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Xie He, Arash Habibi Lashkari, Nikhill Vombatkere and Dilli Prasad Sharma
Over the past few decades, researchers have put their effort and paid significant attention to the authorship attribution field, as it plays an important role in software forensics analysis, plagiarism detection, security attack detection, and protection...
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Bahaa Yamany, Mahmoud Said Elsayed, Anca D. Jurcut, Nashwa Abdelbaki and Marianne A. Azer
Ransomware is a type of malicious software that encrypts a victim?s files and demands payment in exchange for the decryption key. It is a rapidly growing and evolving threat that has caused significant damage and disruption to individuals and organizatio...
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Marko Jevtic, Sa?a Mladenovic and Andrina Granic
Due to the everchanging and evergrowing nature of programming technologies, the gap between the programming industry?s needs and the educational capabilities of both formal and informal educational environments has never been wider. However, the need to ...
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Valeria Mercuri, Martina Saletta and Claudio Ferretti
As the prevalence and sophistication of cyber threats continue to increase, the development of robust vulnerability detection techniques becomes paramount in ensuring the security of computer systems. Neural models have demonstrated significant potential...
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Martina Saletta and Claudio Ferretti
Deep neural networks have proven to be able to learn rich internal representations, including for features that can also be used for different purposes than those the networks are originally developed for. In this paper, we are interested in exploring su...
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Zoltán Szabó and Vilmos Bilicki
Due to the proliferation of large language models (LLMs) and their widespread use in applications such as ChatGPT, there has been a significant increase in interest in AI over the past year. Multiple researchers have raised the question: how will AI be a...
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Elena Fedorchenko, Evgenia Novikova, Andrey Fedorchenko and Sergei Verevkin
Currently, enhancing the efficiency of vulnerability detection and assessment remains relevant. We investigate a new approach for the detection of vulnerabilities that can be used in cyber attacks and assess their severity for further effective responses...
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Artyom V. Gorchakov, Liliya A. Demidova and Peter N. Sovietov
In this paper we consider the research and development of classifiers that are trained to predict the task solved by source code. Possible applications of such task detection algorithms include method name prediction, hardware?software partitioning, prog...
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Francesco Barchi, Emanuele Parisi, Andrea Bartolini and Andrea Acquaviva
To cope with the increasing complexity of digital systems programming, deep learning techniques have recently been proposed to enhance software deployment by analysing source code for different purposes, ranging from performance and energy improvement to...
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Claudio Ferretti and Martina Saletta
State-of-the-art neural networks build an internal model of the training data, tailored to a given classification task. The study of such a model is of interest, and therefore, research on explainable artificial intelligence (XAI) aims at investigating i...
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