A TRUSTWORTHY PARTNER SELECTION FOR MMOG USING AN IMPROVED THREE VALUED SUBJECTIVE LOGIC UNCERTAINTY TRUST MODEL
In massively multiplayer online games (MMOG), the player interacts with other players through partners' random selection. Hence, random selection leads to various problems, such as to request contention and cheating in online games. Hence, trust-based partner selection is essential in the virtual world. However, the most existing trust models determine whether the players' absolute trust is either trustworthy or not. Therefore, the proposed work addresses the uncertainty trust assessment in the virtual world. This work proposes to improve the three-value subjective logic uncertainty model (I-3VSL) to assess the trust through a direct and indirect assessment. The Trustwalker (TW) algorithm is designed to assess a selected partner's trust using 3VSL and I-3VSL. As a result, the TW algorithm evaluates trust through other players' recommendations that find the path from trustee to trustee. The recommendations are filtered through the verification of the player's eligibility in the specified depth. To validate the TW algorithm with 3VSL and I-3VSL is assessed using the Travian dataset. The experiment results demonstrate that the I-3VSL with TW algorithm is more efficient than the 3VSL algorithm. I-3VSL provides an optimized error rate using mean absolute error of and root mean square error . Further, the accuracy at various depth levels is obtained and reduces the computation time compared to 3VSL.Keywords: cheating, massively multiplayer online games, recommendations, three-valued subjective logic, trust-partner, Trustwalker, uncertainty, virtual world.