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DOI: 10.14569/IJACSA.2020.0110622
PDF

Analyzing the Performance of Web-services during Traffic Anomalies

Author 1: Avneet Dhingra
Author 2: Monika Sachdeva

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 6, 2020.

  • Abstract and Keywords
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Abstract: Intentional or unintentional, service denial leads to substantial economic and reputation losses to the users and the web-service provider. However, it is possible to take proper measures only if we understand and quantify the impact of such anomalies on the victim. In this paper, essential performance metrics distinguishing both transmission issues and application issues have been discussed and evaluated. The legitimate and attack traffic has been synthetically generated in hybrid testbed using open-source software tools. The experiment covers two scenarios, representing DDoS attacks and Flash Events, with varying attack strengths to analyze the impact of anomalies on the server and the network. It has been demonstrated that as the traffic surges, response time increases, and the performance of the target web-server degrades. The performance of the server and the network is measured using various network level, application level, and aggregate level metrics, including throughput, average response time, number of legitimate active connections and percentage of failed transactions.

Keywords: Denial of service; DDoS attack; flash event; performance metrics; throughput; response time

Avneet Dhingra and Monika Sachdeva, “Analyzing the Performance of Web-services during Traffic Anomalies” International Journal of Advanced Computer Science and Applications(IJACSA), 11(6), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110622

@article{Dhingra2020,
title = {Analyzing the Performance of Web-services during Traffic Anomalies},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110622},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110622},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {6},
author = {Avneet Dhingra and Monika Sachdeva}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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