research-article

The Economics of Cybercrime: The Role of Broadband and Socioeconomic Status

Authors:

Byungtae LeeAuthors Info & Claims

ACM Transactions on Management Information Systems (TMIS), Volume 10, Issue 4

Article No.: 13, Pages 1 - 23

https://doi.org/10.1145/3351159

Published: 05 December 2019 Publication History

Abstract

Under what conditions is the Internet more likely to be used maliciously for criminal activity? This study examines the conditions under which the Internet is associated with cybercriminal offenses. Using comprehensive state-level data in the United States during 2004–2010, our findings show that there is no clear empirical evidence that the Internet penetration rate is related to the number of Internet crime perpetrators; however, cybercriminal activities are contingent upon socioeconomic factors and connection speed. Specifically, a higher income, more education, a lower poverty rate, and a higher inequality are likely to make the Internet penetration be more positively related with cybercrime perpetrators, which are indeed different from the conditions of terrestrial crime in the real world. In addition, as opposed to narrowband, the broadband connections are significantly and positively associated with the number of Internet crime perpetrators, and it amplifies the aforementioned moderating effects of socioeconomic status on Internet crime offenses. Taken together, cybercrime requires more than just a skilled perpetrator, and it requires an infrastructure to facilitate profiteering from the act.

References

[1]

R. Agnew. 1992. Foundation for a general strain theory of crime and delinquency. Criminology 30, 1 (1992), 47--88.

[2]

R. Anderson, C. Barton, R. Bohme, R. Clayton, M. J. Van Esten, and M. Levi. 2013. Measuring the cost of cybercrime. In Economics of Information Security and Privacy. Springer, Berlin.

[3]

J. O. Aransiola and S. O. Asindemade. 2011. Understanding cybercrime perpetrators and the strategies they employ in Nigeria. Cyberpsych., Behav. So. Netw. 14, 12 (2011), 759--763.

[4]

M. Arellano and S. Bond. 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58, 2 (1991), 277--297.

[5]

H. Atasoy. 2013. The effects of broadband internet expansion on labor market outcomes. ILR Rev. 66, 2 (2013), 315--345.

[6]

D. H. Autor, L. F. Katz, and M. S. Kearney. 2008. Trends in U.S. wage inequality: Revising the revisionists. Rev. Econ. Stat. 90, 2 (2008), 300--323.

[7]

Y. Bakos and E. Brynjolfsson. 1999. Bundling information goods: Pricing, profits, and efficiency. Manag. Sci. 45, 12 (1999), 1613--1630.

Digital Library

[8]

G. S. Becker. 1968. Crime and punishment: An economic approach. J. Polit. Econ. 76, 2 (1968), 169--217.

[9]

V. Benjamin, B. Zhang, J. F. Nunamaker, and H. Chen. 2016. Examining hacker participation length in cybercriminal internet-relay-chat communities. J. Manag. Inform. Syst. 33, 2 (2016), 482--510.

[10]

M. Bhuller, T. Havnes, E. Leuven, and M. Mogstad. 2013. Broadband internet: An information superhighway to sex crime? Rev. Econ. Stud. 80, 4 (2013), 1237--1266.

[11]

J. Braithwaite. 1991. Poverty, power, white-collar crime and the paradoxes of criminological theory. Austr. 8 New Zeal. J. Criminol. 24, 1 (1991), 40--58.

[12]

R. Broadhurst, P. Grabosky, M. Alazab, B. Bouhours, and S. K. Chon. 2013. Crime in cyberspace: Offenders and the role of organized crime groups. SSRN Electron. J.

[13]

E. Brynjolfsson and L. Hitt. 1996. Paradox lost? Firm-level evidence on the returns to information systems spending. Manag. Sci. 42, 4 (1996), 541--558.

Digital Library

[14]

W. Capeller. 2001. Not such a neat net: Some comments on virtual criminality. Soc. 8 Legal Stud. 10, 2 (2001), 229--242.

[15]

J. Chan, A. Ghose, and R. Seamans. 2016. The internet and racial hate crimes: Offline spillovers from online access. MIS Quart. 40, 2 (2016), 381--403.

Digital Library

[16]

W. H. Chiu and P. Madden. 1998. Burglary and income inequality. J. Publ. Econ. 69, 1 (1998), 123--141.

[17]

R. Clayton, T. Moore, and N. Christin. 2015. Concentrating correctly on cybercrime concentration. In Proceedings of the 14th Workshop on the Economics of Information Security.

[18]

CNET. 2017. Wannacry ransomware: Everything you need to know (May 19, 2017). https://www.cnet.com/news/wannacry-wannacrypt-uiwix-ransomware-everything-you-need-to-know/.

[19]

D. B. Cornish and R. V. Clarke. 1986. The Reasoning Criminal: Rational Choice Perspectives on Offending. Springer, Piscataway, NJ.

[20]

J. Driscoll and A. Kraay. 1998. Consistent covariance matrix estimation with spatially dependent data. Rev. Econ. Stat. 80, 4 (1998), 549--560.

[21]

K. Edmark. 2005. Unemployment and crime: Is there a connection? Scand. J. Econ. 107, 2 (2005), 353--373.

[22]

M. W. Frank. 2009. Inequality and growth in the United States: Evidence from a new state-level panel of income inequality measures. Econ. Inquiry 47, 1 (2009), 55--68.

[23]

E. L. Glaeser and B. Sacerdote. 1999. Why is there more crime in cities? J. Polit. Econ. 107, S6 (1999), S225--S258.

[24]

E. L. Glaeser, B. Sacerdote, and J. A. Scheinkman. 1996. Crime and social interactions. Quart. J. Econ. 111, 2 (1996), 507--548.

[25]

S. Goel, K. Williams, and E. Dincelli. 2017. Got phished? Internet security and human vulnerability. J. Assoc. Inform. Syst. 18, 1 (2017), 22--44.

[26]

S. Gordon and R. Ford. 2006. On the definition and classification of cybercrime. J. Comput. Virol. 2, 1 (2006), 13--20.

[27]

T. J. Holt, D. Strumsky, O. Smirnova, and M. Kilger. 2012. Examining the social networks of malware writers and hackers. Int. J. Cyber Crim. 6, 1 (2012), 891--903.

[28]

S. Ibrahim. 2016. Social and contextual taxonomy of cybercrime: Socioeconomic theory of Nigerian cybercriminals. Int. J. Law, Crime Just. 47, 44--57.

[29]

IC3. 2009. 2009 Internet Crime Report, Internet Crime Complaint Center. https://pdf.ic3.gov/2009_IC3Report.pdf.

[30]

IC3. 2010. 2010 Internet Crime Report, Internet Crime Complaint Center. https://pdf.ic3.gov/2010_IC3Report.pdf.

[31]

J. P. John, A. Moshchuk, S. D. Gribble, and A. Krishnamurthy. 2009. Studying spamming botnets using botlab. In Proceedings of the 6th USENIX Symposium on Networked Systems Design and Implementation (NSDI’09). 291--306.

[32]

I. Kawachi, B. P. Kennedy, K. Lochner, and D. Prothrow-Stith. 1997. Social capital, income inequality, and mortality. Amer. J. Pub. Health 87, 9 (1997), 1491--1498.

[33]

M. Kelly. 2000. Inequality and crime. Rev. Econ. Stat. 82, 4 (2000), 530--539.

[34]

B. P. Kennedy, I. Kawachi, D. Prothrow-Stith, K. Lochner, and V. Gupta. 1998. Social capital, income inequality, and firearm violent crime. Soc. Sci. Med. 47, 1 (1998), 7--17.

[35]

A. Kigerl. 2011. Routine activity theory and the determinants of high cybercrime countries. Soc. Sci. Comput. Rev. 30, 4 (2011), 470--486.

Digital Library

[36]

S. H. Kim, Q.-H. Wang, and J. B. Ullrich. 2012. A comparative study of cyberattacks. Commun. ACM 55, 3 (2012), 66--73.

Digital Library

[37]

J. Kolko. 2012. Broadband and local growth. J. Urb. Econ. 71, 1 (2012), 100--113.

[38]

N. Kshetri. 2006. The simple economics of cybercrimes. IEEE Secur. Priv. 4, 1 (2006), 33--39.

Digital Library

[39]

A. Lakhina, M. Crovella, and C. Diot. 2005. Detecting distributed attacks using network-wide flow traffic. In Proceedings of the FloCon Analysis Workshop.

[40]

L. Langton and N. L. Piquero. 2007. Can general strain theory explain white-collar crime? A preliminary investigation of the relationship between strain and select white-collar offenses. J. Crim. Just. 35, 1 (2018), 1--15.

[41]

S. Lazarus. 2018. Birds of a feather flock together: The Nigerian cyber fraudsters (yahoo boys) and hip hop artists. Criminol., Crim. Just., Law Soc. 19, 2 (2018), 63--80.

[42]

S. Lazarus. 2019. Just married: The synergy between feminist criminology and the tripartite cybercrime framework. Int. Soc. Sci. J. 1--19.

[43]

J. K. Lee. 2015. Research framework for AIS grand vision of the bright ICT initiative. MIS Quart. 39, 2, III--XII.

Digital Library

[44]

J. K. Lee, D. Cho, and G. G. Lim. 2018. Design and validation of the bright internet. J. Assoc. Inform. Syst. 19, 2, 63--85.

[45]

S.-H. Lee and H.-W. Kim. 2015. Why people post benevolent and malicious comments online. Commun. ACM 58, 11, (2015), 74--79.

Digital Library

[46]

H. Liang and Y. Xue (Lucky). 2010. Understanding security behaviors in personal computer usage: A threat avoidance perspective. J. Assoc. Inform. Syst. 11, 7 (2010), 394--413.

[47]

L. Lochner. 2004. Education, work, and crime: A human capital approach. Int. Econ. Rev. 45, 3 (2004), 811--843.

[48]

L. Lochner and E. Moretti. 2004. The effect of education on crime: Evidence from prison inmates, arrest, and self-reports. Amer. Econ. Rev. 94, 1 (2004), 155--189.

[49]

R. K. Merton. 1938. Social structure and anomie. Amer. Sociolog. Rev. 3, 5 (1938), 672--682.

[50]

I. Munyo and M. A. Rossi. 2013. Frustration, euphoria, and violent crime. J. Econ. Behav. Organiz. 89, 136--142.

[51]

N. Nykodym, R. Taylor, and J. Vilela. 2005. Criminal profiling and insider cyber crime. Comput. Law Secur. Rev. 21, 5 (2005), 408--414.

[52]

M.-S. Pang, A. Tafti, and M. S. Krishnan. 2014. Information technology and administrative efficiency in U.S. state governments: A stochastic frontier approach. MIS Quart. 38, 4 (2014), 1079--1101.

Digital Library

[53]

E. B. Patterson. 1991. Poverty, income inequality, and community crime rates. Criminology 29, 4 (1991), 755--776.

[54]

T. Persson and G. Tabellini. 1994. Is inequality harmful for growth? Amer. Econ. Rev. 84, 3 (1994), 600--621.

[55]

I. P. L. Png, C.-Y. Wang, and Q.-H. Wang. 2008. The deterrent and displacement effects of information security enforcement: International evidence. J. Manag. Inform. Syst. 25, 2 (2008), 125--144.

Digital Library

[56]

T. C. Pratt, K. Holtfreter, and M. D. Reisig. 2010. Routine online activity and internet fraud targeting: Extending the generality of routine activity theory. J. Res. Crime Delinq. 47, 3 (2010), 267--296.

[57]

S. Raphael and R. Winter-Ebmer. 2001. Identifying the effect of unemployment on crime. J. Law Econ. 44, 1 (2001), 259--283.

[58]

J. Van Reenen. 2011. Wage inequality, technology and trade: 21st century evidence. Lab. Econ. 18, 6 (2011), 730--741.

[59]

R. J. Sampson, S. W. Raudenbush, and F. Earls. 1997. Neighborhoods and violent crime: A multilevel study of collective efficacy. Science 277, 5328, 918--924.

[60]

P. Sandle and P. Char. 2014. Cyber crime costs global economy &dollar;445 billion a year: Report. Reuters. https://www.reuters.com/article/us-cybersecurity-mcafee-csis/cyber-crime-costs-global-economy-445-billion-a-year-report-idUSKBN0EK0SV20140609.

[61]

C. Van Slyke, J. T. Shim, R. Johnson, and J. J. Jiang. 2006. Concern for information privacy and online consumer purchasing. J. Assoc. Inform. Syst. 7, 6 (2006), 415--444.

[62]

P. C. Solano and A. J. R. Peinado. 2017. Socio-economic factors in cybercrime: Statistical study of the relation between socio-economic factors and cybercrime. In Proceedings of the IEEE International Conference on Cyber Situational Awareness, Data Analytics and Assessment. 1--4.

[63]

Symantec. 2016. Internet Security Threat Report 2016 (Vol. 21), Symantec. https://www.symantec.com/content/dam/symantec/docs/reports/istr-21-2016-en.pdf.

[64]

P. Tambe and L. M. Hitt. 2012. The productivity of information technology investments: New evidence from IT labor data. Inform. Syst. Res. 23, 3-part 1, 599--617.

[65]

D. Thomas and B. Loader. 2000. Cybercrime: Law Enforcement, Security and Surveillance in the Information Age. Routledge, London.

[66]

P. A. Watters, S. McCombie, R. Layton, and J. Pieprzyk. 2012. Characterising and predicting cyber attacks using the cyber attacker model profile (CAMP). J. Money Laund. Contr. 15, 4 (2012), 430--441.

[67]

B. Weber. 2014. Can safe ride programs reduce urban crime? Reg. Sci. Urban Econ. 48, 1--11.

[68]

S. Wheeler. 1994. The problem of white-collar crime motivation. In White-collar Crime Reconsidered. Northeastern, Boston, MA, 108--123.

[69]

M. Yar. 2005. The novelty of “cybercrime”: An assessment in light of routine activity theory. Euro. J. Criminol. 2, 4 (2005), 407--427.

[70]

M. Yar. 2013. Cybercrime and Society (2nd ed.). SAGE Publications, London.

Cited By

Maras KSweiry AVilladsen AFitzsimons E(2024)Cyber offending predictors and pathways in middle adolescence: Evidence from the UK Millennium Cohort StudyComputers in Human Behavior10.1016/j.chb.2023.108011151(108011)Online publication date: Feb-2024
https://doi.org/10.1016/j.chb.2023.108011
Wright C(2023)Geographical Aspects of Cybercrime: A Literature ReviewSSRN Electronic Journal10.2139/ssrn.4521486Online publication date: 2023
https://doi.org/10.2139/ssrn.4521486
Andrade RFuertes WCazares MOrtiz-Garcés INavas G(2022)An Exploratory Study of Cognitive Sciences Applied to CybersecurityElectronics10.3390/electronics1111169211:11(1692)Online publication date: 26-May-2022
https://doi.org/10.3390/electronics11111692
Show More Cited By

Index Terms

The Economics of Cybercrime: The Role of Broadband and Socioeconomic Status
1. Security and privacy
  1. Human and societal aspects of security and privacy
    1. Economics of security and privacy

Recommendations

Introduction—Cybercrime: A Note on International Issues

Cybercrime investigations often transcend national boundaries. This creates problems for investigators because the procedural laws that govern the conduct of criminal investigations are territorially-based; that is, they apply only within the territory ...
U.S. Cybercrime Law: Defining Offenses

In recent years, a new term has arisen—“cybercrime”—which essentially denotes the use of computer technology to commit or to facilitate the commission of unlawful acts, or “crimes.” This article explains why we treat cybercrime as a special class of “...
U.S. and EU Legislation on Cybercrime
EISIC '11: Proceedings of the 2011 European Intelligence and Security Informatics Conference

The advent of Internet technologies has created global cyber crime problems. Cyber crimes affect all of us at the time when online transactions are in billions of dollars per year and cyber criminals are costing e-commerce billions of dollars in damages ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 10, Issue 4

December 2019

98 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/3374918

Editor:
Daniel Zeng
Chinese Academy of Sciences, China

Issue’s Table of Contents

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 December 2019

Accepted: 01 July 2019

Revised: 01 June 2019

Received: 01 August 2018

Published in TMIS Volume 10, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

KAIST EEWS Research Center
KAIST Bright Internet Research Center

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
1,055
Total Downloads

Downloads (Last 12 months)193
Downloads (Last 6 weeks)12

Reflects downloads up to 03 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Maras KSweiry AVilladsen AFitzsimons E(2024)Cyber offending predictors and pathways in middle adolescence: Evidence from the UK Millennium Cohort StudyComputers in Human Behavior10.1016/j.chb.2023.108011151(108011)Online publication date: Feb-2024
https://doi.org/10.1016/j.chb.2023.108011
Wright C(2023)Geographical Aspects of Cybercrime: A Literature ReviewSSRN Electronic Journal10.2139/ssrn.4521486Online publication date: 2023
https://doi.org/10.2139/ssrn.4521486
Andrade RFuertes WCazares MOrtiz-Garcés INavas G(2022)An Exploratory Study of Cognitive Sciences Applied to CybersecurityElectronics10.3390/electronics1111169211:11(1692)Online publication date: 26-May-2022
https://doi.org/10.3390/electronics11111692
Lazarus SButton MKapend R(2022)Exploring the value of feminist theory in understanding digital crimes: Gender and cybercrime typesThe Howard Journal of Crime and Justice10.1111/hojo.1248561:3(381-398)Online publication date: 21-Jun-2022
https://doi.org/10.1111/hojo.12485
Lazarus SButton M(2022)Tweets and Reactions: Revealing the Geographies of Cybercrime Perpetrators and the North-South DivideCyberpsychology, Behavior, and Social Networking10.1089/cyber.2021.033225:8(504-511)Online publication date: 1-Aug-2022
https://doi.org/10.1089/cyber.2021.0332
Caldarulo MWelch EFeeney M(2022)Determinants of cyber-incidents among small and medium US citiesGovernment Information Quarterly10.1016/j.giq.2022.10170339:3(101703)Online publication date: Jul-2022
https://doi.org/10.1016/j.giq.2022.101703
Chen SGao CJiang DHao MDing FMa TZhang SLi S(2021)The Spatiotemporal Pattern and Driving Factors of Cyber Fraud Crime in ChinaISPRS International Journal of Geo-Information10.3390/ijgi1012080210:12(802)Online publication date: 30-Nov-2021
https://doi.org/10.3390/ijgi10120802

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Issue’s Table of Contents