| Issue |
E3S Web Conf.
Volume 202, 2020
The 5th International Conference on Energy, Environmental and Information System (ICENIS 2020)
|
|
|---|---|---|
| Article Number | 15003 | |
| Number of page(s) | 10 | |
| Section | Smart Information System | |
| DOI | https://doi.org/10.1051/e3sconf/202020215003 | |
| Published online | 10 November 2020 | |
Denial of Service (DoS) attack identification and analyse using sniffing technique in the network environment
1 Department of Information System, School of Postgraduate Studies Diponegoro University, Semarang – Indonesia
2 Department of Information System, School of Postgraduate Studies Diponegoro University, Semarang – Indonesia
3 Data Entry and Update Taxpayer’s Registry in Rwanda Revenue Authority(RRA) Kigali-Rwanda
* Corresponding author: alexkagiraneza@gmail.com
Network-based intruders such as (DoS) attacks have become one of the most significant internet interruptions. Some operations that rely on the internet, such as banking transactions, education, trade marketing, and social networking, have become the primary targets. The attacker is trying to surround and making it difficult for the system to defend. The research's objective is to recognize the characteristics and level of DoS attacks. In understanding the behavior of intruders against a target web server, Wireshark was used in all traffic networks—capturing the traffic in a networked environment. In this research, the user identifies the attack levels (TCP SYN, UDP, and HTTP protocol), ranging from low (Q1), medium (Q2), and high (Q4) attacks. The approach is to simulate the TCP, HTTP, and UDP flood attacks and analyze the attacks' effects on the network environment. In this work, normal scenarios and pattern attacks were compared. In this case, the intruder floods unwanted packets to the victim with a massive number of request packets; the SYN from the corresponding SYN-ACK replies are not achieved. This paper will identify the DoS attacks level and analyze the behavior of traffics.
Key words: DoS attacks level Identification and traffic analysis criteria of traffic
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.