Evolutionary based Generative Adversarial Learning Approach to Metamorphic Malware Detection
  Malicious attacks account for a significant portion of attacks to information assets and computer networks in organisations today. More specifically, dangerous groups of malware that transform their code structures between generations such as metamorphic malware, provide a greater attack surface for the perpetuation of cyber crimes. The detection of these malware family thus poses a challenge. Recent research show that Machine Learning (ML) techniques outperform traditional methods in detecting these dangerous malware groups. Hence, this research will involve the use of Evolutionary based Adversarial ML in defeating metamorphic malware.

  • Start Date:

    1 June 2022

  • End Date:

    31 August 2022

  • Activity Type:

    Externally Funded Research

  • Funder:

    The Scottish Informatics & Computer Science Alliance

  • Value:


Project Team