Rana

Rana Abou Khamis

I’m a Ph.D. student at Carleton University and work in the government of Canada as Technical Advisor. I completed a bachelor’s degree in Informatics Engineering with a specialization in Computer Systems and Network Engineering from Damascus University. Later, I earned from the University of Liverpool a graduate diploma in Information System Management.

In 2020, I completed my master’s degree in Information Technology from Carleton University. My master’s thesis work was centered around securing machine learning models against adversarial samples in a network application. I published two papers and was nominated for the Senate Award for Outstanding Academic Achievement in my graduate study at Carleton University.

I have over 10 years of experience in Network administration and Support and a strong background in Computer Applications and Operating Systems. Also, I have an extensive experience in Programming and Web development. Currently, I’m a Technical Advisor in Innovation Research and Development Lab in Shared Services Canada. I won a Bravo Award from Service Canada for my great innovation and commitment and designed an Inventory Tool for Service Canada, presented to the Assistant Deputy Minister of Employment and Social Development Canada (ESDC).

Publications

Abou Khamis, R., Shafiq, M. O., & Matrawy, A. (2020, June). Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization. In ICC 2020-2020 IEEE International Conference on Communications (ICC) (pp. 1-7). IEEE.

Abou Khamis, R., & Matrawy, A. (2020, October). Evaluation of adversarial training on different types of neural networks in deep learning-based idss. In 2020 international symposium on networks, computers and communications (ISNCC) (pp. 1-6). IEEE.

Ibitoye, O., Abou-Khamis, R., Matrawy, A., & Shafiq, M. O. (2019). The Threat of Adversarial Attacks on Machine Learning in Network Security--A Survey. arXiv preprint arXiv:1911.02621.

Abou Khamis, R. (2020). Evaluating adversarial learning on different types of deep learning-based intrusion detection systems using min-max optimization (Doctoral dissertation, Carleton University).

Research Interest

  • Cybersecurity

  • Machine learning

  • Usability, and human-centric privacy and security