Under the supervision of Dr. Ahmad Hasasneh, two students in the Master's in Information Security program, Marah Hawa and Tahani Kmail, have published two qualitative research papers in peer-reviewed and prestigious journals indexed in the Scopus database. These papers addressed modern topics combining cyber security and natural language processing (NLP).

The first paper, entitled “Advanced Deep Learning Techniques to Improve Cyber-bullying Detection in Arabic Tweets,” was published in the Jordanian Journal of Computers and Information Technology (JJCIT). This paper presented an advanced model based on Recurrent Neural Networks (RNNs) to detect cyber-bullying in Arabic-language tweets. The research achieved outstanding results, confirming the effectiveness of deep learning techniques in processing Arabic texts and addressing the linguistic challenges facing Arabic-speaking communities.

The second paper, entitled “Spam Detection Using an Advanced Hybrid Model,” was published in the Journal of Advances in Information Technology (JAIT). The research developed a hybrid model that combines bidirectional encoder representations from transformers (BERT), multilayer perceptron (MLP) neural networks, and modern transformer techniques to detect spam messages. This model makes a significant scientific contribution to the development of email systems, enhancing information security, and protecting user privacy.

This achievement underscores the excellence of the Master’s in Information Security students and the pioneering role of the Arab American University in supporting qualitative research that employs advanced artificial intelligence and machine learning techniques to address real-world challenges in cyber security, strengthening its position as a leading academic institution in scientific research and technological development.