Pete Burnap

9.1k total citations · 7 hit papers
156 papers, 5.6k citations indexed

About

Pete Burnap is a scholar working on Computer Networks and Communications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Pete Burnap has authored 156 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Computer Networks and Communications, 62 papers in Information Systems and 53 papers in Artificial Intelligence. Recurrent topics in Pete Burnap's work include Network Security and Intrusion Detection (46 papers), Information and Cyber Security (29 papers) and Advanced Malware Detection Techniques (27 papers). Pete Burnap is often cited by papers focused on Network Security and Intrusion Detection (46 papers), Information and Cyber Security (29 papers) and Advanced Malware Detection Techniques (27 papers). Pete Burnap collaborates with scholars based in United Kingdom, United States and Spain. Pete Burnap's co-authors include Matthew Williams, Luke Sloan, Omer Rana, Kevin Jones, Eirini Anthi, Jeffrey Morgan, Lowri Williams, George Theodorakopoulos, Adam Edwards and William Housley and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Accounting and Economics.

In The Last Decade

Pete Burnap

148 papers receiving 5.3k citations

Hit Papers

A review of cyber security risk assessment methods for SC... 2015 2026 2018 2022 2015 2019 2015 2015 2017 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pete Burnap United Kingdom 39 2.3k 1.6k 1.6k 1.3k 1.1k 156 5.6k
Bernard J. Jansen United States 56 3.7k 1.6× 5.9k 3.6× 728 0.5× 3.7k 2.8× 854 0.8× 432 14.1k
Haining Wang United States 43 2.5k 1.1× 2.4k 1.5× 2.8k 1.8× 977 0.7× 2.0k 1.8× 238 6.1k
Nigel Shadbolt United Kingdom 37 2.6k 1.1× 1.9k 1.1× 839 0.5× 989 0.7× 239 0.2× 270 5.6k
Ed H. United States 49 3.3k 1.4× 3.8k 2.3× 684 0.4× 1.8k 1.4× 508 0.5× 174 9.8k
Yan Chen China 35 1.1k 0.5× 1.8k 1.1× 904 0.6× 1.3k 1.0× 423 0.4× 174 4.7k
Jason Hong United States 55 3.2k 1.4× 5.6k 3.4× 2.1k 1.3× 4.0k 3.0× 2.9k 2.7× 248 12.8k
Tim Finin United States 57 8.3k 3.5× 6.0k 3.6× 4.6k 2.9× 2.1k 1.6× 1.1k 1.0× 405 15.0k
Norman Sadeh United States 48 2.8k 1.2× 2.5k 1.5× 1.3k 0.8× 3.7k 2.8× 1.3k 1.2× 201 8.5k
John G. Breslin Ireland 35 1.3k 0.6× 1.2k 0.7× 765 0.5× 506 0.4× 186 0.2× 238 4.9k
Arvind Narayanan United States 33 4.1k 1.8× 2.9k 1.8× 835 0.5× 2.3k 1.7× 831 0.8× 80 7.9k

Countries citing papers authored by Pete Burnap

Since Specialization
Citations

This map shows the geographic impact of Pete Burnap's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pete Burnap with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pete Burnap more than expected).

Fields of papers citing papers by Pete Burnap

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pete Burnap. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pete Burnap. The network helps show where Pete Burnap may publish in the future.

Co-authorship network of co-authors of Pete Burnap

This figure shows the co-authorship network connecting the top 25 collaborators of Pete Burnap. A scholar is included among the top collaborators of Pete Burnap based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pete Burnap. Pete Burnap is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Anthi, Eirini, et al.. (2025). Collaborative intrusion detection in resource-constrained IoT environments: Challenges, methods, and future directions a review. Journal of Information Security and Applications. 93. 104127–104127.
2.
Heartfield, Ryan, et al.. (2025). Real-Time Anomaly Detection for Industrial Robotic Arms Using Edge Computing. IEEE Internet of Things Journal. 12(15). 29696–29712. 1 indexed citations
3.
Burnap, Pete, et al.. (2025). Towards the Deployment of Realistic Autonomous Cyber Network Defence: A Systematic Review. ACM Computing Surveys. 58(1). 1–36. 1 indexed citations
4.
Williams, Lowri & Pete Burnap. (2025). The Emotional Landscape of Technological Innovation: A Data-Driven Case Study of ChatGPT’s Launch. Informatics. 12(3). 58–58. 1 indexed citations
5.
Williams, Lowri, et al.. (2025). The Evolution of Digital Security by Design Using Temporal Network Analysis. Informatics. 12(1). 8–8. 1 indexed citations
6.
Anthi, Eirini, et al.. (2025). STADe: An unsupervised time-windows method of detecting anomalies in oil and gas Industrial Cyber-Physical Systems (ICPS) networks. International Journal of Critical Infrastructure Protection. 49. 100762–100762.
7.
Burnap, Pete, et al.. (2024). Mapping Automated Cyber Attack Intelligence to Context-Based Impact on System-Level Goals. SHILAP Revista de lepidopterología. 4(2). 340–356.
8.
Heartfield, Ryan, et al.. (2024). CASPER: Context-Aware IoT Anomaly Detection System for Industrial Robotic Arms. ORCA Online Research @Cardiff (Cardiff University). 5(3). 1–36. 5 indexed citations
9.
Williams, Lowri, Eirini Anthi, & Pete Burnap. (2024). Comparing Hierarchical Approaches to Enhance Supervised Emotive Text Classification. Big Data and Cognitive Computing. 8(4). 38–38. 4 indexed citations
10.
Williams, Lowri, et al.. (2024). Topic Modelling: Going beyond Token Outputs. Big Data and Cognitive Computing. 8(5). 44–44. 5 indexed citations
11.
Williams, Lowri, Eirini Anthi, & Pete Burnap. (2024). Uncovering Key Factors That Drive the Impressions of Online Emerging Technology Narratives. Information. 15(11). 706–706.
12.
Saxena, Neetesh, et al.. (2023). Extended Dependency Modeling Technique for Cyber Risk Identification in ICS. IEEE Access. 11. 37229–37242. 3 indexed citations
13.
Saxena, Neetesh, et al.. (2023). Understanding Indicators of Compromise against Cyber-attacks in Industrial Control Systems: A Security Perspective. ACM Transactions on Cyber-Physical Systems. 7(2). 1–33. 30 indexed citations
14.
Giommoni, Luca, et al.. (2023). Digital fingerprinting for identifying malicious collusive groups on Twitter. ORCA Online Research @Cardiff (Cardiff University). 9(1). 2 indexed citations
15.
Reinecke, Philipp, et al.. (2022). Cybersecurity Challenges in the Offshore Oil and Gas Industry: An Industrial Cyber-Physical Systems (ICPS) Perspective. ACM Transactions on Cyber-Physical Systems. 6(3). 1–27. 22 indexed citations
16.
Saxena, Neetesh, et al.. (2022). Smart Grid Cyber-Physical Situational Awareness of Complex Operational Technology Attacks: A Review. ACM Computing Surveys. 55(10). 1–36. 92 indexed citations
17.
Burnap, Pete, et al.. (2021). Real-Time Malware Process Detection and Automated Process Killing. Security and Communication Networks. 2021. 1–23. 6 indexed citations
18.
Saxena, Neetesh, et al.. (2020). PharmaCrypt: Blockchain for Critical Pharmaceutical Industry to Counterfeit Drugs. Computer. 53(7). 29–44. 45 indexed citations
19.
Radanliev, Petar, David De Roure, Kevin Page, et al.. (2020). Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics.. arXiv (Cornell University). 1 indexed citations
20.
Burnap, Pete, et al.. (2017). Malware classification using self organising feature maps and machine activity data. Computers & Security. 73. 399–410. 99 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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