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Identity and access management (IAM) system usually consist of predefined tasks as an information security system. Themain task is the authentication, since it is responsible for user identity proving for service providers that corporate with (IAM).This paper provides a review on intelligent authentication research applicable to IAM systems. These researches areevaluated according to the proposal of intelligent authentication key factors. Depending on this evaluation it could not be foundresearch implement an authentication that satisfies all these key factors.

Speaker recognition depends on specific predefined steps. The most important steps are feature extraction and features matching. In addition, the category of the speaker voice features has an impact on the recognition process. The proposed speaker recognition makes use of biometric (voice) attributes to recognize the identity of the speaker. The long-term features were used such that maximum frequency, pitch and zero crossing rate (ZCR).  In features matching step, the fuzzy inner product was used between feature vectors to compute the matching value between a claimed speaker voice utterance and test voice utterances. The experiments implemented using (ELSDSR) data set. These experiments showed that the recognition accuracy is 100% when using text dependent speaker recognition.