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Full-Text Articles in Computer Engineering
Robustness Of Image-Based Malware Classification Models Trained With Generative Adversarial Networks, Ciaran Reilly, Stephen O Shaughnessy, Christina Thorpe
Robustness Of Image-Based Malware Classification Models Trained With Generative Adversarial Networks, Ciaran Reilly, Stephen O Shaughnessy, Christina Thorpe
Conference papers
As malware continues to evolve, deep learning models are increasingly used for malware detection and classification, including image based classification. However, adversarial attacks can be used to perturb images so as to evade detection by these models. This study investigates the effectiveness of training deep learning models with Generative Adversarial Network-generated data to improve their robustness against such attacks. Two image conversion methods, byte plot and space-filling curves, were used to represent the malware samples, and a ResNet-50 architecture was used to train models on the image datasets. The models were then tested against a projected gradient descent attack. It …
Cybercrime: An Investigation Of The Attitudes And Environmental Factors That Make People More Willing To Participate In Online Crime, Dearbhail Kirwan
Cybercrime: An Investigation Of The Attitudes And Environmental Factors That Make People More Willing To Participate In Online Crime, Dearbhail Kirwan
Dissertations
Cybercrime incidence rates are increasing. In order to identify solutions to this problem, the sources of cybercrime need to be identified. This research attempted to identify a potential set of circumstances that create an environment in which people are more likely to engage in cybercrime. There are three aspects to this; (1) Behaviour on the internet – Are people more likely to engage in illicit activities online than in the physical world? (2) Crime Perceptions – Do people perceive cybercrime as being less serious than non-cybercrime? (3) Resources on the Internet – Are people aware of the types of free …