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2021-03-01
Tao, J., Xiong, Y., Zhao, S., Xu, Y., Lin, J., Wu, R., Fan, C..  2020.  XAI-Driven Explainable Multi-view Game Cheating Detection. 2020 IEEE Conference on Games (CoG). :144–151.
Online gaming is one of the most successful applications having a large number of players interacting in an online persistent virtual world through the Internet. However, some cheating players gain improper advantages over normal players by using illegal automated plugins which has brought huge harm to game health and player enjoyment. Game industries have been devoting much efforts on cheating detection with multiview data sources and achieved great accuracy improvements by applying artificial intelligence (AI) techniques. However, generating explanations for cheating detection from multiple views still remains a challenging task. To respond to the different purposes of explainability in AI models from different audience profiles, we propose the EMGCD, the first explainable multi-view game cheating detection framework driven by explainable AI (XAI). It combines cheating explainers to cheating classifiers from different views to generate individual, local and global explanations which contributes to the evidence generation, reason generation, model debugging and model compression. The EMGCD has been implemented and deployed in multiple game productions in NetEase Games, achieving remarkable and trustworthy performance. Our framework can also easily generalize to other types of related tasks in online games, such as explainable recommender systems, explainable churn prediction, etc.
2021-02-03
Ye, S., Feigh, K., Howard, A..  2020.  Learning in Motion: Dynamic Interactions for Increased Trust in Human-Robot Interaction Games. 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). :1186—1189.

Embodiment of actions and tasks has typically been analyzed from the robot's perspective where the robot's embodiment helps develop and maintain trust. However, we ask a similar question looking at the interaction from the human perspective. Embodied cognition has been shown in the cognitive science literature to produce increased social empathy and cooperation. To understand how human embodiment can help develop and increase trust in human-robot interactions, we created conducted a study where participants were tasked with memorizing greek letters associated with dance motions with the help of a humanoid robot. Participants either performed the dance motion or utilized a touch screen during the interaction. The results showed that participants' trust in the robot increased at a higher rate during human embodiment of motions as opposed to utilizing a touch screen device.

2020-11-17
Jaiswal, M., Malik, Y., Jaafar, F..  2018.  Android gaming malware detection using system call analysis. 2018 6th International Symposium on Digital Forensic and Security (ISDFS). :1—5.
Android operating systems have become a prime target for attackers as most of the market is currently dominated by Android users. The situation gets worse when users unknowingly download or sideload cloning applications, especially gaming applications that look like benign games. In this paper, we present, a dynamic Android gaming malware detection system based on system call analysis to classify malicious and legitimate games. We performed the dynamic system call analysis on normal and malicious gaming applications while applications are in execution state. Our analysis reveals the similarities and differences between benign and malware game system calls and shows how dynamically analyzing the behavior of malicious activity through system calls during runtime makes it easier and is more effective to detect malicious applications. Experimental analysis and results shows the efficiency and effectiveness of our approach.
2020-08-28
Ferreira, P.M.F.M., Orvalho, J.M., Boavida, F..  2005.  Large Scale Mobile and Pervasive Augmented Reality Games. EUROCON 2005 - The International Conference on "Computer as a Tool". 2:1775—1778.
Ubiquitous or pervasive computing is a new kind of computing, where specialized elements of hardware and software will have such high level of deployment that their use will be fully integrated with the environment. Augmented reality extends reality with virtual elements but tries to place the computer in a relatively unobtrusive, assistive role. To our knowledge, there is no specialized network middleware solution for large-scale mobile and pervasive augmented reality games. We present a work that focus on the creation of such network middleware for mobile and pervasive entertainment, applied to the area of large scale augmented reality games. In, this context, mechanisms are being studied, proposed and evaluated to deal with issues such as scalability, multimedia data heterogeneity, data distribution and replication, consistency, security, geospatial location and orientation, mobility, quality of service, management of networks and services, discovery, ad-hoc networking and dynamic configuration
Ferreira, Pedro, Orvalho, Joao, Boavida, Fernando.  2007.  Security and privacy in a middleware for large scale mobile and pervasive augmented reality. 2007 15th International Conference on Software, Telecommunications and Computer Networks. :1—5.
Ubiquitous or pervasive computing is a new kind of computing, where specialized elements of hardware and software will have such high level of deployment that their use will be fully integrated with the environment. Augmented reality extends reality with virtual elements but tries to place the computer in a relatively unobtrusive, assistive role. In this paper we propose, test and analyse a security and privacy architecture for a previously proposed middleware architecture for mobile and pervasive large scale augmented reality games, which is the main contribution of this paper. The results show that the security features proposed in the scope of this work do not affect the overall performance of the system.
2020-04-10
Baral, Gitanjali, Arachchilage, Nalin Asanka Gamagedara.  2019.  Building Confidence not to be Phished Through a Gamified Approach: Conceptualising User's Self-Efficacy in Phishing Threat Avoidance Behaviour. 2019 Cybersecurity and Cyberforensics Conference (CCC). :102—110.

Phishing attacks are prevalent and humans are central to this online identity theft attack, which aims to steal victims' sensitive and personal information such as username, password, and online banking details. There are many antiphishing tools developed to thwart against phishing attacks. Since humans are the weakest link in phishing, it is important to educate them to detect and avoid phishing attacks. One can argue self-efficacy is one of the most important determinants of individual's motivation in phishing threat avoidance behaviour, which has co-relation with knowledge. The proposed research endeavours on the user's self-efficacy in order to enhance the individual's phishing threat avoidance behaviour through their motivation. Using social cognitive theory, we explored that various knowledge attributes such as observational (vicarious) knowledge, heuristic knowledge and structural knowledge contributes immensely towards the individual's self-efficacy to enhance phishing threat prevention behaviour. A theoretical framework is then developed depicting the mechanism that links knowledge attributes, self-efficacy, threat avoidance motivation that leads to users' threat avoidance behaviour. Finally, a gaming prototype is designed incorporating the knowledge elements identified in this research that aimed to enhance individual's self-efficacy in phishing threat avoidance behaviour.

2020-03-09
Prabhakar, Kashish, Dutta, Kaushik, Jain, Rachana, Sharma, Mayank, Khatri, Sunil Kumar.  2019.  Securing Virtual Machines on Cloud through Game Theory Approach. 2019 Amity International Conference on Artificial Intelligence (AICAI). :859–863.

With the ever so growing boundaries for security in the cloud, it is necessary to develop ways to prevent from total cloud server failure. In this paper, we try to design a Game Strategy Block that sets up rules for security based on a tower defence game to secure the hypervisor from potential threats. We also try to define a utility function named the Virtual Machine Vitality Measure (VMVM) that could enlighten on the status of the virtual machines on the virtual environment.

2020-02-10
Carneiro, Lucas R., Delgado, Carla A.D.M., da Silva, João C.P..  2019.  Social Analysis of Game Agents: How Trust and Reputation can Improve Player Experience. 2019 8th Brazilian Conference on Intelligent Systems (BRACIS). :485–490.
Video games normally use Artificial Intelligence techniques to improve Non-Player Character (NPC) behavior, creating a more realistic experience for their players. However, rational behavior in general does not consider social interactions between player and bots. Because of that, a new framework for NPCs was proposed, which uses a social bias to mix the default strategy of finding the best possible plays to win with a analysis to decide if other players should be categorized as allies or foes. Trust and reputation models were used together to implement this demeanor. In this paper we discuss an implementation of this framework inside the game Settlers of Catan. New NPC agents are created to this implementation. We also analyze the results obtained from simulations among agents and players to conclude how the use of trust and reputation in NPCs can create a better gaming experience.
2018-12-10
Volz, V., Majchrzak, K., Preuss, M..  2018.  A Social Science-based Approach to Explanations for (Game) AI. 2018 IEEE Conference on Computational Intelligence and Games (CIG). :1–2.

The current AI revolution provides us with many new, but often very complex algorithmic systems. This complexity does not only limit understanding, but also acceptance of e.g. deep learning methods. In recent years, explainable AI (XAI) has been proposed as a remedy. However, this research is rarely supported by publications on explanations from social sciences. We suggest a bottom-up approach to explanations for (game) AI, by starting from a baseline definition of understandability informed by the concept of limited human working memory. We detail our approach and demonstrate its application to two games from the GVGAI framework. Finally, we discuss our vision of how additional concepts from social sciences can be integrated into our proposed approach and how the results can be generalised.

Zhu, J., Liapis, A., Risi, S., Bidarra, R., Youngblood, G. M..  2018.  Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation. 2018 IEEE Conference on Computational Intelligence and Games (CIG). :1–8.

Growing interest in eXplainable Artificial Intelligence (XAI) aims to make AI and machine learning more understandable to human users. However, most existing work focuses on new algorithms, and not on usability, practical interpretability and efficacy on real users. In this vision paper, we propose a new research area of eXplainable AI for Designers (XAID), specifically for game designers. By focusing on a specific user group, their needs and tasks, we propose a human-centered approach for facilitating game designers to co-create with AI/ML techniques through XAID. We illustrate our initial XAID framework through three use cases, which require an understanding both of the innate properties of the AI techniques and users' needs, and we identify key open challenges.

2018-12-03
Larsson, A., Ibrahim, O., Olsson, L., Laere, J. van.  2017.  Agent based simulation of a payment system for resilience assessments. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). :314–318.

We provide an agent based simulation model of the Swedish payment system. The simulation model is to be used to analyze the consequences of loss of functionality, or disruptions of the payment system for the food and fuel supply chains as well as the bank sector. We propose a gaming simulation approach, using a computer based role playing game, to explore the collaborative responses from the key actors, in order to evoke and facilitate collective resilience.

2018-11-19
Gharsallaoui, R., Hamdi, M., Kim, T..  2017.  A Novel Privacy Technique for Augmented Reality Cloud Gaming Based on Image Authentication. 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC). :252–257.

The evolution of cloud gaming systems is substantially the security requirements for computer games. Although online game development often utilizes artificial intelligence and human computer interaction, game developers and providers often do not pay much attention to security techniques. In cloud gaming, location-based games are augmented reality games which take the original principals of the game and applies them to the real world. In other terms, it uses the real world to impact the game experience. Because the execution of such games is distributed in cloud computing, users cannot be certain where their input and output data are managed. This introduces the possibility to input incorrect data in the exchange between the gamer's terminal and the gaming platform. In this context, we propose a new gaming concept for augmented reality and location-based games in order to solve the aforementioned cheating scenario problem. The merit of our approach is to establish an accurate and verifiable proof that the gamer reached the goal or found the target. The major novelty in our method is that it allows the gamer to submit an authenticated proof related to the game result without altering the privacy of positioning data.

2018-01-10
Holdsworth, J., Apeh, E..  2017.  An Effective Immersive Cyber Security Awareness Learning Platform for Businesses in the Hospitality Sector. 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW). :111–117.
The rapid digitalisation of the hospitality industry over recent years has brought forth many new points of attack for consideration. The hasty implementation of these systems has created a reality in which businesses are using the technical solutions, but employees have very little awareness when it comes to the threats and implications that they might present. This gap in awareness is further compounded by the existence of preestablished, often rigid, cultures that drive how hospitality businesses operate. Potential attackers are recognising this and the last two years have seen a huge increase in cyber-attacks within the sector.Attempts at addressing the increasing threats have taken the form of technical solutions such as encryption, access control, CCTV, etc. However, a high majority of security breaches can be directly attributed to human error. It is therefore necessary that measures for addressing the rising trend of cyber-attacks go beyond just providing technical solutions and make provision for educating employees about how to address the human elements of security. Inculcating security awareness amongst hospitality employees will provide a foundation upon which a culture of security can be created to promote the seamless and secured interaction of hotel users and technology.One way that the hospitality industry has tried to solve the awareness issue is through their current paper-based training. This is unengaging, expensive and presents limited ways to deploy, monitor and evaluate the impact and effectiveness of the content. This leads to cycles of constant training, making it very hard to initiate awareness, particularly within those on minimum waged, short-term job roles.This paper presents a structured approach for eliciting industry requirement for developing and implementing an immersive Cyber Security Awareness learning platform. It used a series of over 40 interviews and threat analysis of the hospitality industry to identify the requirements fo- designing and implementing cyber security program which encourage engagement through a cycle of reward and recognition. In particular, the need for the use of gamification elements to provide an engaging but gentle way of educating those with little or no desire to learn was identified and implemented. Also presented is a method for guiding and monitoring the impact of their employee's progress through the learning management system whilst monitoring the levels of engagement and positive impact the training is having on the business.
2017-12-28
Vu, Q. H., Ruta, D., Cen, L..  2017.  An ensemble model with hierarchical decomposition and aggregation for highly scalable and robust classification. 2017 Federated Conference on Computer Science and Information Systems (FedCSIS). :149–152.

This paper introduces an ensemble model that solves the binary classification problem by incorporating the basic Logistic Regression with the two recent advanced paradigms: extreme gradient boosted decision trees (xgboost) and deep learning. To obtain the best result when integrating sub-models, we introduce a solution to split and select sets of features for the sub-model training. In addition to the ensemble model, we propose a flexible robust and highly scalable new scheme for building a composite classifier that tries to simultaneously implement multiple layers of model decomposition and outputs aggregation to maximally reduce both bias and variance (spread) components of classification errors. We demonstrate the power of our ensemble model to solve the problem of predicting the outcome of Hearthstone, a turn-based computer game, based on game state information. Excellent predictive performance of our model has been acknowledged by the second place scored in the final ranking among 188 competing teams.

2017-05-18
Kohn, Josh, Rank, Stefan.  2016.  Evaluating Physical Movement As Trigger for Transitioning Between Environments in Virtual Reality. Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. :1973–1979.

Virtual reality allows users to experience unusual immersive environments. There are still several aspect of design for virtual reality that need more investigation, such as transitioning between environments. Multiple studies have shown that physical movement in a virtual environment supports immersion and presence. Our setup will allow the comparative study of the coupling of virtual camera movements with simultaneous physical movements of the user in terms of user preference and comfort. This work-in-progress uses a within-subject experimental design for evaluating interaction prototypes based on the Oculus Rift DK2 where participants will be tasked with transitioning between different environments; once using physical motion to merely trigger the transition and once with the virtual camera movement being coupled to the physical motion. Qualitative and quantitative data will be collected utilizing questionnaires and in-game metrics. Pretests of a similar setup were used to establish minimal levels of comfort.

2017-03-08
Dangra, B. S., Rajput, D., Bedekar, M. V., Panicker, S. S..  2015.  Profiling of automobile drivers using car games. 2015 International Conference on Pervasive Computing (ICPC). :1–5.

In this paper we use car games as a simulator for real automobiles, and generate driving logs that contain the vehicle data. This includes values for parameters like gear used, speed, left turns taken, right turns taken, accelerator, braking and so on. From these parameters we have derived some more additional parameters and analyzed them. As the input from automobile driver is only routine driving, no explicit feedback is required; hence there are more chances of being able to accurately profile the driver. Experimentation and analysis from this logged data shows possibility that driver profiling can be done from vehicle data. Since the profiles are unique, these can be further used for a wide range of applications and can successfully exhibit typical driving characteristics of each user.

2017-03-07
Aggarwal, P., Maqbool, Z., Grover, A., Pammi, V. S. C., Singh, S., Dutt, V..  2015.  Cyber security: A game-theoretic analysis of defender and attacker strategies in defacing-website games. 2015 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA). :1–8.

The rate at which cyber-attacks are increasing globally portrays a terrifying picture upfront. The main dynamics of such attacks could be studied in terms of the actions of attackers and defenders in a cyber-security game. However currently little research has taken place to study such interactions. In this paper we use behavioral game theory and try to investigate the role of certain actions taken by attackers and defenders in a simulated cyber-attack scenario of defacing a website. We choose a Reinforcement Learning (RL) model to represent a simulated attacker and a defender in a 2×4 cyber-security game where each of the 2 players could take up to 4 actions. A pair of model participants were computationally simulated across 1000 simulations where each pair played at most 30 rounds in the game. The goal of the attacker was to deface the website and the goal of the defender was to prevent the attacker from doing so. Our results show that the actions taken by both the attackers and defenders are a function of attention paid by these roles to their recently obtained outcomes. It was observed that if attacker pays more attention to recent outcomes then he is more likely to perform attack actions. We discuss the implication of our results on the evolution of dynamics between attackers and defenders in cyber-security games.

2015-05-06
Ravindran, K., Mukhopadhyay, S., Sidhanta, S., Sabbir, A..  2014.  Managing shared contexts in distributed multi-player game systems. Communication Systems and Networks (COMSNETS), 2014 Sixth International Conference on. :1-8.

In this paper, we consider the impact of a weaker model of eventual consistency on distributed multi-player games. This model is suitable for networks in which hosts can leave and join at anytime, e.g., in an intermittently connected environment. Such a consistency model is provided by the Secure Infrastructure for Networked Systems (SINS) [24], a reliable middleware framework. SINS allows agents to communicate asynchronously through a distributed transactional key-value store using anonymous publish-subscribe. It uses Lamport's Paxos protocol [17] to replicate state. We consider a multi-player maze game as example to illustrate our consistency model and the impact of network losses/delays therein. The framework based on SINS presented herein provides a vehicle for studying the effect of human elements participating in collaborative simulation of a physical world as in war games.

2015-05-05
Baughman, A.K., Chuang, W., Dixon, K.R., Benz, Z., Basilico, J..  2014.  DeepQA Jeopardy! Gamification: A Machine-Learning Perspective. Computational Intelligence and AI in Games, IEEE Transactions on. 6:55-66.

DeepQA is a large-scale natural language processing (NLP) question-and-answer system that responds across a breadth of structured and unstructured data, from hundreds of analytics that are combined with over 50 models, trained through machine learning. After the 2011 historic milestone of defeating the two best human players in the Jeopardy! game show, the technology behind IBM Watson, DeepQA, is undergoing gamification into real-world business problems. Gamifying a business domain for Watson is a composite of functional, content, and training adaptation for nongame play. During domain gamification for medical, financial, government, or any other business, each system change affects the machine-learning process. As opposed to the original Watson Jeopardy!, whose class distribution of positive-to-negative labels is 1:100, in adaptation the computed training instances, question-and-answer pairs transformed into true-false labels, result in a very low positive-to-negative ratio of 1:100 000. Such initial extreme class imbalance during domain gamification poses a big challenge for the Watson machine-learning pipelines. The combination of ingested corpus sets, question-and-answer pairs, configuration settings, and NLP algorithms contribute toward the challenging data state. We propose several data engineering techniques, such as answer key vetting and expansion, source ingestion, oversampling classes, and question set modifications to increase the computed true labels. In addition, algorithm engineering, such as an implementation of the Newton-Raphson logistic regression with a regularization term, relaxes the constraints of class imbalance during training adaptation. We conclude by empirically demonstrating that data and algorithm engineering are complementary and indispensable to overcome the challenges in this first Watson gamification for real-world business problems.

Sunny, S., Pavithran, V., Achuthan, K..  2014.  Synthesizing perception based on analysis of cyber attack environments. Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on. :2027-2030.

Analysing cyber attack environments yield tremendous insight into adversory behavior, their strategy and capabilities. Designing cyber intensive games that promote offensive and defensive activities to capture or protect assets assist in the understanding of cyber situational awareness. There exists tangible metrics to characterizing games such as CTFs to resolve the intensity and aggression of a cyber attack. This paper synthesizes the characteristics of InCTF (India CTF) and provides an understanding of the types of vulnerabilities that have the potential to cause significant damage by trained hackers. The two metrics i.e. toxicity and effectiveness and its relation to the final performance of each team is detailed in this context.
 

2015-05-04
Alsaleh, M.N., Al-Shaer, E.A..  2014.  Security configuration analytics using video games. Communications and Network Security (CNS), 2014 IEEE Conference on. :256-264.

Computing systems today have a large number of security configuration settings that enforce security properties. However, vulnerabilities and incorrect configuration increase the potential for attacks. Provable verification and simulation tools have been introduced to eliminate configuration conflicts and weaknesses, which can increase system robustness against attacks. Most of these tools require special knowledge in formal methods and precise specification for requirements in special languages, in addition to their excessive need for computing resources. Video games have been utilized by researchers to make educational software more attractive and engaging. Publishing these games for crowdsourcing can also stimulate competition between players and increase the game educational value. In this paper we introduce a game interface, called NetMaze, that represents the network configuration verification problem as a video game and allows for attack analysis. We aim to make the security analysis and hardening usable and accurately achievable, using the power of video games and the wisdom of crowdsourcing. Players can easily discover weaknesses in network configuration and investigate new attack scenarios. In addition, the gameplay scenarios can also be used to analyze and learn attack attribution considering human factors. In this paper, we present a provable mapping from the network configuration to 3D game objects.