Outputs (47)

"Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems (2021)
Presentation / Conference Contribution

In March 2020, the COVID-19 pandemic led to a dramatic shift in educational practice, whereby home-schooling and remote working became the norm. Many typical schools outreach projects to encourage uptake of learning cyber security skills therefore we... Read More about "Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems.

Investigating anti-evasion malware triggers using automated sandbox reconfiguration techniques (2020)
Journal Article

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.

"What did you say?": Extracting unintentional secrets from predictive text learning systems (2020)
Presentation / Conference Contribution

As a primary form of communication, text is used widely in applications including e-mail conversations, mobile text messaging, chatrooms, and forum discussions. Modern systems include facilities such as predictive text, recently implemented using dee... Read More about "What did you say?": Extracting unintentional secrets from predictive text learning systems.

The visual design of network data to enhance cyber security awareness of the everyday internet user (2020)
Presentation / Conference Contribution

Technology and the use of online services are very prevalent across much of our everyday lives. As our digital interactions continue to grow, there is a need to improve public awareness of the risks to our personal online privacy and security. Design... Read More about The visual design of network data to enhance cyber security awareness of the everyday internet user.

Shouting through letterboxes: A study on attack susceptibility of voice assistants (2020)
Presentation / Conference Contribution

Voice assistants such as Amazon Echo and Google Home have become increasingly popular for many home users, for home automation, entertainment, and convenience. These devices process speech commands from a user to execute some action, such as playing... Read More about Shouting through letterboxes: A study on attack susceptibility of voice assistants.

Tools and techniques for improving cyber situational awareness of targeted phishing attacks (2019)
Presentation / Conference Contribution

© 2019 IEEE. Phishing attacks continue to be one of the most common attack vectors used online today to deceive users, such that attackers can obtain unauthorised access or steal sensitive information. Phishing campaigns often vary in their level of... Read More about Tools and techniques for improving cyber situational awareness of targeted phishing attacks.

What makes for effective visualisation in cyber situational awareness for non-expert users? (2019)
Presentation / Conference Contribution

© 2019 IEEE. As cyber threats continue to become more prevalent, there is a need to consider how best we can understand the cyber landscape when acting online, especially so for non-expert users. Satellite navigation systems provide the de facto stan... Read More about What makes for effective visualisation in cyber situational awareness for non-expert users?.

Efficient and interpretable real-time malware detection using random-forest (2019)
Presentation / Conference Contribution

© 2019 IEEE. Malicious software, often described as malware, is one of the greatest threats to modern computer systems, and attackers continue to develop more sophisticated methods to access and compromise data and resources. Machine learning methods... Read More about Efficient and interpretable real-time malware detection using random-forest.

Visual analytics for collaborative human-machine confidence in human-centric active learning tasks (2019)
Journal Article

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

© 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.