In real and virtual communities, complex and sophisticated forms of social interactions and cooperation are increasingly taking place between heterogeneous actors such as people, intelligent objects and virtual entities. At the same time, in such communities the risks of interacting with unreliable partners engaged in malicious activities increase. Therefore, it is important to provide all players with adequate information in order to allow them to choose the most reliable partner to interact with. In this context, we have focused our attention on colluding activities. In particular we propose a reputation method that preliminarily identifies those actors who most likely can be considered colluding players. This method does not introduce side effects to trust scores of honest actors while detecting colluding ones with high accuracy. A simple example supports our results.
Identifying Colluding Actors in Social Communities by Reputation Measures / Cotronei, Mariantonia; Giuffrè, Sofia; Marcianò, Attilio; Rosaci, Domenico; Sarnè, Giuseppe M. L.. - 1724:(2022), pp. 347-359. [10.1007/978-3-031-24801-6_25]
Identifying Colluding Actors in Social Communities by Reputation Measures
Cotronei, Mariantonia;Giuffrè, Sofia;Rosaci, Domenico;
2022-01-01
Abstract
In real and virtual communities, complex and sophisticated forms of social interactions and cooperation are increasingly taking place between heterogeneous actors such as people, intelligent objects and virtual entities. At the same time, in such communities the risks of interacting with unreliable partners engaged in malicious activities increase. Therefore, it is important to provide all players with adequate information in order to allow them to choose the most reliable partner to interact with. In this context, we have focused our attention on colluding activities. In particular we propose a reputation method that preliminarily identifies those actors who most likely can be considered colluding players. This method does not introduce side effects to trust scores of honest actors while detecting colluding ones with high accuracy. A simple example supports our results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.