Collaboration in Social Networks

The very notion of social network implies that linked individuals interact repeatedly with each other. This allows them not only to learn successful strategies and adapt to them, but also to condition their own behavior on the behavior of others, in a strategic forward looking manner. Game theory of repeated games shows that these circumstances are conducive to the emergence of collaboration in simple games of two players. We investigate the extension of this concept to the case where players are engaged in a local contribution game and show that rationality and credibility of threats identify a class of Nash equilibria -- that we call "collaborative equilibria" -- that have a precise interpretation in terms of sub-graphs of the social network. For large network games, the number of such equilibria is exponentially large in the number of players. When incentives to defect are small, equilibria are supported by local structures whereas when incentives exceed a threshold they acquire a non-local nature, which requires a "critical mass" of more than a given fraction of the players to collaborate. Therefore, when incentives are high, an individual deviation typically causes the collapse of collaboration across the whole system. At the same time, higher incentives to defect typically support equilibria with a higher density of collaborators. The resulting picture conforms with several results in sociology and in the experimental literature on game theory, such as the prevalence of collaboration in denser groups and in the structural hubs of sparse networks

A sensing platform for physiological and contextual feedback to tennis athletes

In this paper we describe our work on creating a multi-modal sensing platform for providing feedback to tennis coaches and players. The platform includes a fixed installation around a tennis court consisting of a video camera network and a localisation system as well as wearable sensing technology deployed to individual athletes. We describe the various components of this platform and explain how we can capture synchronised multi-modal sensor data streams for games or training sessions. We then describe the content-based retrieval system we are building to facilitate the development of novel coaching tools. We provide some examples of the queries that the system can support, where these queries are chosen to be suitably expressive so as to reflect a coach's complex information needs regarding tennis-related performance factors

Resource allocation for massively multiplayer online games using fuzzy linear assignment technique

This paper investigates the possible use of fuzzy system and Linear Assignment Problem (LAP) for resource allocation for Massively Multiplayer Online Games (MMOGs). Due to the limitation of design capacity of such complex MMOGs, resources available in the game cannot be unlimited. Resources in this context refer to items used to support the game play and activities in the MMOGs, also known as in-game resources. As for network resources, it is also one of the important research areas for MMOGs due to the increasing number of players. One of the main objectives is to ensure the Quality of Service (QoS) in the MMOGs environment for each player. Regardless, which context the resource is defined, the proposed method can still be used. Simulated results based on the network resources to ensure QoS shows that the proposed method could be an alternative

DScent Final Report

DScent was a joint project between five UK universities combining research theories in the disciplines of computational inference, forensic psychology and expert decision-making in the area of counter-terrorism. This document discusses the work carried out by Leeds Metropolitan University which covers the research, design and development work of an investigator support system in the area of deception using artificial intelligence. For the purposes of data generation along with system and hypothesis testing the project team devised two closed world games, the Cutting Corners Board Game and the Location Based Game. DScentTrail presents the investigator with a ‘scent trail’ of a suspect’s behaviour over time, allowing the investigator to present multiple challenges to a suspect from which they may prove the suspect guilty outright or receive cognitive or emotional clues of deception (Ekman 2002; Ekman & Frank 1993; Ekman & Yuille 1989; Hocking & Leathers 1980; Knapp & Comadena 1979). A scent trail is a collection of ordered, relevant behavioural information over time for a suspect. There are links into a neural network, which attempts to identify deceptive behavioural patterns of individuals. Preliminary work was carried out on a behavioural based AI module which would work separately alongside the neural network, with both identifying deception before integrating their results to update DScentTrail. Unfortunately the data that was necessary to design such a system was not provided and therefore, this section of research only reached its preliminary stages. To date research has shown that there are no specific patterns of deceptive behaviour that are consistent in all people, across all situations (Zuckerman 1981). DScentTrail is a decision support system, incorporating artificial intelligence (AI), which is intended to be used by investigators and attempts to find ways around the problem stated by Zuckerman above

Crime Scene Re-investigation: A Postmortem Analysis of Game Account Stealers' Behaviors

As item trading becomes more popular, users can change their game items or money into real money more easily. At the same time, hackers turn their eyes on stealing other users game items or money because it is much easier to earn money than traditional gold-farming by running game bots. Game companies provide various security measures to block account- theft attempts, but many security measures on the user-side are disregarded by users because of lack of usability. In this study, we propose a server-side account theft detection system base on action sequence analysis to protect game users from malicious hackers. We tested this system in the real Massively Multiplayer Online Role Playing Game (MMORPG). By analyzing users full game play log, our system can find the particular action sequences of hackers with high accuracy. Also, we can trace where the victim accounts stolen money goes.Comment: 7 pages, 8 figures, In Proceedings of the 15th Annual Workshop on Network and Systems Support for Games (NetGames 2017

Bandwith Optimization on Hotspot using PCQ Method And L2tp VPN Routing for Online Game Latency

VPN L2TP (Layer 2 Tunneling Protocol) is available on one of the services at Mikrotik. L2TP is a development of PPTP and a combination of L2F. The network security protocol and encryption used for authentication is the same as PPTP. However, to communicate, L2TP requires UDP port 1701 so that the security is better, L2TP is connected to IPSec to L2TP/IPSec. An example of its use is for the Windows operating system, which by default the Windows OS uses L2TP/IPSec. However, the consequences in terms of configuration are not as simple as PPTP. The client side must also support IPSec when implementing L2TP/IPSec. In terms of encryption, of course, encryption on L2TP/IPSec has a higher level of security than PPTP which uses MPPE. Traffic passing through the L2TP tunnel will experience overhead. The L2TP protocol is more firewall friendly than other types of VPNs such as PPTP. This is a big advantage if using this protocol, because most firewalls do not support GRE. However, L2TP does not have encryption, so it requires additional services to support higher security. So the author concludes that it will be easier to configure with online games. Online game is a type of computer game that is currently growing and requires a computer network . The networks that are usually used are internet networks or internet wifi and the like and always use current technology, such as modems and cable connections. Therefore, internet service providers (ISPs) must provide stable and fast internet quality. Bandwidth Needs Online games must be supported by an internet network that supports the speed and stability of the internet connection, especially the stability of the latency of the online game itsel

Towards Autonomous Defense of SDN Networks Using MuZero Based Intelligent Agents

The Software Defined Networking (SDN) paradigm enables the development of systems that centrally monitor and manage network traffic, providing support for the deployment of machine learning-based systems that automatically detect and mitigate network intrusions. This paper presents an intelligent system capable of deciding which countermeasures to take in order to mitigate an intrusion in a software defined network. The interaction between the intruder and the defender is posed as a Markov game and MuZero algorithm is used to train the model through self-play. Once trained, the model is integrated with an SDN controller, so that it is able to apply the countermeasures of the game in a real network. To measure the performance of the model, attackers and defenders with different training steps have been confronted and the scores obtained by each of them, the duration of the games and the ratio of games won have been collected. The results show that the defender is capable of deciding which measures minimize the impact of the intrusion, isolating the attacker and preventing it from compromising key machines in the network.This work was supported in part by the Spanish Centre for the Development of Industrial Technology (CDTI) through the Project EGIDA-RED DE EXCELENCIA EN TECNOLOGIAS DE SEGURIDAD Y PRIVACIDAD under Grant CER20191012, in part by the Spanish Ministry of Science and Innovation under Grant PID2019-104966GB-I00, in part by the Basque Business Development Agency (SPRI)-Basque Country Government ELKARTEK Program through the projects TRUSTIND under Grant KK-2020/00054 and 3KIA under Grant KK-2020/00049, and in part by the Basque Country Program of Grants for Research Groups under Grant IT-1244-19

Network traffic characterisation, analysis, modelling and simulation for networked virtual environments

Networked virtual environment (NVE) refers to a distributed software system where a simulation, also known as virtual world, is shared over a data network between several users that can interact with each other and the simulation in real-time. NVE systems are omnipresent in the present globally interconnected world, from entertainment industry, where they are one of the foundations for many video games, to pervasive games that focus on e-learning, e-training or social studies. From this relevance derives the interest in better understanding the nature and internal dynamics of the network tra c that vertebrates these systems, useful in elds such as network infrastructure optimisation or the study of Quality of Service and Quality of Experience related to NVE-based services. The goal of the present work is to deepen into this understanding of NVE network tra c by helping to build network tra c models that accurately describe it and can be used as foundations for tools to assist in some of the research elds enumerated before. First contribution of the present work is a formal characterisation for NVE systems, which provides a tool to determine which systems can be considered as NVE. Based on this characterisation it has been possible to identify numerous systems, such as several video games, that qualify as NVE and have an important associated literature focused on network tra c analysis. The next contribution has been the study of this existing literature from a NVE perspective and the proposal of an analysis pipeline, a structured collection of processes and techniques to de ne microscale network models for NVE tra c. This analysis pipeline has been tested and validated against a study case focused on Open Wonderland (OWL), a framework to build NVE systems of di erent purpose. The analysis pipeline helped to de ned network models from experimental OWL tra c and assessed on their accuracy from a statistical perspective. The last contribution has been the design and implementation of simulation tools based on the above OWL models and the network simulation framework ns-3. The purpose of these simulations was to con rm the validity of the OWL models and the analysis pipeline, as well as providing potential tools to support studies related to NVE network tra c. As a result of this nal contribution, it has been proposed to exploit the parallelisation potential of these simulations through High Throughput Computing techniques and tools, aimed to coordinate massively parallel computing workloads over distributed resources