Skip to main content
SpringerLink
Log in

Framework Proposal to Measure the Stress as Adversarial Factor on Cyber Decision Making

  • Conference paper
  • First Online:
Computer Security. ESORICS 2021 International Workshops (ESORICS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 13106))

Included in the following conference series:

Abstract

There are several factors that make cyber operations stressful, which include their complexity, unpredictability, and a continuum of decisions involving high risk and fast cost-benefit reasoning. Thus, in this context, defining a working methodology or framework to assess and quantify the impact of stress during decision making can be extremely useful both in real operations and in cyber exercises (to enhance decision making skills). Defining this framework is not a trivial task due to the complexity of stress and the innumerable subjective nuances associated with it, which correspond to the characteristics of each individual.

This paper presents stress understood as a disease and introduces the main current biometric systems that allow inferring and quantifying the stress level of an individual. Secondly, the main methodologies that allow to evaluate the stress level of a person are presented. Thirdly, a framework composed of five stages (monitoring, visualization, risk management, evaluation, decision making) is defined to model and standardize a methodology for assessing the level of stress in cyber-operations. Fourthly, a validation scenario is proposed to test the proposed framework. Finally, the procedure for the use of the methodology is defined and future directions for the continuation of this research are proposed.

This research has received funding from the European Defence Industrial Development Programme (EDIDP) under the grant agreement Number EDIDP-CSAMN-SSC-2019-022-ECYSAP (European Cyber SituationalAwareness Platform).

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Institutional subscriptions

References

  1. Sandoval Rodríguez-Bermejo, D., Maestre Vidal, J., Estévez Tapiador, J.: The stress as adversarial factor for cyber decision making. In: The 16th International Conference on Availability, Reliability and Security, pp. 1–10 (2021)

    Google Scholar 

  2. Dykstra, J., Paul, C.L.: Cyber operations stress survey (COSS): studying fatigue, frustration, and cognitive workload in cybersecurity operations. In: 11th USENIX Workshop on Cyber Security Experimentation and Test (CSET 2018), Baltimore, MD, August 2018. USENIX Association (2018). https://www.usenix.org/conference/cset18/presentation/dykstra

  3. Wemm, S.E., Wulfert, E.: Effects of acute stress on decision making. Appl. Psychophysiol. Biofeedback 42(1), 1–12 (2017). https://doi.org/10.1007/s10484-016-9347-8

    Article  Google Scholar 

  4. Maestre Vidal, J., Sotelo Monge, M.A.: Denial of sustainability on military tactical clouds. In: 15th International Conference on Availability, Reliability and Security (ARES), Dublin, Ireland, pp. 1–9, August 2020

    Google Scholar 

  5. Endsley, M.R., Selcon, S.J., Hardiman, T.D., Croft, D.G.: A comparative analysis of SAGAT and SART for evaluations of situation awareness. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 42, pp. 82–86. SAGE Publications, Los Angeles (1998)

    Google Scholar 

  6. Maestre Vidal, J., Sotelo Monge, M.A.: Framework for anticipatory self-protective 5G environments. In: 14th International Conference on Availability, Reliability and Security (ARES) (2019)

    Google Scholar 

  7. Maestre Vidal, J., Sotelo Monge, M.A.: A novel self-organizing network solution towards crypto-ransomware mitigation. In: 13th International Conference on Availability, Reliability and Security (ARES) (2018)

    Google Scholar 

  8. Belloch, A., Bonifacio, S., Francisco, R.: Manual de psicopatología (2008)

    Google Scholar 

  9. Selye, H.: The Stress of Life. McGran-Hill Book Company, New York (1956)

    Google Scholar 

  10. Cannon, W.B.: The wisdom of the body, New York (1932). Harvey’s work with bodily circulation looms over this book. In his chapter “Feedback and Oscillation," Norbert Wierner redefined homeostasis in terms of information: cybernetics, or control and communication in the animal and the machine, (Cambridge, Mass., 1961), esp, pp. 114–15 (1932)

    Google Scholar 

  11. Cox, T.: Stress: a review of theories, causes and effects of stress in the light of empirical research (1978)

    Google Scholar 

  12. Lazarus, R.S., Folkman, S.: Stress, Appraisal, and Coping. Springer, New York (1984)

    Google Scholar 

  13. Lazarus, R.S.: Coping theory and research: past, present, and future. In: Fifty Years of the Research and Theory of RS Lazarus: An Analysis of Historical and Perennial Issues, pp. 366–388 (1993)

    Google Scholar 

  14. Levine, J.A., Pavlidis, I., Cooper, M.: The face of fear. The Lancet 357(9270), 1757 (2001)

    Article  Google Scholar 

  15. Puri, C., Olson, L., Pavlidis, I., Levine, J., Starren, J.: StressCam: non-contact measurement of users’ emotional states through thermal imaging. In: CHI 2005 Extended Abstracts on Human Factors in Computing Systems, pp. 1725–1728 (2005)

    Google Scholar 

  16. Merla, A., Romani, G.L.: Thermal signatures of emotional arousal: a functional infrared imaging study. In: 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 247–249. IEEE (2007)

    Google Scholar 

  17. Ballinger, B., et al.: DeepHeart: semi-supervised sequence learning for cardiovascular risk prediction. arXiv preprint arXiv:1802.02511 (2018)

  18. Mousavi, S., Afghah, F., Razi, A., Acharya, U.R.: ECGNET: learning where to attend for detection of atrial fibrillation with deep visual attention. In: 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), pp. 1–4. IEEE (2019)

    Google Scholar 

  19. Mundell, C., Vielma, J.P., Zaman, T.: Predicting performance under stressful conditions using galvanic skin response. arXiv preprint arXiv:1606.01836 (2016)

  20. Hernandez-Ortega, J., Daza, R., Morales, A., Fierrez, J., Ortega-Garcia, J.: edBB: biometrics and behavior for assessing remote education. arXiv preprint arXiv:1912.04786 (2019)

  21. Mequanint, E., Zhang, S., Forutanpour, B., Qi, Y., Bi, N.: Weakly-supervised degree of eye-closeness estimation. In: Proceedings of the IEEE International Conference on Computer Vision Workshops (2019)

    Google Scholar 

  22. Minadakis, G., Lohan, K.: Using pupil diameter to measure cognitive load. arXiv preprint arXiv:1812.07653 (2018)

  23. Sandoval Rodríguez-Bermejo, D., Ugena, A.M.: Diseño e implementación de un sistema para la detección del estrés mediante redes neuronales convolucionales a partir de imágenes térmicas. Master’s thesis, Universidad Politécnica de Madrid (2019)

    Google Scholar 

  24. Skoluda, N., et al.: Intra-individual psychological and physiological responses to acute laboratory stressors of different intensity. Psychoneuroendocrinology 51, 227–236 (2015)

    Article  Google Scholar 

  25. Hou, X., Liu, Y., Sourina, O., Tan, Y.R.E., Wang, L., Mueller-Wittig, W.: EEG based stress monitoring. In: 2015 IEEE International Conference on Systems, Man, and Cybernetics, pp. 3110–3115. IEEE (2015)

    Google Scholar 

  26. Tulen, J.H.M., Moleman, P., Van Steenis, H.G., Boomsma, F.: Characterization of stress reactions to the Stroop Color Word Test. Pharmacol. Biochem. Behav. 32(1), 9–15 (1989)

    Article  Google Scholar 

  27. Kirschbaum, C., Pirke, K.-M., Hellhammer, D.H.: The ‘Trier Social Stress Test’-a tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiology 28(1–2), 76–81 (1993)

    Article  Google Scholar 

  28. Poh, C.H., et al.: The effect of antireflux treatment on patients with gastroesophageal reflux disease undergoing a mental arithmetic stressor. Neurogastroenterol. Motil. 23(11), e489–e496 (2011)

    Article  Google Scholar 

  29. Stroop, J.R.: Studies of interference in serial verbal reactions. J. Exp. Psychol. Gen. 121(1), 15 (1992)

    Article  Google Scholar 

  30. Šiška, E.: The stroop colour-word test in psychology and biomedicine. Acta Universitatis Palackianae Olomucensis. Gymnica 32(1), 45–52 (2002)

    Google Scholar 

  31. Payne, J.D., Nadel, L., Allen, J.J.B., Thomas, K.G.F., Jacobs, W.J.: The effects of experimentally induced stress on false recognition. Memory 10(1), 1–6 (2002)

    Article  Google Scholar 

  32. Smeets, T., Cornelisse, S., Quaedflieg, C.W.E.M., Meyer, T., Jelicic, M., Merckelbach, H.: Introducing the Maastricht Acute Stress Test (MAST): a quick and non-invasive approach to elicit robust autonomic and glucocorticoid stress responses. Psychoneuroendocrinology 37(12), 1998–2008 (2012)

    Article  Google Scholar 

  33. Yuenyongchaiwat, K.: Cardiovascular response to mental stress tests and the prediction of blood pressure. Indian J. Psychol. Med. 39(4), 413 (2017)

    Article  Google Scholar 

  34. Longo, L.: Experienced mental workload, perception of usability, their interaction and impact on task performance. PLoS ONE 13(8), e0199661 (2018)

    Article  Google Scholar 

  35. Young, M.S., Brookhuis, K.A., Wickens, C.D., Hancock, P.A.: State of science: mental workload in ergonomics. Ergonomics 58(1), 1–17 (2015)

    Article  Google Scholar 

  36. Cain, B.: A review of the mental workload literature. Technical report, Defence Research And Development Toronto, Canada (2007)

    Google Scholar 

  37. Xie, B., Salvendy, G.: Review and reappraisal of modelling and predicting mental workload in single-and multi-task environments. Work Stress. 14(1), 74–99 (2000)

    Article  Google Scholar 

  38. Brooke, J.: SUS: a ‘quick and dirty’ usability, p. 189. Usability Evaluation in Industry (1996)

    Google Scholar 

  39. Hart, S.G.: NASA-task load index (NASA-TLX); 20 years later. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 50, pp. 904–908. Sage Publications, Los Angeles (2006)

    Google Scholar 

  40. Reid, G.B., Nygren, T.E.: The subjective workload assessment technique: a scaling procedure for measuring mental workload. Adv. Psychol. 52, 185–218 (1988)

    Article  Google Scholar 

  41. Tsang, P.S., Velazquez, V.L.: Diagnosticity and multidimensional subjective workload ratings. Ergonomics 39(3), 358–381 (1996)

    Article  Google Scholar 

  42. Zijlstra, F.R.H.: Efficiency in work behaviour: a design approach for modern tools (1995)

    Google Scholar 

  43. Vidullch, M.A., Ward, G.F., Schueren, J.: Using the subjective workload dominance (SWORD) technique for projective workload assessment. Hum. Factors 33(6), 677–691 (1991)

    Article  Google Scholar 

  44. Salmon, P.M., et al.: Measuring situation awareness in complex systems: comparison of measures study. Int. J. Ind. Ergon. 39(3), 490–500 (2009)

    Article  Google Scholar 

  45. Endsley, M.R.: Direct measurement of situation awareness: validity and use of SAGAT. In: Situation Awareness Analysis and Measurement, vol. 10, pp. 147–173 (2000)

    Google Scholar 

  46. Taylor, R.M.: Situational awareness rating technique (SART): the development of a tool for aircrew systems design. In: Situational Awareness, pp. 111–128. Routledge (2017)

    Google Scholar 

  47. Elasticsearch B.V.: ELK stack (2020). https://www.elastic.co/es/elk-stack

  48. Maestre Vidal, J., Sotelo Monge, M.A.: Obfuscation of malicious behaviors for thwarting masquerade detection systems based on locality features. Sensors 20(7), 2084 (2020)

    Article  Google Scholar 

Download references

Acknowledgment

figure a

This research has received funding from the European Defence Industrial Development Programme (EDIDP) under the grant agreement Number EDIDP-CSAMN-SSC-2019-022-ECYSAP (European Cyber Situational Awareness Platform).

Author information

Authors and Affiliations

  1. Tarlogic, Madrid, Spain

    David Sandoval Rodríguez-Bermejo

  2. Indra, Madrid, Spain

    Jorge Maestre Vidal

  3. Universidad Carlos III de Madrid, Madrid, Spain

    David Sandoval Rodríguez-Bermejo & Juan Manuel Estévez Tapiador

Authors
  1. David Sandoval Rodríguez-Bermejo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jorge Maestre Vidal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juan Manuel Estévez Tapiador
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jorge Maestre Vidal .

Editor information

Editors and Affiliations

  1. Norwegian University of Science and Technology, Gjøvik, Norway

    Sokratis Katsikas

  2. University of Piraeus, Piraeus, Greece

    Costas Lambrinoudakis

  3. Polytechnique Montréal, Montréal, QC, Canada

    Nora Cuppens

  4. University of Toronto, Toronto, ON, Canada

    John Mylopoulos

  5. University of the Aegean, Mytilene, Greece

    Christos Kalloniatis

  6. Technical University of Denmark, Kongens Lyngby, Denmark

    Weizhi Meng

  7. University of Nottingham, Nottingham, UK

    Steven Furnell

  8. Technische Universität Berlin, Berlin, Germany

    Frank Pallas

  9. Alexander von Humboldt Institut für Internet und Gesellschaft gGmbH, Berlin, Germany

    Jörg Pohle

  10. Ruhr-Universität Bochum, Bochum, Germany

    M. Angela Sasse

  11. Norwegian Computing Center, Oslo, Norway

    Habtamu Abie

  12. University of Trento and Fondazione Bruno Kessler, Trento, Italy

    Silvio Ranise

  13. Università degli Studi di Genova, Genoa, Italy

    Luca Verderame

  14. Consiglio Nazionale delle Ricerche (CNR), Genoa, Italy

    Enrico Cambiaso

  15. Indra, Alcobendas, Spain

    Jorge Maestre Vidal

  16. Indra, Alcobendas, Spain

    Marco Antonio Sotelo Monge

Ethics declarations

Disclaimer

The contents reported in the paper reflect the opinions of the authors and do not necessarily reflect the opinions of the respective agencies, institutions or companies.

Appendix

Appendix

figure b
Table 1. Appendix A - Biometric calibration template
Full size table
figure c
Table 2. Appendix B - SART template
Full size table

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sandoval Rodríguez-Bermejo, D., Maestre Vidal, J., Estévez Tapiador, J.M. (2022). Framework Proposal to Measure the Stress as Adversarial Factor on Cyber Decision Making. In: Katsikas, S., et al. Computer Security. ESORICS 2021 International Workshops. ESORICS 2021. Lecture Notes in Computer Science(), vol 13106. Springer, Cham. https://doi.org/10.1007/978-3-030-95484-0_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-95484-0_30

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-95483-3

  • Online ISBN: 978-3-030-95484-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation