• Hybrid Machine Learning for Network Anomaly Intrusion Detection 

      Chkirbene, Zina; Eltanbouly, Sohaila; Bashendy, May; Alnaimi, Noora; Erbad, Aiman ( IEEE , 2020 , Conference Paper)
      In this paper, a hybrid approach of combing two machine learning algorithms is proposed to detect the different possible attacks by performing effective feature selection and classification. This system uses Random Forest ...
    • LIME: Long-Term Forecasting Model for Desalination Membrane Fouling to Estimate the Remaining Useful Life of Membrane 

      Eltanbouly, Sohaila; Erradi, Abdelkarim; Tantawy, Ashraf; Ben Said, Ahmed; Shaban, Khaled; ... more authors ( Springer Science and Business Media Deutschland GmbH , 2023 , Conference Paper)
      Membrane fouling is one of the major problems in desalination processes as it can cause a severe drop in the quality and quantity of the permeate water. This paper presents a data-driven approach for long-term forecasting ...
    • Machine Learning Techniques for Network Anomaly Detection: A Survey 

      Eltanbouly, Sohaila; Bashendy, May; Alnaimi, Noora; Chkirbene, Zina; Erbad, Aiman ( IEEE , 2020 , Conference Paper)
      Nowadays, distributed data processing in cloud computing has gained increasing attention from many researchers. The intense transfer of data has made the network an attractive and vulnerable target for attackers to exploit ...
    • Multimodal Intrusion Detection System for Cyber Physical Systems 

      Eltanbouly, Sohaila Salah (2021 , Master Thesis)
      Cyber-Physical Systems (CPS) are deployed to control critical infrastructure in many fields, including industry and manufacturing. In recent years, CPS have been affected by cyberattacks due to the increased connectivity ...