A survey on network game cheats and P2P solutions

The increasing popularity of Massively Multiplayer Online Games (MMOG) - games involving thousands of players participating simultaneously in a single virtual world - has highlighted the scalability bottlenecks present in centralised Client/Server (C/S) architectures. Researchers are proposing Peer-to-Peer (P2P) game technologies as a scalable alternative to C/S; however, P2P is more vulnerable to cheating as it decentralises the game state and logic to un-trusted peer machines, rather than using trusted centralised servers. Cheating is a major concern for online games, as a minority of cheaters can potentially ruin the game for all players. In this paper we present a review and classification of known cheats, and provide real-world examples where possible. Further, we discuss counter measures used by C/S game technologies to prevent cheating. Finally, we discuss several P2P architectures designed to prevent cheating, highlighting their strengths and weaknesses

Cheating in networked computer games: a review

The increasing popularity of Massively Multiplayer Online Games (MMOG) - games involving thousands of players participating simultaneously in a single virtual world - has highlighted the scalability bottlenecks present in centralised Client/Server (C/S) architectures. Researchers are proposing Peer-to-Peer (P2P) architectures as a scalable alternative to C/S; however, P2P is more vulnerable to cheating as it decentralises the game state and logic to un-trusted peer machines, rather than using trusted centralised servers. Cheating is a major concern for online games, as a minority of cheaters can potentially ruin the game for all players. In this paper we present a review and classification of known cheats, and provide real-world examples where possible. Further, we discuss counter measures used by C/S architectures to prevent cheating. Finally, we discuss several P2P architectures designed to prevent cheating, highlighting their strengths and weaknesses

Referee-based architectures for massively multiplayer online games

Network computer games are played amongst players on different hosts across the Internet. Massively Multiplayer Online Games (MMOG) are network games in which thousands of players participate simultaneously in each instance of the virtual world. Current commercial MMOG use a Client/Server (C/S) architecture in which the server simulates and validates the game, and notifies players about the current game state. While C/S is very popular, it has several limitations: (i) C/S has poor scalability as the server is a bandwidth and processing bottleneck; (ii) all updates must be routed through the server, reducing responsiveness; (iii) players with lower client-to-server delay than their opponents have an unfair advantage as they can respond to game events faster; and (iv) the server is a single point of failure.The Mirrored Server (MS) architecture uses multiple mirrored servers connected via a private network. MS achieves better scalability, responsiveness, fairness, and reliability than C/S; however, as updates are still routed through the mirrored servers the problems are not eliminated. P2P network game architectures allow players to exchange updates directly, maximising scalability, responsiveness, and fairness, while removing the single point of failure. However, P2P games are vulnerable to cheating. Several P2P architectures have been proposed to detect and/or prevent game cheating. Nevertheless, they only address a subset of cheating methods. Further, these solutions require costly distributed validation algorithms that increase game delay and bandwidth, and prevent players with high latency from participating.In this thesis we propose a new cheat classification that reflects the levels in which the cheats occur: game, application, protocol, or infrastructure. We also propose three network game architectures: the Referee Anti-Cheat Scheme (RACS), the Mirrored Referee Anti-Cheat Scheme (MRACS), and the Distributed Referee Anti-Cheat Scheme (DRACS); which maximise game scalability, responsiveness, and fairness, while maintaining cheat detection/prevention equal to that in C/S. Each proposed architecture utilises one or more trusted referees to validate the game simulation - similar to the server in C/S - while allowing players to exchange updates directly - similar to peers in P2P.RACS is a hybrid C/S and P2P architecture that improves C/S by using a referee in the server. RACS allows honest players to exchange updates directly between each other, with a copy sent to the referee for validation. By allowing P2P communication RACS has better responsiveness and fairness than C/S. Further, as the referee is not required to forward updates it has better bandwidth and processing scalability. The RACS protocol could be applied to any existing C/S game. Compared to P2P protocols RACS has lower delay, and allows players with high delay to participate. Like in many P2P architectures, RACS divides time into rounds. We have proposed two efficient solutions to find the optimal round length such that the total system delay is minimised.MRACS combines the RACS and MS architectures. A referee is used at each mirror to validate player updates, while allowing players to exchange updates directly. By using multiple mirrored referees the bandwidth required by each referee, and the player-to mirror delays, are reduced; improving the scalability, responsiveness and fairness of RACS, while removing its single point of failure. Direct communication MRACS improves MS in terms of its responsiveness, fairness, and scalability. To maximise responsiveness, we have defined and solved the Client-to-Mirror Assignment (CMA) problem to assign clients to mirrors such that the total delay is minimised, and no mirror is overloaded. We have proposed two sets of efficient solutions: the optimal J-SA/L-SA and the faster heuristic J-Greedy/L-Greedy to solve CMA.DRACS uses referees distributed to player hosts to minimise the publisher / developer infrastructure, and maximise responsiveness and/or fairness. To prevent colluding players cheating DRACS requires every update to be validated by multiple unaffiliated referees, providing cheat detection / prevention equal to that in C/S. We have formally defined the Referee Selection Problem (RSP) to select a set of referees from the untrusted peers such that responsiveness and/or fairness are maximised, while ensuring the probability of the majority of referees colluding is below a pre-defined threshold. We have proposed two efficient algorithms, SRS-1 and SRS-2, to solve the problem.We have evaluated the performances of RACS, MRACS, and DRACS analytically and using simulations. We have shown analytically that RACS, MRACS and DRACS have cheat detection/prevention equivalent to that in C/S. Our analysis shows that RACS has better scalability and responsiveness than C/S; and that MRACS has better scalability and responsiveness than C/S, RACS, and MS. As there is currently no publicly available traces from MMOG we have constructed artificial and realistic inputs. We have used these inputs on all simulations in this thesis to show the benefits of our proposed architectures and algorithms

Cheating Prevention in Peer-to-Peer-based Massively Multiuser Virtual Environments

Massively multiuser virtual environments (MMVEs) have become an increasingly popular Internet application in recent years. Until now, they are all based on client/server technology. Due to its inherent lack of scalability, realizing MMVEs based on peer-to-peer technology has received a lot of interest. From the perspective of the operator, using peer-to-peer technology raises additional challenges: the lack of trust in peers and their unreliability. The simulation of the virtual environment is governed by certain rules specified by the operator. These rules state what actions can be taken by users in the virtual environment and how the state of the environment changes based on these actions. Since MMVEs are very often competitive environments, some people will cheat and try to break the rules to get an unfair advantage over others. Using a central server performing the simulation of the virtual environment, the operator can ensure only allowed actions can be performed and the state of the environment evolves according to the rules. In a peer-to-peer setting, the operator has no control over the peers so they might not behave as implemented by the operator. Furthermore, a central server is inherently more reliable than a peer which could fail at any time so data might be lost. This thesis presents the design of a storage performing a distributed simulation of a virtual environment. It uses a deterministic event-based simulation to calculate the state of the virtual environment only based on the actions of its users. There are multiple replicated simulations using a voting mechanism to overcome the influence of malicious peers trying to tamper with the state of the environment as long as the number of malicious peers does not reach a critical threshold. Replication of data also ensures data is not lost when peers fail. The storage is based on a peer-to-peer overlay allowing peers to exchange messages to store and retrieve data. It creates a Delaunay graph structure matching the way the data in the virtual environment is distributed among the peers. A self-stabilizing algorithm keeps the structure intact as peers join and leave the network. Additional routing tables allow peers to retrieve stored replicas independently on short, disjoint paths reducing the influence of malicious peers on the retrieval of data. A redundant filling algorithm prevents malicious peers from tampering with these routing tables to get more messages routed their way

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp