CRF Based Secured Framework for Filtering Malicious Traffic
Network security contains the provisions and policies adopted by a network administrator to prevent and monitor unauthorized access. It involves the authorization of access to data in a network. Filtering capabilities are available in access control lists (ACLs). It is typically stored in Ternary Content Addressable Memory (TCAM), whereas the size and cost of TCAM puts a limit on the number of filters, and this parallel access and reduces the number of lookups per forwarded is not expected to change in the near future. In this paper, the authors present a secured framework for filtering Malicious Traffic. This filtering framework is designed using CRF, where Conditional models are discriminative probabilistic systems that are used to model the conditional distribution over a set of random variables.