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All Outputs (4)

Privacy based triage of suspicious activity reports using offline large language models (2024)
Book Chapter
Legg, P., Ryder, N., Bourton, S., Johnson, D., & Walker, R. (in press). Privacy based triage of suspicious activity reports using offline large language models. In Advancements in Cyber Crime Investigations and Modern Data Analytics. CRC Press / Taylor and Francis

Suspicious Activity Reports (SAR) form a vital part of incident response and case management for the investigation of known or suspected money laundering. However, those submitting SARs, and those tasked with analysing SARs, often find the task overw... Read More about Privacy based triage of suspicious activity reports using offline large language models.

Federated learning: Data privacy and cyber security in edge-based machine learning (2023)
Book Chapter
White, J., & Legg, P. (2023). Federated learning: Data privacy and cyber security in edge-based machine learning. In C. Hewage, Y. Rahulamathavan, & D. Ratnayake (Eds.), Data Protection in a Post-Pandemic Society (DPPPS) – Best Practices, Laws, Regulations, and Recent Solutions. Springer. https://doi.org/10.1007/978-3-031-34006-2

Machine learning is now a key component of many applications for understanding trends and characteristics within the wealth of data that may be processed, whether this be learning about customer preferences and travel preferences, forecasting future... Read More about Federated learning: Data privacy and cyber security in edge-based machine learning.

Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models (2017)
Book Chapter
Smith, E. M., Smith, J., Legg, P., & Francis, S. (2017). Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models. In F. Chao, S. Schockaert, & Q. Zhang (Eds.), Advances in Computational Intelligence Systems: UKCI 2017 (191-202). Springer Cham

The ability to predict future states is fundamental for a wide variety of applications, from weather forecasting to stock market analysis. Understanding the related data attributes that can influence changes in time series is a challenging task that... Read More about Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models.

Human-machine decision support systems for insider threat detection
Book Chapter
Legg, P. Human-machine decision support systems for insider threat detection. In Y. Huang, I. Palomares, & H. Kalutarage (Eds.), Data Analytics and Decision Support for Cybersecurity: Trends, Methodologies and Applications. Springer

Insider threats are recognised to be quite possibly the most damaging attacks that an organisation could experience. Those on the inside, who have privileged access and knowledge, are already in a position of great responsibility for contributing tow... Read More about Human-machine decision support systems for insider threat detection.