Skip to main content

Human Characteristics and Genomic Factors as Behavioural Aspects for Cybersecurity

  • 893 Accesses

Part of the Lecture Notes in Computer Science book series (LNAI,volume 12776)

Abstract

Modern behavioural genetic studies of personality investigate the genetic and environmental contribution to the development of personality and the genetic and environmental covariance with a range of characteristics, as well as stress, impulsiveness, and addiction. Cyber kill chains are used to define stages of the incident and to position an event. The risky behaviour, possible human addictions, and weaknesses are used in the evaluation, selecting the best human-to-human or human-machine-human interactions strategy. An unintentional human error can cause cybersecurity breaches, because stress, long working hours, and set of wide-range responsibilities lower caution and increase the impact of individual characteristics on the decision rationality. This work aims to hypothesise a possible holistic architecture for specific human behaviour factors involved in cybersecurity risks. A good cybersecurity habit could prevent incidents and protect against attacks. Habits are mostly initiated automatically. Therefore, they can dominate personal behavioural patterns under specific circumstances. Genetic heritability of impulsiveness is considered as moderate from 33% to 50%. Genomic data study of particular individuals can help identify one’s behaviour patterns and show the risks in cybersecurity for that individual. An individual risk profile could be generated by combining known genome variants linked to a trait of particular behaviour analysing molecular pathways of Dopamin, Serotonin, Catecholaminergic, GABAergic, neurons migration, Opioid, cannabinoid system and other addiction genes. Construction of a model strategy when including genomic information results for the specification of human behavioural characteristics might benefit towards higher risk assessment in cybersecurity processes.

Keywords

  • Behaviour genomics
  • Impulsiveness
  • Risky behaviour
  • Decision-making
  • Impulse control
  • Genome variation
  • Cybersecurity
  • Cyber kill-chain

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-78114-9_23
  • Chapter length: 18 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-78114-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.

References

  1. Assary, E., Zavos, H.M., Krapohl, E., Keers, R., Pluess, M.: Genetic architecture of environmental sensitivity reflects multiple heritable components: a twin study with adolescents. Mol. Psychiatry 2020, 1–9 (2020). https://doi.org/10.1038/s41380-020-0783-8

    CrossRef  Google Scholar 

  2. Barr, P.B., Dick, D.M.: The genetics of externalizing problems. In: de Wit, H., Jentsch, J.D. (eds.) Recent Advances in Research on Impulsivity and Impulsive Behaviors. CTBN, vol. 47, pp. 93–112. Springer, Cham (2019). https://doi.org/10.1007/7854_2019_120

    CrossRef  Google Scholar 

  3. Barrot, C., et al.: Relationships between the molecular basis of impulsivity and suicidal behavior. Forensic Sci. Int.: Genet. Suppl. Ser. 5, e530–e531 (2015)

    Google Scholar 

  4. Bauer, L.O., Yang, B.Z., Houston, R.J., Kranzler, H.R., Gelernter, J.: GABRA2 genotype, impulsivity, and body mass. Am. J. Addict. 21(5), 404–410 (2012)

    Google Scholar 

  5. Benko, A., et al.: Significant association between the C(- 1019) G functional polymorphism of the HTR1A gene and impulsivity. Am. J. Med. Genet. Part B: Neuropsychiatric Genet. 153(2), 592–599 (2010)

    Google Scholar 

  6. Bevilacqua, L., et al.: A population-specific HTR2B stop codon predisposes to severe impulsivity. Nature 468(7327), 1061–1066 (2010)

    Google Scholar 

  7. Bevilacqua, L., Goldman, D.: Genetics of impulsive behaviour. Philos. Trans. Roy. Soc. B: Biol. Sci. 368(1615), 20120380 (2013)

    Google Scholar 

  8. Boardman, J.D., Daw, J., Freese, J.: Defining the environment in gene-environment research: lessons from social epidemiology. Am. J. Public Health 103(S1), S64–S72 (2013)

    Google Scholar 

  9. Border, R., et al.: No support for historical candidate gene or candidate gene-by-interaction hypotheses for major depression across multiple large samples. Am. J. Psychiatry 176(5), 376–387 (2019)

    Google Scholar 

  10. Brewer III, A.J., et al.: Genetic variation of the dopamine transporter (DAT1) influences the acute subjective responses to cocaine in volunteers with cocaine use disorders. Pharmacogenet. Genomics 25(6), 296 (2015)

    Google Scholar 

  11. Bulik-Sullivan, B.K., et al.: LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47(3), 291–295 (2015)

    Google Scholar 

  12. Burns, J.A., et al.: Molecular imaging of opioid and dopamine systems: insights into the pharmacogenetics of opioid use disorders. Front. Psychiatry 10, 626 (2019)

    Google Scholar 

  13. Capecchi, M.R.: Gene targeting in mice: functional analysis of the mammalian genome for the twenty-first century. Nat. Rev. Genet. 6(6), 507–512 (2005)

    Google Scholar 

  14. Chan, T., et al.: Impulsivity and genetic variants in DRD2 and ANKK1 moderate longitudinal associations between sleep problems and overweight from ages 5 to 11. Int. J. Obesity 38(3), 404–410 (2014)

    Google Scholar 

  15. Chester, D.S., et al.: Monoamine oxidase a (MAOA) genotype predicts greater aggression through impulsive reactivity to negative affect. Behav. Brain Res. 283, 97–101 (2015)

    Google Scholar 

  16. Chowdhury, N.H., Adam, M.T., Teubner, T.: Time pressure in human cybersecurity behavior: theoretical framework and countermeasures. Comput. Secur. 97 (2020). https://doi.org/10.1016/j.cose.2020.101931

  17. Conner, T.S., Jensen, K.P., Tennen, H., Furneaux, H.M., Kranzler, H.R., Covault, J.: Functional polymorphisms in the serotonin 1B receptor gene (HTR1B) predict self-reported anger and hostility among young men. Am. J. Med. Genet. Part B: Neuropsychiatric Genet. 153(1), 67–78 (2010)

    Google Scholar 

  18. Cummins, T., et al.: Dopamine transporter genotype predicts behavioural and neural measures of response inhibition. Mol. Psychiatry 17(11), 1086–1092 (2012)

    Google Scholar 

  19. Dick, D.M.: Gene-environment interaction in psychological traits and disorders. Ann. Rev. Clin. Psychol. 7, 383–409 (2011)

    Google Scholar 

  20. Donalds, C., Osei-Bryson, K.M.: Cybersecurity compliance behavior: exploring the influences of individual decision style and other antecedents. Int. J. Inf. Manag. 51 (2020). https://doi.org/10.1016/j.ijinfomgt.2019.102056

  21. Duncan, L.E., Keller, M.C.: A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry. Am. J. Psychiatry 168(10), 1041–1049 (2011)

    Google Scholar 

  22. ENISA: Cybersecurity culture guidelines: behavioural aspects of cybersecurity. European Union Agency for Network and Information Security (2018). https://doi.org/10.2824/324042

  23. Ersche, K.D., Turton, A.J., Pradhan, S., Bullmore, E.T., Robbins, T.W.: Drug addiction endophenotypes: impulsive versus sensation-seeking personality traits. Biol. Psychiatry 68(8), 770–773 (2010)

    Google Scholar 

  24. Ertan, A., Crossland, G., Heath, C., Denny, D., Jensen, R.B.: Cyber security behaviour in organisations. CoRR abs/2004.11768 (2020). https://arxiv.org/abs/2004.11768

  25. Evenden, J.L.: Varieties of impulsivity. Psychopharmacology 146(4), 348–361 (1999). https://doi.org/10.1007/PL00005481

    CrossRef  Google Scholar 

  26. Fatemi, S.H.: Reelin glycoprotein: structure, biology and roles in health and disease. Mol. Psychiatry 10(3), 251–257 (2005)

    Google Scholar 

  27. Findling, C., Chopin, N., Koechlin, E.: Imprecise neural computations as a source of adaptive behaviour in volatile environments. Nat. Hum. Behav. 5, 99–112 (2021). https://doi.org/10.1038/s41562-020-00971-z

    CrossRef  Google Scholar 

  28. Gadow, K.D., et al.: Allele-specific associations of 5-HTTLPR/rs25531 with ADHD and autism spectrum disorder. Progr. Neuro-Psychopharmacol. Biol. Psychiatry 40, 292–297 (2013)

    Google Scholar 

  29. Genis-Mendoza, A.D., et al.: Genetic association analysis of 5-HTR2A gene variants in eating disorders in a Mexican population. Brain Behav. 9(7) (2019)

    Google Scholar 

  30. Gordon, B., Caramazza, A.: Lexical decision for open-and closed-class words: failure to replicate differential frequency sensitivity. Brain Lang. 15(1), 143–160 (1982)

    Google Scholar 

  31. Gray, J.C., et al.: Genetic analysis of impulsive personality traits: examination of a priori candidates and genome-wide variation. Psychiatry Res. 259, 398–404 (2018)

    Google Scholar 

  32. Groman, S.M.: The neurobiology of impulsive decision-making and reinforcement learning in nonhuman animals. In: de Wit, H., Jentsch, J.D. (eds.) Recent Advances in Research on Impulsivity and Impulsive Behaviors. CTBN, vol. 47, pp. 23–52. Springer, Cham (2020). https://doi.org/10.1007/7854_2020_127

    CrossRef  Google Scholar 

  33. Grotzinger, A.D., et al.: Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits. Nat. Hum. Behav. 3(5), 513–525 (2019)

    Google Scholar 

  34. Gustavson, D.E., et al.: The latent genetic structure of impulsivity and its relation to internalizing psychopathology. Psychol. Sci. 31(8), 1025–1035 (2020)

    Google Scholar 

  35. Hadlington, L.: Human factors in cybersecurity; examining the link between internet addiction, impulsivity, attitudes towards cybersecurity, and risky cybersecurity behaviours. Heliyon 3(7) (2017). https://doi.org/10.1016/j.heliyon.2017.e00346

  36. Hadlington, L., Popovac, M., Janicke, H., Yevseyeva, I., Jones, K.: Exploring the role of work identity and work locus of control in information security awareness. Comput. Secur. 81, 41–48 (2019). https://doi.org/10.1016/j.cose.2018.10.006

    CrossRef  Google Scholar 

  37. Hariri, A.R., Weinberger, D.R.: Imaging genomics. Br. Med. Bull. 65(1), 259–270 (2003). https://doi.org/10.1093/bmb/65.1.259

    CrossRef  Google Scholar 

  38. Hong, Y., Furnell, S.: Understanding cybersecurity behavioral habits: insights from situational support. J. Inf. Secur. Appl. 57 (2021). https://doi.org/10.1016/j.jisa.2020.102710

  39. Hutchins, E., Cloppert, M., Amin, R.: Intelligence-driven computer network defense informed by analysis of adversary campaigns and intrusion kill chains. Lead. Issues Inf. Warfare Secur. Res. 1(1), 80 (2011)

    Google Scholar 

  40. Hutchins, E.M., Cloppert, M.J., Amin, R.M.: Intelligence-Driven Computer Network Defense Informed by Analysis of Adversary Campaigns and Intrusion Kill Chains (2011). https://www.lockheedmartin.com/content/dam/lockheed-martin/rms/documents/cyber/LM-White-Paper-Intel-Driven-Defense.pdf. Lockheed Martin Corporation. White paper

  41. International Schizophrenia Consortium, et al.: Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009). https://doi.org/10.1038/nature08185

  42. Juárez Olguín, H., Calderon Guzman, D., Hernandez Garcia, E., Barragan Mejia, G.: The role of dopamine and its dysfunction as a consequence of oxidative stress. Oxidative Med. Cell. Longevity 2016, 1–13 (2016)

    Google Scholar 

  43. Keller, M.C., Coventry, W.L., Heath, A.C., Martin, N.G.: Widespread evidence for non-additive genetic variation in Cloninger’s and Eysenck’s personality dimensions using a twin plus sibling design. Behav. Genet. 35(6), 707–721 (2005). https://doi.org/10.1007/s10519-005-6041-7

    CrossRef  Google Scholar 

  44. Khemiri, L., Kuja-Halkola, R., Larsson, H., Jayaram-Lindström, N.: Genetic overlap between impulsivity and alcohol dependence: a large-scale national twin study. Psychol. Med. 46(5), 1091 (2016)

    Google Scholar 

  45. Koeneke, A., Ponce, G., Troya-Balseca, J., Palomo, T., Hoenicka, J.: Ankyrin repeat and kinase domain containing 1 gene, and addiction vulnerability. Int. J. Mol. Sci. 21(7), 2516 (2020)

    Google Scholar 

  46. Kozak, K., Lucatch, A.M., Lowe, D.J., Balodis, I.M., MacKillop, J., George, T.P.: The neurobiology of impulsivity and substance use disorders: implications for treatment. Ann. New York Acad. Sci. 1451(1), 71 (2019)

    Google Scholar 

  47. Kranzler, H.R., et al.: Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat. Commun. 10(1), 1–11 (2019)

    Google Scholar 

  48. Krueger, R.F., Hicks, B.M., Patrick, C.J., Carlson, S.R., Iacono, W.G., McGue, M.: Etiologic connections among substance dependence, antisocial behavior, and personality: modeling the externalizing spectrum. J. Abnormal Psychol. 111(3) (2009)

    Google Scholar 

  49. Kuhn, B.N., Kalivas, P.W., Bobadilla, A.C.: Understanding addiction using animal models. Front. Behav. Neurosci. 13, 262 (2019)

    Google Scholar 

  50. Lahcen, R.A.M., Caulkins, B.D., Mohapatra, R., Kumar, M.: Review and insight on the behavioral aspects of cybersecurity. Cybersecurity 3(1), 10 (2020). https://doi.org/10.1186/s42400-020-00050-w

    CrossRef  Google Scholar 

  51. Logan, G.D., Cowan, W.B.: On the ability to inhibit thought and action: a theory of an act of control. Psychol. Rev. 91(3), 295 (1984)

    Google Scholar 

  52. Martel, M.M., Levinson, C.A., Lee, C.A., Smith, T.E.: Impulsivity symptoms as core to the developmental externalizing spectrum. J. Abnormal Child Psychol. 45(1), 83–90 (2017)

    Google Scholar 

  53. Mazur, J.E.: An adjusting procedure for studying delayed reinforcement. In: Commons, M.L., Mazur, J.E. Nevin, J.A. (eds.) pp. 55–73 (1987)

    Google Scholar 

  54. McGuffin, P., Riley, B., Plomin, R.: Toward behavioral genomics. Science 291(5507), 1232–1249 (2001)

    Google Scholar 

  55. Montag, C., Kirsch, P., Sauer, C., Markett, S., Reuter, M.: The role of the CHRNA4 gene in internet addiction: a case-control study. J. Addict. Med. 6(3), 191–195 (2012)

    Google Scholar 

  56. Niv, S., Tuvblad, C., Raine, A., Wang, P., Baker, L.A.: Heritability and longitudinal stability of impulsivity in adolescence. Behav. Genet. 42(3), 378–392 (2012). https://doi.org/10.1007/s10519-011-9518-6

    CrossRef  Google Scholar 

  57. Oh, B.: Direct-to-consumer genetic testing: advantages and pitfalls. Genomics Inform. 17(3), e33 (2019)

    Google Scholar 

  58. Pattij, T., Vanderschuren, L.J.M.J.: The neuropharmacology of impulsive behaviour, an update. In: de Wit, H., Jentsch, J.D. (eds.) Recent Advances in Research on Impulsivity and Impulsive Behaviors. CTBN, vol. 47, pp. 3–22. Springer, Cham (2020). https://doi.org/10.1007/7854_2020_143

    CrossRef  Google Scholar 

  59. Perry, J.L., Carroll, M.E.: The role of impulsive behavior in drug abuse. Psychopharmacology 200(1), 1–26 (2008). https://doi.org/10.1007/s00213-008-1173-0

    CrossRef  Google Scholar 

  60. Pietrzak, R.H., Sprague, A., Snyder, P.J.: Trait impulsiveness and executive function in healthy young adults. J. Res. Pers. 42(5), 1347–1351 (2008)

    Google Scholar 

  61. Reynolds, B., Ortengren, A., Richards, J.B., De Wit, H.: Dimensions of impulsive behavior: personality and behavioral measures. Pers. Individ. Differ. 40(2), 305–315 (2006)

    Google Scholar 

  62. Robertson, B.D., et al.: SLC6A3 polymorphism predisposes to dopamine overdose in Parkinson’s disease. Front. Neurol. 9, 693 (2018)

    Google Scholar 

  63. Rosvold, H.E., Mirsky, A.F., Sarason, I., Bransome Jr., E.D., Beck, L.H.: A continuous performance test of brain damage. J. Consult. Psychol. 20(5), 343–350 (1956)

    Google Scholar 

  64. Salvatore, J.E., Dick, D.M.: Genetic influences on conduct disorder. Neurosci. Biobehav. Rev. 91, 91–101 (2018)

    Google Scholar 

  65. Sanchez-Roige, S., et al.: Genome-wide association studies of impulsive personality traits (BIS-11 and UPPS-P) and drug experimentation in up to 22,861 adult research participants identify loci in the CACNA1I and CADM2 genes. J. Neurosci. 39(13), 2562–2572 (2019)

    Google Scholar 

  66. Shanahan, M.J., Hofer, S.M.: Social context in gene-environment interactions: Retrospect and prospect. J. Gerontol. Ser. B: Psychol. Sci. Soc. Sci. 60(Special_Issue_1), 65–76 (2005)

    Google Scholar 

  67. Slof-Op’t Landt, M.C., et al.: Genetic variation at the TPH2 gene influences impulsivity in addition to eating disorders. Behav. Genet. 43(1), 24–33 (2013). https://doi.org/10.1007/s10519-012-9569-3

    CrossRef  Google Scholar 

  68. Soeiro-De-Souza, M.G., Stanford, M.S., Bio, D.S., Machado-Vieira, R., Moreno, R.A.: Association of the COMT Met158 allele with trait impulsivity in healthy young adults. Mol. Med. Rep. 7(4), 1067–1072 (2013)

    Google Scholar 

  69. Sonuga-Barke, E.J., et al.: A functional variant of the serotonin transporter gene (SLC6A4) moderates impulsive choice in attention-deficit/hyperactivity disorder boys and siblings. Biol. Psychiatry 70(3), 230–236 (2011)

    Google Scholar 

  70. Stoltenberg, S.F., Lehmann, M.K., Christ, C.C., Hersrud, S.L., Davies, G.E.: Associations among types of impulsivity, substance use problems and neurexin-3 polymorphisms. Drug Alcohol Depend. 119(3), e31–e38 (2011)

    Google Scholar 

  71. Tandy-Connor, S., et al.: False-positive results released by direct-to-consumer genetic tests highlight the importance of clinical confirmation testing for appropriate patient care. Genet. Med. 20(12), 1515–1521 (2018)

    Google Scholar 

  72. The European Parliament and the Council of the European Union: Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). Official Journal of the European Union (2016)

    Google Scholar 

  73. Torgersen, S.: Behavioral genetics of personality. Cur. Psychiatry Rep. 7, 51–56 (2005). https://doi.org/10.1007/s11920-005-0025-4

    CrossRef  Google Scholar 

  74. Ullsperger, M.: Imprecise learning and uncertainty. Nat. Hum. Behav. 1–2 (2020)

    Google Scholar 

  75. Varga, G., et al.: Additive effects of serotonergic and dopaminergic polymorphisms on trait impulsivity. Am. J. Med. Genet. Part B: Neuropsychiatric Genet. 159(3), 281–288 (2012)

    Google Scholar 

  76. Verdejo-García, A., Lawrence, A.J., Clark, L.: Impulsivity as a vulnerability marker for substance-use disorders: review of findings from high-risk research, problem gamblers and genetic association studies. Neurosci. Biobehav. Rev. 32(4), 777–810 (2008)

    Google Scholar 

  77. Visscher, P.M., et al.: 10 years of GWAS discovery: biology, function, and translation. Am. J. Hum. Genet. 101(1), 5–22 (2017)

    Google Scholar 

  78. Walters, R.K., et al.: Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nat. Neurosci. 21(12), 1656–1669 (2018)

    Google Scholar 

  79. Wellcome Trust Case Control Consortium and others: Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447(7145), 661 (2007)

    Google Scholar 

  80. Whiteside, S.P., Lynam, D.R.: The five factor model and impulsivity: using a structural model of personality to understand impulsivity. Pers. Individ. Differ. 30(4), 669–689 (2001)

    Google Scholar 

  81. Wrzosek, M., et al.: Association between Fok I vitamin D receptor gene (VDR) polymorphism and impulsivity in alcohol-dependent patients. Mol. Biol. Rep. 41(11), 7223–7228 (2014)

    Google Scholar 

  82. Young, S.E., Stallings, M.C., Corley, R.P., Krauter, K.S., Hewitt, J.K.: Genetic and environmental influences on behavioral disinhibition. Am. J. Med. Genet. 96(5), 684–695 (2000)

    Google Scholar 

Download references

Acknowledgements

This work was partially supported by project Advancing Human Performance in Cybersecurity, ADVANCES. The ADVANCES is funded by Iceland, Liechtenstein and Norway through the EEA Grants.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Laima Ambrozaitytė .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Ambrozaitytė, L., Brilingaitė, A., Bukauskas, L., Domarkienė, I., Rančelis, T. (2021). Human Characteristics and Genomic Factors as Behavioural Aspects for Cybersecurity. In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Augmented Cognition. HCII 2021. Lecture Notes in Computer Science(), vol 12776. Springer, Cham. https://doi.org/10.1007/978-3-030-78114-9_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78114-9_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78113-2

  • Online ISBN: 978-3-030-78114-9

  • eBook Packages: Computer ScienceComputer Science (R0)