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Recent years, online social networks (OSNs) are facing increasingly serious Sybil attack, which results in unexpected terrible impacts on social network services with illegal behaviors as manipulating online votes, publishing large amount of annoying advertises, etc. To detect Sybil account among ordinary users, several attributes and behavioral characteristics based detection algorithms were proposed,...
Feature selection is a hot topic in current information science, especially in the field of pattern recognition. In this paper, a combination feature selection Algorithm, ReGA, which merges the feature selection technique, ReliefF, into Genetic Algorithms Method, is presented. Experiments show that the new method improves the fitness of initial population, it can find the optimal solution more quickly,...
Intrusion detection based on System calls is a very important domain of anomaly detection, this paper firstly introduces the basic idea of Hidden Markov Model (HMM) based intrusion detection, and then expounds its current development with comparisons about the merits and shortcomings to the current mainstream technologies, by the way, presenting some further discussions upon the future direction of...
In this paper, we try to bring the concept of Ensemble into Outlier Detection. Two Outlier mining algorithms are ensembled: one based on similar coefficient sum and the other based on kernel density. An anomaly detection approach based on voting mechanism is proposed and applied into intrusion detection. We convert the character feature into numerical value by code mapping and use principal Components...
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