Skip to main content

No Gambles with Information Security: The Victim Psychology of a Ransomware Attack

  • Chapter
  • First Online:
  • 1044 Accesses

Part of the book series: Crime and Justice in Digital Society ((CJDS,volume I))

Abstract

Ransomware is a cybercrime in which criminals must coerce their victims’ cooperation to profit from infections. There are generally three possible outcomes of a successful infection: (1) a user, having a secure recent backup of his data, will not feel compelled to pay; (2) an unprepared victim would rather accept the data loss than pay the ransom; and (3) the victim values the compromised data more than the ransom being asked, and therefore pays. Though such crimes are initiated by technological means, they rely on social persuasion for success. The argument will be put forward in this paper that ransomware attacks take advantage of the psychology of loss aversion, and that by delivering loss feedback, these attacks exert a psychological influence that is advantageous to the attackers, and which affects individuals differently according to their neural characteristics. Evidence from cognitive, personality and evolutionary psychology are each presented; directions for further research into the risk factors and mechanisms of persuasion in ransomware attacks are indicated.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Andersson, O., Holm, H. J., Tyran, J. R., & Wengström, E. (2014). Deciding for others reduces loss aversion. Management Science, 62(1), 29–36.

    Article  Google Scholar 

  • Baluch, F., & Itti, L. (2011). Mechanisms of top-down attention. Trends in Neurosciences, 34(4), 210–224.

    Article  Google Scholar 

  • Bohr, J., & Bashir, M. (2014, July). Who uses bitcoin? An exploration of the bitcoin community. In Twelfth Annual International Conference on Privacy, Security and Trust (PST) (pp. 94–101). IEEE. doi:https://doi.org/10.1109/PST.2014.6890928

  • Bressler, S. L., & Ding, M. (2006). Event-related potentials. Wiley encyclopedia of biomedical engineering. Hoboken, NJ: Wiley.

    Google Scholar 

  • Brewer, R. (2016). Ransomware attacks: Detection, prevention and cure. Network Security, 2016(9), 5–9.

    Article  Google Scholar 

  • Carver, C. S. (1980). Perceived coercion, resistance to persuasion, and the type a behavior pattern. Journal of Research in Personality, 14(4), 467–481.

    Article  Google Scholar 

  • Cleck, J. N., & Blendy, J. A. (2008). Making a bad thing worse: Adverse effects of stress on drug addiction. The Journal of Clinical Investigation, 118(2), 454–461.

    Article  Google Scholar 

  • Dehaene, S., Posner, M. I., & Tucker, D. M. (1994). Localization of a neural system for error detection and compensation. Psychological Science, 5(5), 303–305.

    Article  Google Scholar 

  • Dias-Ferreira, E., Sousa, J. C., Melo, I., Morgado, P., Mesquita, A. R., Cerqueira, J. J., … Sousa, N. (2009). Chronic stress causes frontostriatal reorganization and affects decision-making. Science, 325(5940), 621–625.

    Article  Google Scholar 

  • Friedman, M., & Rosenman, R. H. (1959). Association of specific overt behavior pattern with blood and cardiovascular findings: Blood cholesterol level, blood clotting time, incidence of arcus senilis, and clinical coronary artery disease. Journal of the American Medical Association, 169(12), 1286–1296.

    Article  Google Scholar 

  • Gehring, W. J., & Willoughby, A. R. (2002). The medial frontal cortex and the rapid processing of monetary gains and losses. Science, 295(5563), 2279–2282.

    Article  Google Scholar 

  • Haigh, M. S., & List, J. A. (2005). Do professional traders exhibit myopic loss aversion? An experimental analysis. The Journal of Finance, 60(1), 523–534.

    Article  Google Scholar 

  • Herrmann, C. S., Strüber, D., Helfrich, R. F., & Engel, A. K. (2016). EEG oscillations: From correlation to causality. International Journal of Psychophysiology, 103, 12–21.

    Article  Google Scholar 

  • Itagaki, S., & Katayama, J. I. (2008). Self-relevant criteria determine the evaluation of outcomes induced by others. Neuroreport, 19(3), 383–387.

    Article  Google Scholar 

  • Jones, C. L., Minati, L., Harrison, N. A., Ward, J., & Critchley, H. D. (2011). Under pressure: Response urgency modulates striatal and insula activity during decision-making under risk. PLoS One, 6(6), e20942.

    Article  Google Scholar 

  • Judges, R. A., Gallant, S. N., Yang, L., & Lee, K. (2017). The role of cognition, personality, and trust in fraud victimization in older adults. Frontiers in Psychology, 8, 588.

    Article  Google Scholar 

  • Kharraz, A., Robertson, W., Balzarotti, D., Bilge, L., & Kirda, E. (2015). Cutting the gordian knot: A look under the hood of ransomware attacks. In International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment (pp. 3–24). Cham: Springer.

    Google Scholar 

  • Kiehl, K. A., Liddle, P. F., & Hopfinger, J. B. (2000). Error processing and the rostral anterior cingulate: An event-related fMRI study. Psychophysiology, 37(2), 216–223.

    Article  Google Scholar 

  • Kircanski, K., Notthoff, N., DeLiema, M., Samanez-Larkin, G. R., Shadel, D., Mottola, G., … Gotlib, I. H. (2018). Emotional arousal may increase susceptibility to fraud in older and younger adults. Psychology and Aging, 33(2), 325.

    Article  Google Scholar 

  • Knoch, D., Gianotti, L. R., Pascual-Leone, A., Treyer, V., Regard, M., Hohmann, M., & Brugger, P. (2006). Disruption of right prefrontal cortex by low-frequency repetitive transcranial magnetic stimulation induces risk-taking behavior. Journal of Neuroscience, 26(24), 6469–6472.

    Article  Google Scholar 

  • Kobayakawa, M., Koyama, S., Mimura, M., & Kawamura, M. (2008). Decision making in Parkinson’s disease: Analysis of behavioral and physiological patterns in the Iowa gambling task. Movement Disorders, 23(4), 547–552.

    Article  Google Scholar 

  • Krawczyk, D. C., & D’esposito, M. (2013). Modulation of working memory function by motivation through loss-aversion. Human Brain Mapping, 34(4), 762–774.

    Article  Google Scholar 

  • Lee, J. K., Moon, S. Y., & Park, J. H. (2017). CloudRPS: A cloud analysis based enhanced ransomware prevention system. The Journal of Supercomputing, 73(7), 3065–3084.

    Article  Google Scholar 

  • Leng, Y., & Zhou, X. (2014). Interpersonal relationship modulates brain responses to outcome evaluation when gambling for/against others: An electrophysiological analysis. Neuropsychologia, 63, 205–214.

    Article  Google Scholar 

  • Li, Y. J., Kenrick, D. T., Griskevicius, V., & Neuberg, S. L. (2012). Economic decision biases and fundamental motivations: How mating and self-protection alter loss aversion. Journal of Personality and Social Psychology, 102(3), 550.

    Article  Google Scholar 

  • Liu, Y., Nelson, L. D., Bernat, E. M., & Gehring, W. J. (2014). Perceptual properties of feedback stimuli influence the feedback-related negativity in the flanker gambling task. Psychophysiology, 51(8), 782–788.

    Article  Google Scholar 

  • Luck, S. J. (2014). An introduction to the event-related potential technique. Cambridge, MA: MIT Press.

    Google Scholar 

  • Luo, X., & Liao, Q. (2007). Awareness education as the key to ransomware prevention. Information Systems Security, 16(4), 195–202.

    Article  Google Scholar 

  • Masaki, H., Takeuchi, S., Gehring, W. J., Takasawa, N., & Yamazaki, K. (2006). Affective-motivational influences on feedback-related ERPs in a gambling task. Brain Research, 1105(1), 110–121.

    Article  Google Scholar 

  • Minati, L., Grisoli, M., Franceschetti, S., Epifani, F., Granvillano, A., Medford, N., … Critchley, H. D. (2012). Neural signatures of economic parameters during decision-making: A functional MRI (FMRI), electroencephalography (EEG) and autonomic monitoring study. Brain Topography, 25(1), 73–96.

    Article  Google Scholar 

  • Modic, D., Anderson, R., & Palomäki, J. (2018). We will make you like our research: The development of a susceptibility-to-persuasion scale. PLoS One, 13(3), e0194119.

    Article  Google Scholar 

  • Paddon, D. (2018, May 16), Dozens of Canadian firms have paid ransoms to regain control of data, study finds. The Globe and Mail. Retrieved from http://www.theglobeandmail.com/report-on-business/study-finds-dozens-of-canadian-firms-have-paid-ransoms-to-regain-control-of-data/article31253317/

  • Patyal, M., Sampalli, S., Ye, Q., & Rahman, M. (2017). Multi-layered defense architecture against ransomware. International Journal of Business and Cyber Security, 1(2), 52–64.

    Google Scholar 

  • Polman, E. (2012). Self–other decision making and loss aversion. Organizational Behavior and Human Decision Processes, 119(2), 141–150.

    Article  Google Scholar 

  • Richardson, R., & North, M. M. (2017). Ransomware: Evolution, mitigation and prevention. International Management Review, 13(1), 10–21.

    Google Scholar 

  • Rozendaal, E., Buijs, L., & Reijmersdal, E. A. V. (2016). Strengthening children’s advertising defenses: The effects of forewarning of commercial and manipulative intent. Frontiers in Psychology, 7, 1186.

    Article  Google Scholar 

  • Sagarin, B. J., Cialdini, R. B., Rice, W. E., & Serna, S. B. (2002). Dispelling the illusion of invulnerability: The motivations and mechanisms of resistance to persuasion. Journal of Personality and Social Psychology, 83(3), 526.

    Article  Google Scholar 

  • Schonberg, T., Fox, C. R., & Poldrack, R. A. (2011). Mind the gap: Bridging economic and naturalistic risk-taking with cognitive neuroscience. Trends in Cognitive Sciences, 15(1), 11–19.

    Article  Google Scholar 

  • Schutte, I., Kenemans, J. L., & Schutter, D. J. (2017). Resting-state theta/beta EEG ratio is associated with reward-and punishment-related reversal learning. Cognitive, Affective, & Behavioral Neuroscience, 17(4), 1–10.

    Article  Google Scholar 

  • Symantec. (2016). Symantec 2016 Internet security threat report. Tempe, AZ: Symantec.

    Google Scholar 

  • Takács, Á., Kóbor, A., Janacsek, K., Honbolygó, F., Csépe, V., & Németh, D. (2015). High trait anxiety is associated with attenuated feedback-related negativity in risky decision making. Neuroscience Letters, 600, 188–192.

    Article  Google Scholar 

  • Taylor, S. E. (1991). Asymmetrical effects of positive and negative events: The mobilization-minimization hypothesis. Psychological Bulletin, 110(1), 67.

    Article  Google Scholar 

  • Taylor, S. F., Martis, B., Fitzgerald, K. D., Welsh, R. C., Abelson, J. L., Liberzon, I., … Gehring, W. J. (2006). Medial frontal cortex activity and loss-related responses to errors. Journal of Neuroscience, 26(15), 4063–4070.

    Article  Google Scholar 

  • Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The neural basis of loss aversion in decision-making under risk. Science, 315(5811), 515–518.

    Article  Google Scholar 

  • Treadway, M. T., Buckholtz, J. W., & Zald, D. (2013). Perceived stress predicts altered reward and loss feedback processing in medial prefrontal cortex. Frontiers in Human Neuroscience, 7, 180.

    Article  Google Scholar 

  • Trustwave. (2017). 2017 Trustwave global security report. Chicago, IL: Trustwave. Retrieved from https://www.trustwave.com/en-us/resources/library/documents/2017-trustwave-global-security-report/

    Google Scholar 

  • Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference-dependent model. The Quarterly Journal of Economics, 106(4), 1039–1061.

    Article  Google Scholar 

  • van de Weijer, S. G., & Leukfeldt, E. R. (2017). Big five personality traits of cybercrime victims. Cyberpsychology, Behavior and Social Networking, 20(7), 407–412.

    Article  Google Scholar 

  • Vance, A., Anderson, B. B., Kirwan, C. B., & Eargle, D. (2014). Using measures of risk perception to predict information security behavior: Insights from electroencephalography (EEG). Journal of the Association for Information Systems, 15(10), 679.

    Article  Google Scholar 

  • Welte, J. W., Barnes, G. M., Tidwell, M. C. O., & Hoffman, J. H. (2011). Gambling and problem gambling across the lifespan. Journal of Gambling Studies, 27(1), 49–61.

    Article  Google Scholar 

  • West, R., Tiernan, B. N., Kieffaber, P. D., Bailey, K., & Anderson, S. (2014). The effects of age on the neural correlates of feedback processing in a naturalistic gambling game. Psychophysiology, 51(8), 734–745.

    Article  Google Scholar 

  • Whitty, M. T., & Buchanan, T. (2012). The online romance scam: A serious cybercrime. CyberPsychology, Behavior, and Social Networking, 15(3), 181–183.

    Article  Google Scholar 

  • Wohl, M. J., Christie, K. L., Matheson, K., & Anisman, H. (2010). Animation-based education as a gambling prevention tool: Correcting erroneous cognitions and reducing the frequency of exceeding limits among slots players. Journal of Gambling Studies, 26(3), 469–486.

    Article  Google Scholar 

  • Yeung, N., Holroyd, C. B., & Cohen, J. D. (2004). ERP correlates of feedback and reward processing in the presence and absence of response choice. Cerebral Cortex, 15(5), 535–544.

    Article  Google Scholar 

  • Zheng, Y., Li, Q., Wang, K., Wu, H., & Liu, X. (2015). Contextual valence modulates the neural dynamics of risk processing. Psychophysiology, 52(7), 895–904.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David L. McIntyre .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

McIntyre, D.L., Frank, R. (2021). No Gambles with Information Security: The Victim Psychology of a Ransomware Attack. In: Weulen Kranenbarg, M., Leukfeldt, R. (eds) Cybercrime in Context. Crime and Justice in Digital Society, vol I. Springer, Cham. https://doi.org/10.1007/978-3-030-60527-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-60527-8_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60526-1

  • Online ISBN: 978-3-030-60527-8

  • eBook Packages: Law and CriminologyLaw and Criminology (R0)

Publish with us

Policies and ethics