Journal of Data Analytics and Engineering Decision Making(JDAEDM)

Department of Electrical and Computer Engineering, American University of Beirut, Lebanon

Publications

• Review Article   
  Exploring the Landscape for Generative Sequence Models for Specialized Data Synthesis
  Author(s): Mohammad Zbeeb*, Mohammad Ghorayeb and Mariam Salman
  
  Artificial Intelligence (AI) research often aims to develop models that can generalize reliably across complex datasets, yet this remains challenging in fields where data is scarce, intricate, or inaccessible. This paper introduces a novel approach that leverages three generative models of varying complexity to synthesize one of the most demanding structured datasets: Malicious Network Traffic. Our approach uniquely transforms numerical data into text, re-framing data generation as a language-modeling task, which not only enhances data regularization but also significantly improves generalization and the quality of the synthetic data. Extensive statistical analyses demonstrate that our method surpasses state-of-the-art generative models in producing high-fidelity synthetic data. Additionally, we conduct a comprehensive study on synthetic data applications, effectiveness, and evaluatio.. Read More»
  

  Abstract PDF