The Cybersecurity Department at Jordan University of Science and Technology (JUST) proudly announces the publication of a pioneering dataset in the Elsevier | Mendeley Data repository, advancing global research in darknet traffic detection and cybersecurity.
The novel dataset, titled “SafeSurf Darknet 2025”, was developed under the supervision of Dr. Qasem Abu Al-Haija, Head of the Cybersecurity Department, as part of the graduation project “SafeSurf: Defender Against Darknet Threats,” by a talented team of undergraduate cybersecurity students: Mohammad Obeidat, Ibrahim Al-Syouf, Yahea Awawdeh, and Anas Masadeh.
Innovative Scope:
The dataset includes labeled darknet traffic from platforms such as Tor, Freenet, I2P, and others.
Applications:
It is designed to support research in darknet detection, intrusion detection systems (IDS), and AI-powered threat analysis.
Dr. Abu Al-Haija stated:
"This dataset provides a vital resource for the research community to strengthen security solutions against darknet threats. It demonstrates the capacity of our students to contribute impactful work to the international cybersecurity field."
Prof. Muneer Bani Yasseen, Dean of the Faculty of Computer and Information Technology, also praised the achievement, stating:
"We are proud of this pioneering work, which reflects the high caliber of our students and faculty in the Cybersecurity Department. This initiative exemplifies the synergy between education and applied research and reinforces the university's position as a regional and international leader in cybersecurity."
Access and Publications:
The dataset is publicly accessible via Elsevier’s repository:
For more details, refer to the related research articles:
