Chatting Pattern Based Game BOT Detection: Do They Talk Like Us?

Abstract

Localization of sensor nodes is a key technology in Wireless Sensor Networks(WSNs). Trilateration is an important position determination strategy. To further improve the localization accuracy, a novel Trilateration based on Point In Triangle testing Localization (TPITL)algorithm is proposed in the paper. Unlike the traditional trilateration localization algorithm which randomly selects three neighbor anchors, the proposed TPITL algorithm selects three special neighbor anchors of the unknown node for trilateration. The three anchors construct the smallest anchor triangle which encloses the unknown node. To choose the optimized anchors, we propose Point In Triangle testing based on Distance(PITD) method, which applies the estimated distances for trilateration to reduce the PIT testing errors. Simulation results show that the PIT testing errors of PITD are much lower than Approximation PIT(APIT) method and the proposed TPITL algorithm significantly improves the localization accuracy.

I know what the BOTs did yesterday: Full action sequence analysis using Naïve Bayesian algorithm

“…Thus, server-side detection methods are more secure than client-side methods. Previous studies on server-side BOT detection methods selected features from a vast array of user actions, and applied data mining techniques [3,4,5,6]. Most of these studies used one-dimensional log data due to computational complexity in spite of the fact that game BOT traces are found in multidimensional log data.…”

Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM

“…Leveraging chat logs among users, Kang et al derived lexical, syntactic, semantic features from chatting contents using text mining methods. As bots have similar pattern of chatting to evade detection rules, analyzing text features with machine learning algorithms showed such high performance [9]. Kang et al also analyzed party play log for game bot classification.…”

You are a Game Bot!: Uncovering Game Bots in MMORPGs via Self-similarity in the Wild

“…Unsurprisingly, using general features have relatively low performance compared with the classification algorithms with features specific to games and/or genre. Kang et al [14] proposed a bot detection model based on the difference in chatting patterns between bots and human users. Kang et al [15] also proposed a game bot detection method based on the players' network characteristics.…”