Abstract
Intrusion detection system’s aim is to note malicious activities in a network. But it has to tackle many challenges against its goal. Intrusion detection is the action of detecting inapt, inexact, and abnormal activity in the network data. Network security is a major worry in large organization. Data integrity, secrecy, and ease of use must be conserved in order to make certain network security. In this paper, we consider the accuracy as the first issue and efficiency as the second issue using conditional random field and encrusted method. The proposed technique performs well than best-known methods such as naïve Bayes and Decision tree. The probe layer attacks stops network service. Remote to local (R2L), User to root (U2R) attacks and denial-of-service attacks (DOS) are widely known attacks that make impact on network assets. Improved attack detection efficiency can be obtained through CRF and high efficiency by implementing encrusted approach.
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