A Target Classification Architectural Scheme for Secure Decision Making in Network Centric Environment with MPLS-VPN Architecture

Abstract

We present a new approach for military decision-making in a network centric environment in perspective of warfare information received from sensors of several networks geographically dispersed. Sensors used across various networks are different types, which generate data that need to be classified for target identification in real time. We also describe the network architecture and secure data communication using Multi Protocol Level Switching (MPLS)-Virtual Private Network (VPN) techniques that enables interoperability, convergence in diverse communication structures across land, air and sea to protect war assets and go offensive when required, which depends on effective communication, information assurance and information security across a challenging terrain and various theatres of battlefield arena. Our proposed network architecture and classification framework ensures packet level authentication that enables the network to restructure itself after a large scale or dedicated attack. It ensures scalability of the system as a whole. It is resilient to data corrupted by enemy’s countermeasures and can perform even if a sensor is jammed. Also, the diversity in the classifiers of our ensemble system allows different decision boundaries to be generated by using slightly different training parameters, such as different training datasets. The classification approach primarily applies to a single target or multiple targets that are separated sufficiently in space and/or time.

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