Book contents
- The Cambridge Handbook of Behavioural Data Science
- Cambridge Handbooks in Psychology
- Reviews
- The Cambridge Handbook of Behavioural Data Science
- Copyright page
- Dedication
- Contents
- Contributors
- Preface
- Introduction
- Part IIntroduction to Behavioural Data Science
- Part IIHuman Behaviour
- Part IIIAlgorithmic Behaviour
- Part IVSystems and Culture
- Part VApplications
- 29Applications of Behavioural Data Science
- 30Pro-Social Nudging
- 31Social Media Analytics
- 32Quantifying Luck
- 33Quantifying the Connection between Scenic Beauty and Reported Health Using Deep Learning and Econometrics
- 34Money, Methodology and Happiness
- 35Human–Data Interaction
- 36Natural Language Processing in Behavioural Data Science
- 37Understanding Collective Behaviour Using Online Data and Mobile Phones
- 38Burstier Events
- 39Behavioural Data Science in Financial Services
- 40XR, VR and AR Applications in Behavioural Data Science
- 41On Cryptoasset Traders’ Behaviour
- 42Behavioural Data Science of Cybersecurity
- 43Behavioural Data Science Ethics and Governance Pre-AI Act
- 44Behavioural Data Science Ethics and Governance Post-AI Act
- Part VIConcluding Remarks
- Main Abbreviations and Acronyms
- Glossary
- References
42 - Behavioural Data Science of Cybersecurity
from Part V - Applications
Published online by Cambridge University Press: 29 May 2026
Book contents
- The Cambridge Handbook of Behavioural Data Science
- Cambridge Handbooks in Psychology
- Reviews
- The Cambridge Handbook of Behavioural Data Science
- Copyright page
- Dedication
- Contents
- Contributors
- Preface
- Introduction
- Part IIntroduction to Behavioural Data Science
- Part IIHuman Behaviour
- Part IIIAlgorithmic Behaviour
- Part IVSystems and Culture
- Part VApplications
- 29Applications of Behavioural Data Science
- 30Pro-Social Nudging
- 31Social Media Analytics
- 32Quantifying Luck
- 33Quantifying the Connection between Scenic Beauty and Reported Health Using Deep Learning and Econometrics
- 34Money, Methodology and Happiness
- 35Human–Data Interaction
- 36Natural Language Processing in Behavioural Data Science
- 37Understanding Collective Behaviour Using Online Data and Mobile Phones
- 38Burstier Events
- 39Behavioural Data Science in Financial Services
- 40XR, VR and AR Applications in Behavioural Data Science
- 41On Cryptoasset Traders’ Behaviour
- 42Behavioural Data Science of Cybersecurity
- 43Behavioural Data Science Ethics and Governance Pre-AI Act
- 44Behavioural Data Science Ethics and Governance Post-AI Act
- Part VIConcluding Remarks
- Main Abbreviations and Acronyms
- Glossary
- References
Summary
Cybersecurity remains one of the most technically complex domains of contemporary risk management, yet much of its vulnerability stems not from systems themselves but from the behavioural patterns of their users and adversaries. This chapter introduces a Behavioural Data Science perspective on cybersecurity – an approach that foregrounds the cognitive, social and affective processes underlying digital decision-making and threat response. Moving beyond the dominant paradigm of technological hardening, this chapter explores how insights from behavioural science, combined with computational modelling, can illuminate the conditions under which individuals make secure or insecure choices. It develops the concept of behavioural cyber-risk modelling, investigates the role of human–machine asymmetries and critiques static compliance-based regimes in favour of adaptive, context-aware systems. By synthesising empirical research and theoretical developments, the chapter proposes a new agenda for cybersecurity rooted in the nuanced realities of human behaviour, data-driven learning and interdisciplinary engagement.
Information
- Type
- Chapter
- Information
- The Cambridge Handbook of Behavioural Data Science , pp. 756 - 769Publisher: Cambridge University PressPrint publication year: 2026
References
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