Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning

The burgeoning navigation services using digital maps provide great convenience to drivers. However, there are sometimes anomalies in the lane rendering map images, which might mislead human drivers and result in unsafe driving. To accurately and effectively detect the anomalies, this paper transforms lane rendering image anomaly detection into...

Anomaly Detection and Synthetic Data Generation for Power Systems Using Autoencoder Neural Networks

The scale of the power system has been significantly expanded in recent decades. To gain real-time insights into the power system, an increasing number of sensors have been deployed tomonitor grid states, resulting in a rapidly growing number of measurement points. Simultaneously, there has also been a rise in the penetration of renewable energy...

Attack Graph Model for Cyber-Physical Power Systems Using Hybrid Deep Learning

Electrical power grids are vulnerable to cyber attacks, as seen in Ukraine in 2015 and 2016. However, existing attack detection methods are limited. Most of them are based on power system measurement anomalies that occur when an attack is successfully executed at the later stages of the cyber kill chain. In contrast, the attacks on the Ukrainian...

Cyber Forensic Analysis for Operational Technology Using Graph-Based Deep Learning

The cyber attacks in Ukraine in 2015 and 2016 demonstrated the vulnerability of electrical power grids to cyber threats. They highlighted the significance of Operational Technology (OT) communication-based anomaly detection. Many anomaly detection methods are based on real-time traffic monitoring, i.e., Intrusion Detection Systems (IDS) that may...

Learning State Machines to Monitor and Detect Anomalies on a Kubernetes Cluster

These days more companies are shifting towards using cloud environments to provide their services to their client. While it is easy to set up a cloud environment, it is equally important to monitor the system's runtime behaviour and identify anomalous behaviours that occur during its operation. In recent years, the utilisation of Recurrent...

From Condition Monitoring to Maintenance Management in Electric Power System Generation with focus on Wind Turbines: Sustainable concrete infrastructure design

With increase in the number of sensors installed on sub-assemblies of industrial components, the amount of data collected is rapidly increasing. These data hold information in the areas of operation of the system and evolution of health condition of the components. Therefore, extracting the knowledge from the data can bring about significant...

DECANTeR: DEteCtion of Anomalous outbouNd HTTP Traffic by Passive Application Fingerprinting

We present DECANTeR, a system to detect anomalous outbound HTTP communication, which passively extracts fingerprints for each application running on a monitored host. The goal of our system is to detect unknown malware and backdoor communication indicated by unknown fingerprints extracted from a host's network traffic. We evaluate a prototype...