Skip to main content

Research Repository

Advanced Search

All Outputs (24)

Longitudinal risk-based security assessment of docker software container images (2023)
Journal Article
Mills, A., White, J., & Legg, P. (2023). Longitudinal risk-based security assessment of docker software container images. Computers and Security, 135, Article 103478. https://doi.org/10.1016/j.cose.2023.103478

As the use of software containerisation has increased, so too has the need for security research on their usage, with various surveys and studies conducted to assess the overall security posture of software container images. To date, there has been v... Read More about Longitudinal risk-based security assessment of docker software container images.

Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range (2023)
Journal Article
Legg, P., Mills, A., & Johnson, I. (2023). Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range. Journal of The Colloquium for Information Systems Security Education, 10(1), 9. https://doi.org/10.53735/cisse.v10i1.172

Computer Science as a subject is now appearing in more school curricula for GCSE and A level, with a growing demand for cyber security to be embedded within this teaching. Yet, teachers face challenges with limited time and resource for preparing pra... Read More about Teaching offensive and defensive cyber security in schools using a Raspberry Pi Cyber Range.

Interactive cyber-physical system hacking: Engaging students early using scalextric (2023)
Journal Article
White, J., Legg, P., & Mills, A. (2023). Interactive cyber-physical system hacking: Engaging students early using scalextric. Journal of The Colloquium for Information Systems Security Education, 10(1), 6. https://doi.org/10.53735/cisse.v10i1.163

Cyber Security as an education discipline covers a variety of topics that can be challenging and complex for students who are new to the subject domain. With this in mind, it is crucial that new students are motivated by understanding both the techni... Read More about Interactive cyber-physical system hacking: Engaging students early using scalextric.

Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification (2022)
Journal Article
McCarthy, A., Ghadafi, E., Andriotis, P., & Legg, P. (2023). Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification. Journal of Information Security and Applications, 72, Article 103398. https://doi.org/10.1016/j.jisa.2022.103398

Machine learning is key for automated detection of malicious network activity to ensure that computer networks and organizations are protected against cyber security attacks. Recently, there has been growing interest in the domain of adversarial mach... Read More about Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification.

Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey (2022)
Journal Article
McCarthy, A., Ghadafi, E., Andriotis, P., & Legg, P. (2022). Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey. Journal of Cybersecurity and Privacy, 2(1), 154-190. https://doi.org/10.3390/jcp2010010

Machine learning has become widely adopted as a strategy for dealing with a variety of cybersecurity issues, ranging from insider threat detection to intrusion and malware detection. However, by their very nature, machine learning systems can introdu... Read More about Functionality-preserving adversarial machine learning for robust classification in cybersecurity and intrusion detection domains: A survey.

Investigating malware propagation and behaviour using system and network pixel-based visualisation (2021)
Journal Article
Williams, J., & Legg, P. (2022). Investigating malware propagation and behaviour using system and network pixel-based visualisation. SN Computer Science, 3(1), Article 53. https://doi.org/10.1007/s42979-021-00926-9

Malicious software, known as malware, is a perpetual game of cat and mouse between malicious software developers and security professionals. Recent years have seen many high profile cyber attacks, including the WannaCry and NotPetya ransomware attack... Read More about Investigating malware propagation and behaviour using system and network pixel-based visualisation.

Deep learning-based security behaviour analysis in IoT environments: A survey (2021)
Journal Article
Yue, Y., Li, S., Legg, P., & Li, F. (2021). Deep learning-based security behaviour analysis in IoT environments: A survey. Security and Communication Networks, 2021, 1-13. https://doi.org/10.1155/2021/8873195

Internet of Things (IoT) applications have been used in a wide variety of domains ranging from smart home, healthcare, smart energy, and Industrial 4.0. While IoT brings a number of benefits including convenience and efficiency, it also introduces a... Read More about Deep learning-based security behaviour analysis in IoT environments: A survey.

Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques (2020)
Journal Article
Mills, A., & Legg, P. (2021). Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques. Journal of Cybersecurity and Privacy, 1(1), 19-39. https://doi.org/10.3390/jcp1010003

Malware analysis is fundamental for defending against prevalent cyber security threats and requires a means to deploy and study behavioural software traits as more sophisticated malware is developed. Traditionally, virtual machines are used to provid... Read More about Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques.

Venue2Vec: An efficient embedding model for fine-grained user location prediction in geo-social networks (2019)
Journal Article
Xu, S., Cao, J., Legg, P., Liu, B., & Li, S. (2020). Venue2Vec: An efficient embedding model for fine-grained user location prediction in geo-social networks. IEEE Systems Journal, 14(2), 1740-1751. https://doi.org/10.1109/JSYST.2019.2913080

Geo-Social Networks (GSN) significantly improve location-aware capability of services by offering geo-located content based on the huge volumes of data generated in the GSN. The problem of user location prediction based on user-generated data in GSN... Read More about Venue2Vec: An efficient embedding model for fine-grained user location prediction in geo-social networks.

Visual analytics for collaborative human-machine confidence in human-centric active learning tasks (2019)
Journal Article
Legg, P., Smith, J., & Downing, A. (2019). Visual analytics for collaborative human-machine confidence in human-centric active learning tasks. Human-Centric Computing and Information Sciences, 9, Article 5. https://doi.org/10.1186/s13673-019-0167-8

Active machine learning is a human-centric paradigm that leverages a small labelled dataset to build an initial weak classifier, that can then be improved over time through human-machine collaboration. As new unlabelled samples are observed, the mach... Read More about Visual analytics for collaborative human-machine confidence in human-centric active learning tasks.

Predicting user confidence during visual decision making (2018)
Journal Article
Smith, J., Legg, P., Matovis, M., & Kinsey, K. (2018). Predicting user confidence during visual decision making. ACM Transactions on Interactive Intelligent Systems, 8(2), Article 10. https://doi.org/10.1145/3185524

© 2018 ACM People are not infallible consistent “oracles”: their confidence in decision-making may vary significantly between tasks and over time. We have previously reported the benefits of using an interface and algorithms that explicitly captured... Read More about Predicting user confidence during visual decision making.

Glyph visualization: A fail-safe design scheme based on quasi-hamming distances (2017)
Journal Article
Legg, P. A., Legg, P., Maguire, E., Walton, S., & Chen, M. (2017). Glyph visualization: A fail-safe design scheme based on quasi-hamming distances. IEEE Computer Graphics and Applications, 37(2), 31-41. https://doi.org/10.1109/MCG.2016.66

© 1981-2012 IEEE. In many spatial and temporal visualization applications, glyphs provide an effective means for encoding multivariate data. However, because glyphs are typically small, they are vulnerable to various perceptual errors. This article i... Read More about Glyph visualization: A fail-safe design scheme based on quasi-hamming distances.

Visual analytics for non-expert users in cyber situation awareness (2016)
Journal Article
Legg, P. (2016). Visual analytics for non-expert users in cyber situation awareness. https://doi.org/10.22619/IJCSA

Situation awareness is often described as the perception and comprehension of the current situation, and the projection of future status. Whilst this may be well understood in an organisational cybersecurity context, there is a strong case to be made... Read More about Visual analytics for non-expert users in cyber situation awareness.

Automated insider threat detection system using user and role-based profile assessment (2015)
Journal Article
Legg, P. A., Buckley, O., Goldsmith, M., & Creese, S. (2017). Automated insider threat detection system using user and role-based profile assessment. IEEE Systems Journal, 11(2), 503-512. https://doi.org/10.1109/JSYST.2015.2438442

© 2007-2012 IEEE. Organizations are experiencing an ever-growing concern of how to identify and defend against insider threats. Those who have authorized access to sensitive organizational data are placed in a position of power that could well be abu... Read More about Automated insider threat detection system using user and role-based profile assessment.

Knowledge-assisted ranking: A visual analytic application for sports event data (2015)
Journal Article
Chung, D. H., Parry, M. L., Griffiths, I. W., Laramee, R. S., Bown, R., Legg, P. A., & Chen, M. (2016). Knowledge-assisted ranking: A visual analytic application for sports event data. IEEE Computer Graphics and Applications, 36(3), 72-82. https://doi.org/10.1109/MCG.2015.25

© 2016 IEEE. Organizing sports video data for performance analysis can be challenging, especially in cases involving multiple attributes and when the criteria for sorting frequently changes depending on the user's task. The proposed visual analytic s... Read More about Knowledge-assisted ranking: A visual analytic application for sports event data.

Feature Neighbourhood Mutual Information for multi-modal image registration: An application to eye fundus imaging (2014)
Journal Article
Legg, P. A., Rosin, P. L., Marshall, D., & Morgan, J. E. (2015). Feature Neighbourhood Mutual Information for multi-modal image registration: An application to eye fundus imaging. Pattern Recognition, 48(6), 1937-1946. https://doi.org/10.1016/j.patcog.2014.12.014

© 2014 Elsevier Ltd. All rights reserved. Multi-modal image registration is becoming an increasingly powerful tool for medical diagnosis and treatment. The combination of different image modalities facilitates much greater understanding of the underl... Read More about Feature Neighbourhood Mutual Information for multi-modal image registration: An application to eye fundus imaging.

Visual analytics of e-mail sociolinguistics for user behavioural analysis (2014)
Journal Article
Legg, P., Buckley, O., Goldsmith, M., & Creese, S. (2014). Visual analytics of e-mail sociolinguistics for user behavioural analysis. Journal of Internet Services and Information Security, 4(4), 1-13

The cyber-security threat that most organisations face is not one that only resides outside their perimeter attempting to get in, but emanates from the inside too. Insider threats encompass anyone or thing which exploits authorised access to company... Read More about Visual analytics of e-mail sociolinguistics for user behavioural analysis.

Towards a conceptual model and reasoning structure for insider threat detection (2013)
Journal Article
Legg, P., Moffat, N., Nurse, J., Happa, J., Agrafiotis, I., Goldsmith, M., & Creese, S. (2013). Towards a conceptual model and reasoning structure for insider threat detection

The insider threat faced by corporations and governments today is a real and significant problem, and one that has become increasingly difficult to combat as the years have progressed. From a technology standpoint, traditional protective measures suc... Read More about Towards a conceptual model and reasoning structure for insider threat detection.

Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop (2013)
Journal Article
Griffiths, I. W., Jones, M. W., Parry, M. L., Legg, P. A., Chung, D. H., Legg, P., …Chen, M. (2013). Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2109-2118. https://doi.org/10.1109/TVCG.2013.207

Traditional sketch-based image or video search systems rely on machine learning concepts as their core technology. However, in many applications, machine learning alone is impractical since videos may not be semantically annotated sufficiently, there... Read More about Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop.

Improving accuracy and efficiency of mutual information for multi-modal retinal image registration using adaptive probability density estimation (2013)
Journal Article
Morgan, J. E., Marshall, D., Rosin, P. L., Legg, P. A., Legg, P., & Rosin, P. (2013). Improving accuracy and efficiency of mutual information for multi-modal retinal image registration using adaptive probability density estimation. Computerized Medical Imaging and Graphics, 37(7-8), 597-606. https://doi.org/10.1016/j.compmedimag.2013.08.004

Mutual information (MI) is a popular similarity measure for performing image registration between different modalities. MI makes a statistical comparison between two images by computing the entropy from the probability distribution of the data. There... Read More about Improving accuracy and efficiency of mutual information for multi-modal retinal image registration using adaptive probability density estimation.