Research report presented at the 4th IEEE International Conference on AI in Cybersecurity
21/11/2024
The research report “MAGICIAN: Malware classification Approach through Generation Image using Conditional and wassersteIn generative Adversarial Network variants”, created by colleagues Andrea Iannacone and Alessandro Stamerra with the collaboration of the University of Bari within the research activities provided for in the Program Contract “Suite cybersecurity products and SOC“, was accepted for presentation at “4th IEEE International Conference on AI in Cybersecurity (ICAIC)”.
The conference will be held from 5 to 7 February 2025 at the University of Houston, Texas and will be published later on IEEE Xplore.
Speed and efficiency
The research proposes an innovative approach to malware detection and classification, based on recognition of synthetic images derived from binary code. This using Conditional Generative Adversarial Networks (cGAN), Wasserstein Generative Adversarial Networks (WGAN) and appropriate scaling and sampling strategies, to improve the accuracy of recognition by ensuring speed and efficiency of the classification algorithm.
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