This study analyses data from a survey of Australian adult computer users conducted in June 2021 to examine the influence of online routine activities and life stressors on the likelihood of profit-motivated cybercrime victimisation.
Compared with non-victims, victims spent more time online, more frequently engaged in recreational online activities and were more likely to employ higher-risk online practices. Small-to-medium enterprise owners working from home were more likely to be victims. Respondents who had experienced recent increases in financial stress and gambling and negative impacts on interpersonal relationships during the COVID-19 pandemic were also more likely to be a victim of cybercrime.
Being accessible online and a lack of personal and physical guardianship are associated with an increased risk of being a victim, but other factors may influence the susceptibility of computer users to cybercrime victimisation. This has important implications for cybercrime responses.
References
URLs correct as at May 2023
Anderson K 2013. Consumer fraud in the United States, 2011: The third FTC survey. https://www.ftc.gov/reports/consumer-fraud-united-states-2011-third-ftc-survey
Archer KJ & Lemeshow S 2006. Goodness-of-fit test for a logistic regression model fitted using survey sample data. Stata Journal 6(1): 97–105. https://doi.org/10.1177/1536867X0600600106
Australian Bureau of Statistics (ABS) 2021. National, state and territory population: Population by age and sex - national. Canberra: ABS. https://www.abs.gov.au/statistics/people/population/national-state-and-territory-population/dec-2020#data-download
Australian Competition and Consumer Commission (ACCC) 2021. Targeting scams: Report of the ACCC on scams activity 2020. Canberra: ACCC. https://www.accc.gov.au/publications/targeting-scams-report-on-scam-activity/targeting-scams-report-of-the-accc-on-scam-activity-2020
Australian Cyber Security Centre (ACSC) 2022. Annual cyber threat report: July 2021 – June 2022. Canberra: ACSC. https://www.cyber.gov.au/about-us/reports-and-statistics/acsc-annual-cyber-threat-report-july-2021-june-2022
Australian Cyber Security Centre (ACSC) 2021. Annual cyber threat report: 1 July 2020 to 30 June 2021. Canberra: ACSC. https://www.cyber.gov.au/about-us/reports-and-statistics/acsc-annual-cyber-threat-report-july-2020-june-2021
Baumeister RF, DeWall CN, Ciarocco NJ & Twenge JM 2005. Social exclusion impairs self-regulation. Journal of Personality and Social Psychology 88(4): 589–604. https://doi.org/10.1037/0022-3514.88.4.589
Baxter J & Warren D 2021. Families in Australia Survey: Report no. 2: Employment & work–family balance in 2020. Australian Institute of Family Studies. https://aifs.gov.au/research/research-reports/towards-covid-normal-employment-work-family-balance
Bergmann MC, Dreißigacker A, von Skarczinski B & Wollinger GR 2018. Cyber-dependent crime victimization: The same risk for everyone? Cyberpsychology, Behavior, and Social Networking 21(2): 84–90. https://doi.org/10.1089/cyber.2016.0727
Bossler AM & Holt TJ 2010. The effect of self-control on victimization in the cyberworld. Journal of Criminal Justice 38(3): 227–236. https://doi.org/10.1016/j.jcrimjus.2010.03.001
Buil-Gil D, Miró-Llinares F, Moneva A, Kemp S & Díaz-Castaño N 2021. Cybercrime and shifts in opportunities during COVID-19: A preliminary analysis in the UK. European Societies 23(S1): S47–S59. https://doi.org/10.1080/14616696.2020.1804973
Buil-Gil D, Zeng Y & Kemp S 2021. Offline crime bounces back to pre-COVID levels, cyber stays high: Interrupted time-series analysis in Northern Ireland. Crime Science 10: article 26. https://doi.org/10.1186/s40163-021-00162-9
Carter E 2023. Distort, extort, deceive and exploit: Exploring the inner workings of a romance fraud. British Journal of Criminology 61(2): 283–302. https://doi.org/10.1093/bjc/azaa072
Cobb-Clark DA, Kong N & Schildberg-Hörisch H 2021. The stability of self-control in a population representative study. IZA Institute of Labor Economics, Discussion paper No. 14976. Germany: IZA – Institute of Labor Economics
Cohen LE & Felson M 1979. Social change and crime rate trends: A routine activity approach. American Sociological Review 44(4): 588–608. https://doi.org/10.2307/2094589
Cross C 2015. No laughing matter: Blaming the victim of online fraud. International Review of Victimology 21: 187–204. https://doi.org/10.1177/0269758015571471
Emami C, Smith RG & Jorna P 2019. Online fraud victimisation in Australia: Risks and protective factors. Research Report no. 16. Canberra: Australian Institute of Criminology. https://www.aic.gov.au/publications/rr/rr16
Gainsbury SM, Browne M & Rockloff M 2018. Identifying risky internet use: Associating negative online experience with specific online behaviours. New Media & Society 21(6): 1232–1252. https://doi.org/10.1177/1461444818815442
Holt TJ, van Wilsem J, van de Weijer S & Leukfeldt R 2020. Testing an integrated self-control and routine activities framework to examine malware infection victimization. Social Science Computer Review 38(2): 187–206. https://doi.org/10.1177/0894439318805067
James BD, Boyle PA & Bennett DA 2014. Correlates of susceptibility to scams in older adults without dementia. Journal of Elder Abuse & Neglect 26(2): 107–122. https://doi.org/10.1080/08946566.2013.821809
Jorna P & Hutchings A 2013. Australasian Consumer Fraud Taskforce: Results of the 2012 online consumer fraud survey. Technical and background paper no. 56. Canberra: Australian Institute of Criminology. https://www.aic.gov.au/publications/tbp/tbp56
Lee J & Soberon-Ferrer H 1997. Consumer vulnerability to fraud: Influencing factors. Journal of Consumer Affairs 31(1): 70–89. https://doi.org/10.1111/j.1745-6606.1997.tb00827.x
Lerner JS, Li Y & Weber EU 2012. The financial costs of sadness. Psychological Science 24(1): 72–79. https://doi.org/10.1177/0956797612450302
Leukfeldt ER & Yar M 2016. Applying routine activity theory to cybercrime: A theoretical and empirical analysis. Deviant Behavior 37(3): 263–280. https://doi.org/10.1080/01639625.2015.1012409
Levi M & Smith RG 2021. Fraud and its relationship to pandemics and economic crises: From Spanish flu to COVID-19. Research Report no. 19. Canberra: Australian Institute of Criminology. https://doi.org/10.52922/rr78115
Mikkola M et al. 2020. Situational and individual risk factors for cybercrime victimization in a cross-national context. International Journal of Offender Therapy and Comparative Criminology. Advance online publication. https://doi.org/10.1177/0306624x20981041
Muller CJ & MacLehose RF 2014. Estimating predicted probabilities from logistic regression: Different methods correspond to different target populations. International Journal of Epidemiology 43(3): 962–970. https://doi.org/10.1093/ije/dyu029
Nabe C 2021. Impact of COVID-19 on cybersecurity. https://www2.deloitte.com/ch/en/pages/risk/articles/impact-covid-cybersecurity.html
Nattino G, Pennell ML & Lemeshow S 2020. Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer-Lemeshow test. Biometrics 76(2): 549–560. https://doi.org/10.1111/biom.13249
Newson R 2006. Confidence intervals for rank statistics: Somers’ D and extensions. Stata Journal 6(3): 309–334. https://doi.org/10.1177/1536867X0600600302
Ngo FT & Paternoster R 2011. Cybercrime victimization: An examination of individual and situational level factors. International Journal of Cyber Criminology 5(1): 773–793.
Pennay DW, Neiger D, Lavrakas PJ & Borg K 2018. The Online Panels Benchmarking Study: A total survey error comparison of findings from probability-based surveys and non-probability online panel surveys in Australia. CSRM & SRC Methods Paper no. 2/2018. Canberra: Australian National University. https://csrm.cass.anu.edu.au/research/publications/online-panels-benchmarking-study-total-survey-error-comparison-findings
Pregibon D 1979. Data analytic methods for generalized linear models. University of Toronto.
Reyns BW 2018. Routine activity theory and cybercrime: A theoretical appraisal and literature review. In KF Steinmetz & MR Nobles (eds), Technocrime and criminological theory. New York: Routledge: 35–54. https://doi.org/10.4324/9781315117249-3
Reyns BW 2013. Online routines and identity theft victimization: Further expanding routine activity theory beyond direct-contact offences. Journal of Research in Crime and Delinquency 50(2): 216–238. https://doi.org/10.1177/0022427811425539
Reyns BW, Fisher BS, Bossler AM & Holt TJ 2019. Opportunity and self-control: Do they predict multiple forms of online victimization? American Journal of Criminal Justice 44(1): 63–82. https://doi.org/10.1007/s12103-018-9447-5
Roberts BW 2009. Back to the future: Personality and assessment and personality development. Journal of Research in Personality 43(2): 137–145. https://doi.org/10.1016/j.jrp.2008.12.015
Ross S & Smith RG 2011. Risk factors for advance fee fraud victimisation. Trends & issues in crime and criminal justice no. 420. Canberra: Australian Institute of Criminology. https://www.aic.gov.au/publications/tandi/tandi420
van de Weijer SGA & Leukfeldt ER 2017. Big Five personality traits of cybercrime victims. Cyberpsychology, Behavior, and Social Networking 20(7): 407–412. https://doi.org/10.1089/cyber.2017.0028
van Wilsem J 2013. ‘Bought it, but never got it’ assessing risk factors for online consumer fraud victimization. European Sociological Review 29(2): 168–178. https://doi.org/10.1093/esr/jcr053
Voce I & Morgan A 2021. Ransomware victimisation among Australian computer users. Statistical Bulletin no. 35. Canberra: Australian Institute of Criminology. https://doi.org/10.52922/sb78382
Wemm SE & Wulfert E 2017. Effects of acute stress on decision making. Applied Psychophysiology and Biofeedback 42(1): 1–12. https://doi.org/10.1007/s10484-016-9347-8
Whitty MT 2019. Predicting susceptibility to cyber-fraud victimhood. Journal of Financial Crime 26(1): 277–292. https://doi.org/10.1108/JFC-10-2017-0095
Williams ML 2016. Guardians upon high: An application of routine activities theory to online identity theft in Europe at the country and individual level. British Journal of Criminology (56)1: 21–48. https://doi.org/10.1093/bjc/azv01