanimportantriskfactorinthepeerdomain(Warr,1993;Weerman,2011),andpovertyandcommunitydisorganizationareexamplesofriskfactorsinthecommunitydomain(Hawkinsetal.,2000).Inadditiontoriskfactors,scholarshavealsoidentifiedpromotivefactors(Farringtonetal.,2008;Sameroffetal.,1998).Promotivefactorsreducethelikelihoodofnegativeoutcomes,andcancounterbalanceriskfactors.Assuch,promotivefactorscan(partially)explainwhynotalljuvenilesthatareexposedtoriskfactorsbecomeinvolvedinantisocialordelinquentbehavior(Farrington&Welsh,2007;Loeberetal.,2008).Examplesofpromotivefactorsarestrongsocialbonds,pro-socialnorms,parentalsupport,andastrongattachmenttoschool(Catalanoetal.,2004).Researchhasshownthattheaccumulationofriskfactorsacrossmultipledomainsincreasesthelikelihoodofnegativeoutcomes,includingantisocialanddelinquentbehavior(Loeberetal.,2008;Stouthamer-Loeberetal.,2002).Studiesonpromotivefactorsshowthatanaccumulationofpromotivefactorsreducesthelikelihoodofnegativeoutcomes(Farringtonetal.,2008;Sameroffetal.,1998).Becausepromotivefactorshavetheabilitytobufferthenegativeinfluencesofrisks,scholarshavealsoexaminedthecumulativeimpactofriskandpromotivefactorsacrossdifferentdomains.Overall,themoreriskfactorsandthefewerpromotivefactorspresent,thehigherthelikelihoodthatindividualsengagein(serious)delinquentbehavior(e.g.,Stouthamer-Loeberetal.,2002;VanderLaanetal.,2010).Assuch,weexpectjuvenileswhocommitseveraltypesofoffenses,bothonlineandoffline,themostseriousdelinquents,tobecharacterizedbythehighestriskprofile(i.e.,mostriskfactorsandfewestpromotivefactors).1.2.TheCurrentStudyInthisstudy,wefirstexaminethedifferencesbetweenself-reportedcyber-enabledandcyber-dependentdelinquentsonriskandpromotivefactors,distinguishingbetweenfactorsintheindividual,family,peerandschooldomain.Secondly,wetestwhethertheseonlinedelinquentsdifferfromofflinedelinquentsonthesefactors.Sofar,researchononlinedelinquencyhasmostlyfocusedonasingletypeorlimitednumberofonlineoffenses,and/orarebasedonsamplesofstudentpopulations.Ourstudybuildsonandextendsthisbodyofliteraturebyexaminingabroaderrangeofcyber-enabled,cyber-dependent,andofflineoffensesamonganationalprobabilitysampleofjuveniles.Thisway,weareabletoprovideamorecomprehensivepictureofdifferenttypesofonlinedelinquents,andtheirdifferenceswithofflinedelinquents.Forthispurpose,wefocusonavarietyofriskandpromotivefactorsderivedfromtheriskfactormodel,andalsoinvestigatethecumulativeimpactoftheseriskandpromotivefactorsacrossdifferentdomains.2.DataandMethodsWeuseddatafromthemostrecentwave(2015)oftheYDS.TheYDSisacross-sectional,self-reportstudy,conductedeveryfiveyearsamonganationalprobabilitysampleofDutchjuveniles,agedbetween10and23years.WithintheYDS,arandomstratifiedsamplingmethodwasfollowed.Theinitialsamplewasdividedinto30strata,definedbyageandethnicorigin,followedbyarandomselectionofjuvenilesfromtheMunicipalPopulationRegister.Ethnicminorities(Turks,Moroccans,SurinameseandAntilleans/Arubans)andjuvenilesundertwelve(10and11-year-olds)wereoversampled,asthesegroupstendtobelesslikelytoparticipateinsurveyresearch.Inthecurrentstudy,wefocusedsolelyonminorsagedbetween12to17years.Weexcludedjuvenilesundertheageoftwelve,astheseindividualscannotbeprosecutedbythejuvenilejusticesystemintheNetherlands.Youngadults(18-to23-year-olds)werealsoexcluded,astheseindividualsareprosecutedbytheadultjusticesystemintheNetherlands.BetweenJanuaryandJune2015,atotalof2,207juveniles,agedbetween12and17years,wereapproachedtoparticipateinthestudy.Withanunweightedresponserateof61.8%,thefinalsampleconsistedof1,365juveniles.Thesamplewaslargelyrepresentativeofthetargetpopulations.JuvenilesfromTurkishandMoroccanoriginwerelesslikelytoparticipateinthestudy(responseratesrespectively52.2%and56.2%).However,thisunderrepresentationissmallenoughthatthedatacanbeconsideredrepresentativeforthesegroupsasawhole(Engelen,Roels&deHeij,2015).ThedataweregatheredbymeansofComputerAssistedPersonalInterviews(CAPI)andComputerAssistedSelfInterviews(CASI),withCASIbeingusedforquestionsaboutsensitiveinformation,includingself-reporteddelinquency.2.1DependentVariablesTomeasuredelinquency,weused27itemsonofflinedelinquency,and10itemsononlinedelinquency.Offlinedelinquencyitemsincludedwhetherornotajuvenilehadbeeninvolvedinanyofthefollowingtypeofoffensesinthe12monthspriortotheinterview:violentoffenses(7items),propertyoffenses(11items),vandalism(5items),distributingnarcotics(3items),andthepossessionofweapons(1item).Onlinedelinquencywasmeasuredusing10items,differentiatingbetweencyber-enabled(5items)andcyber-dependentoffenses(5items).Cyber-enableddelinquencyincluded:threatsthroughtextmessages,e-mailorchat-box,threatsthroughsocialmedia,notsupplyinggoodsthathavebeenpurchasedonline,notpayingforgoodsthathavebeenpurchasedonline,anddistributingsexualpicturesofminorsthroughtheinternet.Cyber-dependentoffensesincluded:carryingoutDDoSattacks,hackingwithoutchanginginformation,hackingandchanginginformation,sendingviruses,andchangingpasswords.Forreadability,weusetheterm‘digitizeddelinquents’torefertojuveniledelinquentsofcyber-enabledoffenses,andtheterm‘cyberdelinquents’torefertojuveniledelinquentsofcyber-dependentoffenses.Juvenileswereaskedtoindicatewhethertheyhadevercommittedanyoftheseoffenses,andifso,howofteninthe12monthspriortotheinterview.Juvenileswerecodedasdelinquentsiftheyreportedcommittingatleastoneoffenseinthe12monthspriortotheinterview(oneyearprevalence).Intotal,23.4%ofthejuvenilesreportedthattheyhadcommittedatleastoneonlineoffenseinthe12monthspriortotheinterview(N=320).Ofthoseonlinedelinquents,42.2%reportedonlycyberoffenses(N=135),32.2%reportedonlydigitizedoffenses(N=103),and26.6%reportedbothcyberanddigitizedoffenses(N=85).Thesethreegroupswereusedtostudythedifferencesbetweencyberanddigitizeddelinquents.Tostudythedifferencesbetweenonlineandofflinedelinquents,fourgroupsweredistinguished:agroupofnon-delinquents(N=796,58.3%),agrouponlyreportingonlineoffenses(N=85,6.2%),agrouponlyreportingofflineoffenses(N=249,18.2%),andagroupthatreportedbothonlineandofflineoffenses(N=235,17.2%).2.2.IndependentVariablesTostudythedifferencesbetween(differenttypesof)onlineandofflinedelinquents,weexaminedfactorsconcerningtheindividual(self-control,alcoholanddruguse,gaming,attitudetowardsdelinquency),family(emotionalwarmth,parentalsolicitation,parentalcontrol),friends(delinquentbehaviorofpeers),andschooldomain(satisfactionwithschool).Unfortunately,theYDSdoesnotincludequestionsregardingthecommunitydomain.DiscussionThepurposeofthecurrentstudywastoidentifydifferencesbetweendigitizeddelinquentsandcyberdelinquents,andtoexaminedifferencesbetweenthemandtraditional,offlinedelinquents.Forthesepurposes,weuseddatafromthe2015waveoftheYouthDelinquencySurvey(YDS),across-sectionalstudywithanationalprobabilitysampleofjuvenilesaged12to17yearsintheNetherlands,containingdetailedinformationonbothself-reportedonlineandofflinedelinquency,andriskandpromotivefactors.Theresultsofourstudysuggestdifferencesbetweenjuvenileswhoreportedonlyonlineoffensesandjuvenileswhoalsoreportedofflineoffenses,regardingriskandpromotivefactors.Juvenileswhoreportbothofflineandonlineoffenseshavethemosthigh-riskprofile,incomparisontojuvenileswhoonlycommitonlineoffensesandjuvenileswhoonlycommitofflineoffenses.Thisfindingsupportstheassumptionthattheriskfactormodelprimarilyprovidesanexplanationformoreseriousdelinquency(Loeberetal.,2008).Furthermore,evidenceisfoundforacounter-balancingeffectofcumulativeriskandpromotivefactors.Themoreriskdomainsandfewerpromotivedomainsthatwereexperienced,thehigherthepercentageofjuvenilesthatcommittedbothofflineandonlineoffenses.Thisimpliesthatforthesejuveniles,preventionsandinterventionsacrossmultipledomainsarerequired.Withinthegroupofonlinedelinquents,juvenileswhocommitbothcyberanddigitizedoffenseshadthehighestriskprofile.Ourfindingssuggestthatcyberdelinquentsareadistinctgroupfromonlinedelinquents.Cyberdelinquentshavetheleastsevereriskprofile:theyreportmorepromotivefactorsandfewerriskfactorscomparedtoothergroupsofonlinedelinquents.Furthermore,cyberdelinquentsarethegroupleastlikelytoalsocommitofflineoffenses.ThesefindingssupportthefindingsofYar(2005b),andBosslerandBurruss(2011).Theytoofoundmixedsupportfortheapplicabilityoftraditionaltheoriestocyber-dependentdelinquency.Assuch,ourresultsimplythatwhilsttraditionalcriminologicaltheoriescanbeusedforexplainingcyber-enableddelinquency,newtheoriesmaybeneededfortheexplanationofcyber-dependentdelinquency.Ourfindingthatonlinedelinquents,andcyberdelinquentsinparticular,havethelowestriskprofileintermsofriskandpromotivefactorsmay,however,indicatealackofrelevantriskfactorstocharacterizethesedelinquents.Todetermineprofilesofonlinedelinquentswereliedontheexistingriskfactormodel(Loeberetal.,2008).Thismodelwasdesignedforunderstandingwhyjuvenilescommitoffensesoffline,butnotnecessarilyonline.Theresultsofourstudysuggestthatsomeoftheseriskfactorsdoapplytoself-reportedonlinedelinquency.Yet,inparticularforcyberdelinquents,wefoundfewsignificantassociationswiththeriskandpromotivefactors.Thissupportsthesuggestionthatdelinquentsofcyber-dependentoffensesareinneedofatypologicalapproachthatspecificallyexplainsthistypeofdelinquency(Capeller,2001).However,insteadof,assomehavesuggested,developinganewtheory,analternativeapproachistoexpandtheriskfactormodeltoincludeadigitaldomain.Digitalriskandpromotivefactors,suchassocialmediause,digitalactivities,andprogrammingskills,areoftenrelatedtocyber-dependentdelinquency(Bossler&Burrus,2011),butaremostlymissinginresearchononlinedelinquency.Inaddition,inordertoverifywhetherourresultsholdwhenusingdatasourcesotherthanself-reporteddata,werecommendfuturestudiesinvestigatehowpoliceandjudicialrecordscanbeusedtodistinguishofflinedelinquencyfromonlinedelinquency.Furthermore,itwouldbeofinteresttoexplorewhetheralternative(online)sources,suchasdatafromsocialmedia,canbeusedtomeasureorpredictonlinedelinquency.ConclusionInconclusion,theresultsofthisstudyprovideafirstinsightintothedifferencesbetweenjuveniledelinquentsofcyber-enabledandcyber-dependentoffenses,andintotheextenttowhichtheydifferfromtraditionalofflinedelinquents.Basedonself-reportdatafromanationalprobabilitysampleofDutchjuveniles,weshowedthatjuvenilecyberdelinquentsareadistinctgroupcomparedtojuveniledigitizeddelinquentsandtojuvenileswhoreportbothcyberanddigitizedoffenses.Giventhatthepreventionandtreatmentofjuveniledelinquencyisprimarilyfocusedontraditionaloffenses,itremainstobeseenwhetherexistinginterventionsarealsoeffectiveinpreventingjuvenilesfromcommittingcyber-dependentoffenses.LimitationsandDirectionsforfutureresearchAlthoughthisisthefirstcomprehensivestudyonthecharacteristicsofjuvenileonlinedelinquentsusinganationalprobabilitysampleofjuveniles,thefindingsandimplicationsshouldbeviewedinlightofsomelimitations.First,thedataweusedarebasedonself-reportdata.Self-reportdatahastheadvantagethatitsuppliesinformationondelinquencythatisnotknowntothepoliceorjusticesystem.However,theuseofself-reportsalsohaslimitations.Forinstance,juvenilesmaybereluctanttorevealcriminalactivities,whichmayleadtoanunder-representationofmoreseriousformsofdelinquency(Weijters,VanderLaan&Kessels,2016).Moreover,self-reportsmaybeaffectedbyrespondents’recallerrors,ifalongperiodoftimesincethedelinquentacthaselapsed(Junger-Tas&HaenMarshall,1999).Second,thecross-sectionalnatureofthisstudyprecludestemporalinferences.Assuch,thevariousriskandpromotivefactorsmaynotonlycausejuveniledelinquency,buttheymayalsobetheresultofjuveniles’engagementindelinquency.Itisfeasible,forinstance,thatjuvenileswhocommitoffensesdevelopamorepositiveattitudetowardsdelinquency.Inaddition,incriminologicalliterature,thereisanongoingdebateonwhetherpeerdelinquencyisacauseorconsequenceofdelinquentbehavior(Weerman,2011).Tostudytemporalorder,longitudinaldataarerequired.Lastly,althoughmanyofthefactorsinpreviousresearchwerealsoaddressedinthecurrentstudy,weknewlittleabouttheinternetbehaviorofjuveniles.Invariousstudies,differentaspectsofinternetbehaviorhavebeenidentifiedasstrongpredictorsofonlineriskbehavioramongjuveniledelinquents(Kerstens&Veenstra,2015).Withthisinmind,werecommendfutureresearchspecificallyfocusesonfactorsthatarerelatedtoonlinebehavior.中文译文虚拟世界中的青少年犯罪：荷兰使用网络犯罪、依赖网络犯罪和线下犯罪的异同摘要本研究调查了青少年犯罪在自述使用网络犯罪、依赖网络犯罪和线下犯罪中的异同。本研究以过去的研究为基础，对荷兰12-17岁青少年的全国性概率样本进行了广泛的在线和线下犯罪调查。结果明，无论是线下犯罪，还是在线犯罪，被举报犯罪的青少年都具有最高的风险。在网络犯罪群体中，依赖网络犯罪和使用网络犯罪的青少年风险最高。研究结果进一步表明，依赖网络犯罪是网络犯罪的一个独特群体。关键词：在线犯罪，网络犯罪，依赖网络犯罪，使用网络犯罪，风险和促进因素导言自2007年以来，警方的人口普查数据显示，荷兰的青少年犯罪率急剧下降（VanderLaan和Goudriaan，2016）。由于这一犯罪率的下降，处理青少年犯罪的紧迫性似乎有所下降，重点已转移到更具体的犯罪形式上，如高影响犯罪。然而，官方统计数据主要涉及传统的线下犯罪。对所观察到的犯罪率下降的一个可能的解释是，青少年已经从传统的线下犯罪转变为在线犯罪（Tcherni等，2016）。随着社会的数字化，传统的线下犯罪出现了新的方式，也出现了新的在线犯罪类型。这就提出了一个问题，即“街头犯罪”是否已经转变为在线犯罪，或者我们是否正在处理一种新型的犯罪。以前的研究区分了两种类型的在线犯罪：使用网络犯罪和依赖网络犯罪（Holt和Bossler，2016；McGuire和Dowling，2013）。使用网络犯罪是指使用信息通信技术（ICT）实施的“传统”犯罪，包括在线欺诈、勒索和在线跟踪等行为。依赖网络犯罪是指只能通过信息通信技术实施且主要针对计算机或网络资源的犯罪。这包括黑客攻击、传播病毒和策划DDoS攻击等行为。为了更好地了解什么样的人参与了在线犯罪，学者们现在已经开始研究在线犯罪的相关性，以及它们与线下犯罪的差异和共同性。以往的大多数研究都将研究重点限制在一种或最多少数几种网络犯罪上。关于使用网络犯罪，研究的重点是在线欺凌和骚扰（例如，Kerstens和Veenstra，2015；Raskauskas和Stolz，2007；Ybarra和Mitchell，2004）、在线儿童色情（概述见Babchishin、Hanson和Hermann，2010）和数字盗版（例如，Brunton-Smith和McCarthy，2016；Higgins，2005；Higg