Jason R. C. Nurse
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Recognitions
Jason R. C. Nurse has a total of 172 co-authors. Here are the top co-authors by number of shared publications:
Sadie Creese
32 shared publicationsMichael Goldsmith
Department of Computer Science, University of Oxford, UK
27 shared publicationsIoannis Agrafiotis
Department of Computer Science, University of Oxford, Oxford, UK
14 shared publicationsKoen Lamberts
Department of Psychology, University of York, York, UK
8 shared publications- Maria Bada
Queen Mary University of London
8 shared publications Arnau Erola
Department of Computer Science, University of Oxford, Oxford, UK
6 shared publications
Latest Publications
- 26 September 2026
- Published by Springer Nature
- p. 1-9
Insider Threat
- 21 August 2026
- Published by Springer Nature
- p. 1-5
Online Extremism
- 18 August 2026
- Published by Springer Nature
- p. 479-496
Analysing the Cyber Security Support Journeys of Small and Medium Sized Organisations
- 18 August 2026
- Published by Springer Nature
- p. 479-496
Analysing the Cyber Security Support Journeys of Small and Medium Sized Organisations
- 5 August 2026
- Published by Elsevier in Computers & Security
- Vol. 171
What makes people susceptible to phishing attacks: A systematic literature review and future research agenda
- 5 August 2026
- Published by Elsevier in Computers & Security
- Vol. 171
What makes people susceptible to phishing attacks: A systematic literature review and future research agenda
- 4 August 2026
- Published by Springer Nature
- p. 1-5
Generative Artificial Intelligence (AI) Misuse
- 4 August 2026
- Published by Springer Nature
- p. 1-5
Cyber Insurance
- 22 July 2026
- Published by Springer Nature
- p. 1-5
Misinformation
- Open Access
- 7 July 2026
- Published by Springer Nature
- p. 492-512
Toward a Behavioral Ontology for Cybersecurity: Introducing SebDB
Cyberattacks that target individuals remain a significant threat to an organization’s security, placing human behavior at the center of effective defense. This paper focuses on this topic and makes two novel contributions to the field. First, we introduce the Security Behaviors Database (SebDB), an open-source resource that documents security behaviors, links them to organizational risks, and maps them to established security standards. SebDB currently includes more than 100 core behaviors, associated impacts when behaviors are not followed, and alignments with widely used frameworks, including the NIST Cybersecurity Framework (CSF) and MITRE ATT&CK. Developed by a consortium of practitioners and researchers, SebDB is intended to improve the understanding, modeling, and measurement of human cyber risk and to support behavior-change initiatives that can measurably improve security posture. In this article, we describe the motivation, design, and structure of SebDB, including behaviors and their risk and control mappings. The second novel contribution of this research is the proposal of a behavioral ontology for cybersecurity. This ontology, which realizes the overarching vision for SebDB, presents one of the first comprehensive conceptualizations of knowledge in the behavioral security and human aspects of the cybersecurity domains. Through this ontology, we model how behaviors can be linked to risks, threat actor tactics, vulnerabilities, and security controls, while also covering how behavioral interventions can be leveraged as part of an organization’s security strategy.
- 7 July 2026
- Published by Springer Nature
- p. 492-512
Open AccessToward a Behavioral Ontology for Cybersecurity: Introducing SebDB
Cyberattacks that target individuals remain a significant threat to an organization’s security, placing human behavior at the center of effective defense. This paper focuses on this topic and makes two novel contributions to the field. First, we introduce the Security Behaviors Database (SebDB), an open-source resource that documents security behaviors, links them to organizational risks, and maps them to established security standards. SebDB currently includes more than 100 core behaviors, associated impacts when behaviors are not followed, and alignments with widely used frameworks, including the NIST Cybersecurity Framework (CSF) and MITRE ATT&CK. Developed by a consortium of practitioners and researchers, SebDB is intended to improve the understanding, modeling, and measurement of human cyber risk and to support behavior-change initiatives that can measurably improve security posture. In this article, we describe the motivation, design, and structure of SebDB, including behaviors and their risk and control mappings. The second novel contribution of this research is the proposal of a behavioral ontology for cybersecurity. This ontology, which realizes the overarching vision for SebDB, presents one of the first comprehensive conceptualizations of knowledge in the behavioral security and human aspects of the cybersecurity domains. Through this ontology, we model how behaviors can be linked to risks, threat actor tactics, vulnerabilities, and security controls, while also covering how behavioral interventions can be leveraged as part of an organization’s security strategy.
- 7 June 2026
- Published by Taylor & Francis in The RUSI Journal
- Vol. 171 (4) , 98-101
From Malware to Marketplaces: The Crossover Between Crime and State Cyber Activity
- 7 June 2026
- Published by Taylor & Francis in The RUSI Journal
- Vol. 171 (4) , 98-101
From Malware to Marketplaces: The Crossover Between Crime and State Cyber Activity
- Open Access
- 3 April 2026
- Published by Taylor & Francis in Information Security Journal: A Global Perspective
- p. 1-39
Understanding cyber security practices in SMEs: A mixed-methods Investigation
- 3 April 2026
- Published by Taylor & Francis in Information Security Journal: A Global Perspective
- p. 1-39
Open AccessUnderstanding cyber security practices in SMEs: A mixed-methods Investigation