Identity authentication based on keystroke latencies
Communications of the ACM
ACM SIGSAC Review
Identity Theft
Recent worms: a survey and trends
Proceedings of the 2003 ACM workshop on Rapid malcode
Typing Patterns: A Key to User Identification
IEEE Security and Privacy
User re-authentication via mouse movements
Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security
Keystroke analysis of free text
ACM Transactions on Information and System Security (TISSEC)
A systematic classification of cheating in online games
NetGames '05 Proceedings of 4th ACM SIGCOMM workshop on Network and system support for games
A classification of biometric signatures
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Identifying MMORPG bots: a traffic analysis approach
Proceedings of the 2006 ACM SIGCHI international conference on Advances in computer entertainment technology
Game traffic analysis: an MMORPG perspective
Computer Networks: The International Journal of Computer and Telecommunications Networking
Clustering of online game users based on their trails using self-organizing map
ICEC'06 Proceedings of the 5th international conference on Entertainment Computing
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
Cybermetrics: user identification through network flow analysis
AIMS'10 Proceedings of the Mechanisms for autonomous management of networks and services, and 4th international conference on Autonomous infrastructure, management and security
Survey and research direction on online game security
Proceedings of the Workshop at SIGGRAPH Asia
Gender swapping and user behaviors in online social games
Proceedings of the 22nd international conference on World Wide Web
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
Account hijacking is considered one of the most serious security problems in online games. A hijacker normally takes away valuable virtual items from the stolen accounts, and trades those items for real money. Even though account hijacking is not uncommon, there is currently no general solutions to determine whether an account has been hijacked. The game company is not aware of a hijack unless it is reported by the victim. However, it is usually too late---usually a hijacker already took away anything valuable when a user finds that his/her account has been stolen. In this paper, we propose a new biometric for human identification based on users' game-play activities. Our main summary are two-fold: 1) we show that the idle time distribution is a representative feature of game players; 2) we propose the RET scheme, which is based on the KullbackLeibler divergence between idle time distributions, for user identification. Our evaluations shows that the RET scheme achieves higher than 90% accuracy with a 20-minute detection time given a 200-minute history size.