THE ANTICHEAT DEVELOPMENT IN THE COUNTER-STRIKE MAIN SERIES
Abstract
This research investigates methods to identify and prevent cheating in online games, focusing on Counter-Strike (CS). It explores various cheating behaviors and their evolution alongside anti-cheat development. The limitations of current anti-cheat systems, exemplified by Valve Anti-Cheat and Faceit Anti-Cheat, are highlighted through real-world cases where cheating suspicions arose but no conclusive evidence was found. The paper proposes analyzing player mechanics, including keyboard patterns and movement, as a potential solution to detect radar hacks, smurfing, and unsportsmanlike behavior. By training a system on player behavioral patterns, the authors aim to create a fairer and more enjoyable online gaming experience for CS players.
Keywords: pattern recognition, cheating, anti-cheat, esport, smurfing, Counter - Strike, CS2
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DOI: http://dx.doi.org/10.30970/eli.26.8
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