Deep Learning Techniques to Detect Botnet
DOI:
https://doi.org/10.54654/isj.v1i15.846Keywords:
deep learning, BoTShark-SA, BoTShark-CNN, botnetTóm tắt
Abstract— Over the past time, the world has witnessed an unprecedented explosion of Deep Learning. Besides thedevelopment of Information Technology, security and safety threats are also increasing, one of which is the Botnet network. Botnet network is increasingly complex and difficult to detect, and traditional techniques are no longer effective, so one of the urgent problems today is to find an effective solution to detecting botnets [2]. Based on the characteristics of deep learning such as scalability, performance, execution time, interpretability, etc., therefore, in this paper, the author proposes to use deep learning techniques to detect Botnet networks.
Downloads
References
Đoàn Xuân Dũng, "Tóm tắt văn bản sử dụng các kỹ thuật trong Deep Learning", Luận văn ThS. Máy tính: 84801, 2018: 30-40.
Hoàng Xuân Dậu, Nguyễn Trọng Hưng và Ninh Thị Thu Trang "Phát hiện botnet dựa trênhọc máy sử dụng dữ liệu truy vấn DNS: Phân tích ảnh hưởng của các đặc trưng huấn luyện", Hội thảo quốc gia lần thứ XXII Công nghệ thông tin và truyền thông. Thái Bình, 28- 29/6/2019: 20-30; 100-120.
Trần Thị Hằng, “Nghiên cứu tìm hiểu thực trạng về an ninh mạng và biện pháp khắc phục”. Đại học Dân lập Hải Phòng, 2016:30-40.
Abu Rajab, M., Zarfoss, J., Monrose, F., &Terzis, A “A multifaceted approach to understanding the botnet phenomenon.” Hội thảo ACM SIGCOMM lần thứ 6 về Internet Measurement, 08/2006: 41- 52.
Banday, M. Tariq, Jameel A. Qadri, and Nisar A. Shah, “Study of Botnets and their threats to Internet
Security”, University of Kashmir, 06/05/2009: 9-24.
Kronotis, Nickolaos “Towards the development of realistic botnet dataset in the internet of things for network forensic analytics: Bot-iot dataset”. Future Generation Computer Systems, University of New South Wales Canberra, Australia, 2019: 779-796.
LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton, “Deep Learning”, Nature, 2015: 436-444.
Nogueira, António, Paulo Salvador, and Fábio Blessa, "A botnet detection system based on neural networks", Hội thảo quốc tế về điện tử truyền thông lần thứ 5, Piscataway, New Jersey, 2010: 57-62.
Wang, Jing, and Ioannis Ch Paschalidis, "Botnet detection based on anomaly and community detection", IEEE Transactions on Control of Network Systems, 2016 4(2): 50-60, 2016.
Downloads
Published
How to Cite
Issue
Section
License
Proposed Policy for Journals That Offer Open Access
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Proposed Policy for Journals That Offer Delayed Open Access
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication, with the work [SPECIFY PERIOD OF TIME] after publication simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
