user selection of clusters and classifiers in behavior based access control
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User Selection of Clusters and Classifiers in Behavior Based Access Control. BBAC uses statistical machine learning techniques (clustering and classification) to make predictions about the intent of actors establishing TCP connections and HTTP requests.

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user selection of clusters and classifiers in behavior based access control
User Selection of Clusters and Classifiers in Behavior Based Access Control

BBAC uses statistical machine learning techniques (clustering and classification) to make predictions about the intent of actors establishing TCP connections and HTTP requests.

We are currently trying to answer the following questions:

How to group similar behaviors?

How to detect suspicious behavior?

How to correct false positives?

How do administrators assign new actors to a behavioral group?

How to alert the administrator of suspicious behavior?

How do administrators select classifiers / set policy?

This work was sponsored by the Air Force Research Laboratory (AFRL). DISTRIBUTION A: Approved for public release; distribution unlimited (Case Number 88ABW-2013-1041)

New Training / Clustering Data

Training Data

Data Streams in

Train Classifiers

Cluster Roles

User traffic

Classification results

Admin Alerts

Suspicious clustering changes

Assigning new machines to cluster

Modifying classifier

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