Behavior Pattern Recognition of Game Dragon Nest Using Bloom Filter Method

Authors

  • Deris Stiawan Universitas Sriwijaya
  • Diky Aryandi Universitas Sriwijaya
  • Ahmad Heryanto Universitas Sriwijaya
  • Tri Wanda Septian Tri Wanda Septian1
  • Farkhana Muchtar Faculty of Engineering, School of Computing, Universiti Teknologi Malaysia
  • Mohd. Yazid Idris Universiti Teknologi Malaysia
  • Rahmat Budiarto Albaha University

DOI:

https://doi.org/10.17762/ijcnis.v11i1.3789

Abstract

Dragon Nest is one of Massively Multiplayer Online Role-playing Game (MMORPG online games. It has become the most popular online game played by people around the world. This work observes two examples of the MMORPG online games: the Dragon Nest INA and the Legend DN II. The purpose is to analyze the traffic data of the Dragon Nest to find and discern the patterns of behavior of the Dragon Nest INA and the Legend DN II using Deep Packet Inspection (DPI).  A dataset is constructed by capturing traffic data from the testbed environment. Then feature extraction, feature selection, and visualization are performed during the experiments. Experiment results shows the traffic data of the Dragon Nest INA is higher than the Legend DN II. It is because of the difference in the number of entries in the game. Then, the Bloom filter method is used as a tool to check the existence of a pattern of the Dragon Nest in the dataset. The false positive rate of matching is 0.399576%.

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Published

2019-04-19 — Updated on 2022-04-17

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How to Cite

Stiawan, D., Aryandi, D., Heryanto, A., Septian, T. W., Muchtar, F., Idris, M. Y., & Budiarto, R. (2022). Behavior Pattern Recognition of Game Dragon Nest Using Bloom Filter Method. International Journal of Communication Networks and Information Security (IJCNIS), 11(1). https://doi.org/10.17762/ijcnis.v11i1.3789 (Original work published April 19, 2019)

Issue

Vol. 11 No. 1 (2019)

Section

Research Articles