[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83667-en":3,"doc-seo-83667-105":30,"detail-sidebar-cat-0-en-105":84},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},83667,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Cybercrime Victimization Among Young Adult Males Aged 18–20: A Post-Pandemic Analysis of Converging Risk Factors","Cybercrime victimization among young adult males aged 18–20 is examined as an urgent post-pandemic public safety issue. Using FBI Internet Crime Complaint Center (IC3) and FTC Consumer Sentinel Network reports from 2022–2024 and ENISA cybersecurity threat intelligence, the study analyzes a distinct risk sub-cohort and integrates criminological, neurological, and behavioral evidence. Results highlight a 49.7% increase in reported losses for ages 20–29 (2023–2024) and identify key typologies including financial sextortion, phishing, task scams, in-game currency fraud, and dark web grooming. The work informs targeted awareness, digital literacy, and policy interventions.","Cybercrime Victimization Among Young Adult  \nMales Aged 18–20:  \nA Post-Pandemic Analysis of Converging Risk  \nFactors  \narXiv :2607 .02530v1 [ cs .CY] 30 May 2026  \nAnveeksh Mahesh Rao  \nKhoury College of Computer Sciences Northeastern University Boston, MA, USA [rao.anv@northeastern.edu](rao.anv@northeastern.edu)[ ](rao.anv@northeastern.edu)[ORCID: 0000-0005-4791-1789](ORCID: 0000-0005-4791-1789)  \nAbstract—Cybercrime victimization among young adult males aged 18–20 has become an increasingly urgent public safety concern in the post-pandemic digital environment. From 2022 to 2024, individuals aged 20–29 submitted 191,787 complaints to the FBI Internet Crime Complaint Center (IC3), reporting combined losses of more than $1.28 billion. Although this population represents a substantial share of cybercrime victims, the 18– 20 male sub-cohort remains insufficiently examined as a distinct demographic group within cybercrime victimization research. This study presents an original risk factor analysis and theoretical synthesis, representing the first integration of criminological, neurological, and behavioral evidence for this specific demographic sub-cohort. Drawing on FBI IC3 and FTC Consumer Sentinel Network data from 2022–2024 alongside European cybersecurity threat intelligence from ENISA, the study develops a unified risk profile centered on three intersecting vulnerability factors: a guardianship gap created by the transition into unsupervised digital independence, heightened behavioral exposure to online risk, and reduced impulse regulation associated with ongoing prefrontal cortex development. The findings show a 49.7% increase in reported losses among the 20–29 age group between 2023 and 2024 and identify financial sextortion, phishing, task scams, ingame currency fraud, and dark web grooming as major attack typologies exploiting this risk convergence. The study offers implications for targeted cybersecurity awareness campaigns, digital literacy education, and policy interventions designed for this high-risk demographic.  \nIndex Terms—cybercrime victimization, young adult males, routine activity theory, sextortion, phishing, prefrontal cortex, post-pandemic, risk factor analysis, digital guardianship, social engineering  \nI. INTRODUCTION  \nCybercrime has become one of the most widespread and consequential threats affecting young adults in the postpandemic digital era. Between 2022 and 2024, individuals aged 20–29 filed 191,787 complaints with the FBI Internet Crime Complaint Center (IC3), reporting cumulative financial losses exceeding $1.28 billion [3]–[5] . Although IC3 reporting groups victims into a broader 20–29 category, existing scholarship suggests that the 18–20 sub-cohort displays especially elevated behavioral risk patterns and vulnerability indicators [8], [9] .  \nFederal Trade Commission (FTC) data further demonstrates that young adults aged 20–29 reported losing money in 44% of fraud cases, nearly twice the rate observed among older populations, highlighting the financial susceptibility of this group [6] .  \nGender is also a significant factor in cybercrime victimization among young adults. Nsi et al. [9] found that males were 1.70 times more likely than females to experience cybercrime victimization (OR = 1 .70, p = 0 .000), with particularly large gender gaps observed in Germany (8.9% male vs. 3.1% female) and the United Kingdom (8.8% male vs. 5.9% female) . Griffith et al. [8] further show that online gaming, dating application use, visits to sexually explicit websites, and public sharing of personal information increase exposure to motivated offenders. These behaviors align closely with attack types that disproportionately affect young men, including financial sextortion, phishing, task scams, in-game currency fraud, and online grooming [11] .  \nThe 18–20 age range represents a particularly acute period of vulnerability for three reasons. First, it marks the transition from supervised adolescence to indep","cbCaibB8f3vyTyN4","https://ap.wps.com/l/cbCaibB8f3vyTyN4","pdf",182687,7,1,6,"English","en",105,"# Introduction\n# Literature Review\n## Demographic Predictors of Cybercrime Victimization\n# Theoretical Framework\n# Methodology\n# Findings\n# Discussion\n# Prevention and Policy Recommendations\n# Conclusion","[{\"question\":\"Which cybercrime attack typologies are identified as major ways risk convergence is exploited?\",\"answer\":\"Major typologies include financial sextortion, phishing, task scams, in-game currency fraud, and dark web grooming.\"}]",1784189627,15,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":79,"head_meta":81,"extra_data":83,"updated_unix":28},"cybercrime-victimization-among-young-adult-males-aged-1820-a-post-pandemic-analysis-of-converging-risk-factors","",{"@graph":36,"@context":78},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/cybercrime-victimization-among-young-adult-males-aged-1820-a-post-pandemic-analysis-of-converging-risk-factors/83667/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-07-27","2026-07-16",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72],{"name":73,"@type":74,"acceptedAnswer":75},"Which cybercrime attack typologies are identified as major ways risk convergence is exploited?","Question",{"text":76,"@type":77},"Major typologies include financial sextortion, phishing, task scams, in-game currency fraud, and dark web grooming.","Answer","https://schema.org",{"og:url":52,"og:type":80,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":82,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":85},[86,90,94,98,103,107,111,114,119,122,126],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":87,"show_sort_weight":88,"slug":89},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":91,"show_sort_weight":92,"slug":93},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Exam",70,"exam",{"id":99,"doc_module":4,"doc_module_name":46,"category_name":100,"show_sort_weight":101,"slug":102},5,"Comic",60,"comic",{"id":22,"doc_module":4,"doc_module_name":46,"category_name":104,"show_sort_weight":105,"slug":106},"Technology",50,"technology",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":112,"slug":113},30,"research-report",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":99,"slug":129},19,"General","general"]