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With the increase in the adoption of Internet of Things (IoT) devices, the security threat they face has become more pervasive. Recent …

This paper explores security vulnerabilities that target RF communications on popular commercial IoT devices such as Wi-Fi, Zigbee, and …

Traditionally, cyber risk assessment considers system-level risk separately from individual component-level risk, i.e., devices, data, …

In this paper, we present a Data Science approach, which involves using machine learning algorithms and statistical models to analyse …

The availability of log data recorded by computer-based systems such as operating system and network logs, makes it possible for the …

This study proposes DroLoVe, a severity-oriented multiclass anomaly detection approach for drone flight log data.

Topic modelling is a text mining technique for identifying salient themes from a number of documents. The output is commonly a set of …

While new technologies are expected to revolutionise and become game-changers in improving the efficiencies and practises of our daily …

This paper provides a comparative investigation into how methods used in hierarchical classification problems in other domains, which …

Machine learning based Intrusion Detection Systems (IDS) allow flexible and efficient automated detection of cyberattacks in Internet …