Stiawan, D. and Idris, M. Y. and Aryandi, D. and Heryanto, A. and Septian, T. W. and Muchtar, F. and Budiarto, R. (2019) Behavior pattern recognition of game dragon nest using bloom filter method. International Journal of Communication Networks and Information Security, 11 (1). pp. 128-133.
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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 show 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 experiment is 0.399576%.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | online game, traffic classification, visualization |
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Computing |
| ID Code: | 89253 |
| Deposited By: | Narimah Nawil |
| Deposited On: | 09 Feb 2021 02:36 |
| Last Modified: | 09 Feb 2021 02:36 |
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