Emotion Recognition on Social Media Using Natural Language Processing (NLP) Techniques
Conference Proceeding
Gomez, L. R., Watt, T., Babaagba, K. O., Chrysoulas, C., Homay, A., Rangarajan, R., & Liu, X. (2023)
Emotion Recognition on Social Media Using Natural Language Processing (NLP) Techniques. In ICISS '23: Proceedings of the 2023 6th International Conference on Information Science and Systems (113-118). https://doi.org/10.1145/3625156.3625173
In recent years, text has been the main form of communication on social media platforms such as Twitter, Reddit, Facebook, Instagram and YouTube. Emotion Recognition from thes...
A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs
Conference Proceeding
McLaren, R. A., Babaagba, K., & Tan, Z. (in press)
A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs. In The 8th International Conference on machine Learning, Optimization and Data science - LOD 2022
As the field of malware detection continues to grow, a shift in focus is occurring from feature vectors and other common, but easily obfuscated elements to a semantics based a...
A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling
Conference Proceeding
Turnbull, L., Tan, Z., & Babaagba, K. (2022)
A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling. In 2022 IEEE Conference on Dependable and Secure Computing (DSC). https://doi.org/10.1109/DSC54232.2022.9888906
Malicious software trends show a persistent yearly increase in volume and cost impact. More than 350,000 new malicious or unwanted programs that target various technologies we...
Image Forgery Detection using Cryptography and Deep Learning
Conference Proceeding
Oke, A., & Babaagba, K. O. (2024)
Image Forgery Detection using Cryptography and Deep Learning. In Big Data Technologies and Applications. BDTA 2023 (62-78). https://doi.org/10.1007/978-3-031-52265-9_5
The advancement of technology has undoubtedly exposed everyone to a remarkable array of visual imagery. Nowadays, digital technology is eating away the trust and historical co...
An Evolutionary based Generative Adversarial Network Inspired Approach to Defeating Metamorphic Malware
Conference Proceeding
Babaagba, K. O., & Wylie, J. (2023)
An Evolutionary based Generative Adversarial Network Inspired Approach to Defeating Metamorphic Malware. In GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation (1753-1759). https://doi.org/10.1145/3583133.3596362
Defeating dangerous families of malware like polymorphic and metamorphic malware have become well studied due to their increased attacks on computer systems and network. Tradi...
Can Federated Models Be Rectified Through Learning Negative Gradients?
Conference Proceeding
Tahir, A., Tan, Z., & Babaagba, K. O. (2024)
Can Federated Models Be Rectified Through Learning Negative Gradients?. In Big Data Technologies and Applications (18-32). https://doi.org/10.1007/978-3-031-52265-9_2
Federated Learning (FL) is a method to train machine learning (ML) models in a decentralised manner, while preserving the privacy of data from multiple clients. However, FL is...
A Study on the Effect of Feature Selection on Malware Analysis using Machine Learning
Conference Proceeding
Babaagba, K. O., & Adesanya, S. O. (2019)
A Study on the Effect of Feature Selection on Malware Analysis using Machine Learning. In ICEIT 2019: Proceedings of the 2019 8th International Conference on Educational and Information Technology (51–55). https://doi.org/10.1145/3318396.3318448
In this paper, the effect of feature selection in malware detection using machine learning techniques is studied. We employ supervised and unsupervised machine learning algori...