Multi-scale anomaly detection on attributed networks by Gutiérrez-Gómez, L, Bovet, A, Delvenne, J-C

A state machine system for insider threat detection by Zhang, H, Agrafiotis, I, Erola, A, Creese, S, Goldsmith, M

“…Research has focused on providing rule-based detection systems or anomaly detection tools which use features indicative of malicious insider activity. …”

Intrusion detection for airborne communication using PHY-layer information by Strohmeier, M, Lenders, V, Martinovic, I

“…Using hypothesis testing and anomaly detection schemes, we develop an intrusion detection system (IDS) that can accurately detect attackers within 40 s.…”

Intrusion detection for airborne communication using PHY-layer information by Strohmeier, M, Lenders, V, Martinovic, I

“…Using hypothesis testing and anomaly detection schemes, we develop an intrusion detection system (IDS) that can accurately detect attackers within 40 s.…”

BRUNO: A deep recurrent model for exchangeable data by Korshunova, I, Degrave, J, Huszár, F, Gal, Y, Gretton, A, Dambre, J

“…The advantages of our architecture are demonstrated on learning tasks that require generalisation from short observed sequences while modelling sequence variability, such as conditional image generation, few-shot learning, and anomaly detection.…”

A Tripwire Grammar for Insider Threat Detection by Agrafiotis, I, Erola, A, Goldsmith, M, Creese, S

“…We then orchestrate these tripwires in conjunction with an anomaly detection system and present an approach to formalising tripwires of both categories. …”

Learning retrospective knowledge with reverse reinforcement learning by Zhang, S, Veeriah, V, Whiteson, S

“…We demonstrate empirically the utility of Reverse GVFs in both representation learning and anomaly detection.…”

The future of event-level information repositories, indexing, and selection in ATLAS by Barberis, D, Cranshaw, J, Dimitrov, G, Doherty, T, Gallas, E, Hrivnac, J, Malon, D, Nairz, A, Nowak, M, Quilty, D, Sorokoletov, R, Gemmeren, P, Zhang, Q

“…This unique resource has been employed for a range of purposes, from monitoring, statistics, anomaly detection, and integrity checking, to event picking, subset selection, and sample extraction. …”

Interpretable stability bounds for spectral graph filters by Kenlay, H, Thanou, D, Dong, X

“…As a ubiquitous tool to process graph-structured data, spectral graph filters have been used to solve common tasks such as denoising and anomaly detection, as well as design deep learning architectures such as graph neural networks. …”

Reflecting on the use of sonification for network monitoring by Axon, L, Creese, S, Goldsmith, M, Nurse, J

“…In Security Operations Centres (SOCs), computer networks are generally monitored using a combination of anomaly detection techniques, Intrusion Detection Systems (IDS) and data presented in visual and text-based forms. …”

On detecting deception in space situational awareness by Pavur, J, Martinovic, I

“…We further develop and evaluate a machine-learning based anomaly detection tool which allows defenders to detect 90-98% of deception attempts with little to no in-house astrometry hardware. …”

Leveraging the urban soundscape: Auditory perception for smart vehicles by Marchegiani, L, Posner, H

“…We first model the urban soundscape and use anomaly detection to identify the presence of an anomalous sound, and later determine the nature of this sound. …”

On identifying anomalies in Tor usage with applications in detecting internet censorship by Wright, J, Darer, A, Farnan, O

“…We demonstrate the our approach in comparison to existing anomaly detection tools, and against both known historical internet censorship events and synthetic datasets. …”