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Nguyen Thi Hai Ha's research paper on Web Attack Detection has been accepted for publication at the international scientific conference SoICT 2023.

Congratulations to Nguyen Thi Hai Ha, a student majoring in Information Security (Faculty of Computer Networks and Communications) and her research team InSecLab for having their research paper on Web Attack Detection accepted at the 12th Symposium on Information and Communication Technology (SoICT 2023) conference.

The SoICT 2023 conference will be held in Ho Chi Minh City, organized by the School of Information and Communication Technology at Hanoi University of Science and Technology, Vietnam National University Ho Chi Minh City-University of Sciences at, Laboratory Informatics, Modelling and Optimisation System (LIMOS), The French National Centre for Scientific Research (CNRS), and the Institute for Advanced Study in Mathematics on December 7-8, 2023.

The research paper was the result of the research project conducted by the student with the InSecLab research group during her participation in the graduation thesis and scientific research on Artificial Intelligence-based techniques for web attack detection at the Information Security Laboratory (InSecLab).

Paper Information:

Title: "WebGuardRL: An Innovative Reinforcement Learning-based Approach for Advanced Web Attack Detection"

Writer: Nguyen Thi Hai Ha - Information Security (Regular program 2019)

Research Topic: Artificial Intelligence and Information Security

Supervisors: MS. Do Hoang Hien & Ph.D. Pham Van Hau

General Information:

SoICT 2023 is an international scientific conference specializing in information technology and communication, covering important research areas including AI Foundations and Big Data, Networking and Communications Technologies, Image Processing and Natural Language, Software Engineering, Artificial Intelligence, and Digital Technologies, Information Security, and Event Information Retrieval from Video.

Abstract: “Web-based applications are often potential targets for attackers due to the important data and assets that they manage. With the explosion and increasing complexity of recent attacks aiming at these applications, traditional security solutions such as intrusion detection systems (IDS) or web application firewalls (WAF) become ineffective against unpredictable threats. Meanwhile, in the trend of applying AI techniques to achieve practical effectiveness in various fields, cutting-edge reinforcement learning (RL) has also gained more attention for its promising applications, one of which is sophisticated attack detection. In this study, we introduce an RL-based model, named WebGuardRL, to detect multiple advanced web attacks by analyzing URLs in HTTP requests containing various attack types. To achieve this, our model is equipped with the capability of representing URLs that differ from attack to attack in the same form for use in RL training. The experimental results and comparisons with other methods indicate the high accuracy and remarkable capability of our WebGuardRL in web attack detection.” 

Conference link: https://soict.org/submission/paper-submission/

https://www.uit.edu.vn/sites/vi/files/image_from_word/hai_ha.jpg

For more details, visit: https://www.facebook.com/inseclab/posts/pfbid02VxnWFVWUvtpapSaw5i6...

Hai Bang - Media Collaborator, University of Information Technology

Translation: Nhat Hien