Search Results for author: Martin Higgins

Found 7 papers, 1 papers with code

Incentive-weighted Anomaly Detection for False Data Injection Attacks Against Smart Meter Load Profiles

no code implementations25 Jan 2023 Martin Higgins, Bruce Stephen, David Wallom

To reduce false positives, we model incentive-based detection, which includes knowledge of spot prices, into the anomaly tracking, enabling the methodology to account for changes in the load profile which are unlikely to be attacks.

Anomaly Detection Clustering

Spatial-Temporal Anomaly Detection for Sensor Attacks in Autonomous Vehicles

no code implementations15 Dec 2022 Martin Higgins, Devki Jha, David Wallom

Time-of-flight (ToF) distance measurement devices such as ultrasonics, LiDAR and radar are widely used in autonomous vehicles for environmental perception, navigation and assisted braking control.

Anomaly Detection Autonomous Vehicles +1

Blending Data and Physics Against False Data Injection Attack: An Event-Triggered Moving Target Defence Approach

1 code implementation27 Apr 2022 Wangkun Xu, Martin Higgins, Jianhong Wang, Imad M. Jaimoukha, Fei Teng

However, the uncontrollable false positive rate of the data-driven detector and the extra cost of frequent MTD usage limit their wide applications.

Cyber-Physical Risk Assessment for False Data Injection Attacks Considering Moving Target Defences

no code implementations22 Feb 2022 Martin Higgins, Wangkun Xu, Fei Teng, Thomas Parisini

In this paper, we examine the factors that influence the success of false data injection (FDI) attacks in the context of both cyber and physical styles of reinforcement.

Locational Marginal Pricing: Towards a Free Market in Power

no code implementations5 Mar 2021 Martin Higgins

Nothing has done more to empower the free market, enterprise, and meritocracy than the spread of electricity and power to everyone.

Topology Learning Aided False Data Injection Attack without Prior Topology Information

no code implementations24 Feb 2021 Martin Higgins, Jiawei Zhang, Ning Zhang, Fei Teng

False Data Injection (FDI) attacks against powersystem state estimation are a growing concern for operators. Previously, most works on FDI attacks have been performedunder the assumption of the attacker having full knowledge ofthe underlying system without clear justification.

Enhanced Cyber-Physical Security Using Attack-resistant Cyber Nodes and Event-triggered Moving Target Defence

no code implementations27 Oct 2020 Martin Higgins, Keith Mayes, Fei Teng

In this context, a distributed event-triggered MTD protocol is implemented at the physical layer to complement cyber side enhancement.

Anomaly Detection

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