4 May 2018 The generative policy approach for dynamic collaboration in coalition environments
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Abstract
Coalition operations of the future will see an increased use of autonomous vehicles, mules and UAVs in different kinds of contexts. Because of the scalability and dynamicity of operations at the tactical edge, such vehicles along with the supporting infrastructure at base-camps and other forward operating bases would need to support an increased degree of autonomy. In this paper, we look at one specific scenario where a surveillance mission needs to be performed sharing resources borrowed from multiple coalition partners. In such an environment, experts who can define security and other types of policies for devices are hard to find. One way to address this problem is to use generative policies – an approach where the devices generate policies for their operations themselves without requiring human involvement as the configuration of the system changes. We show how access control policies can be created automatically by the different devices involved in the mission, with only high-level guidance provided by humans. The generative policy architecture can enable rapid reconfiguration of security policies needed to address dynamic changes from features such as auto-scaling. It can also support improved security in coalition contexts by enabling the solutions to use approaches like moving target defense. In this paper, we would discuss a general architecture which allows the generative policy approach to be used in many different situations, a simulation implementation of the architecture and lessons learnt from the implementation of the simulation.
Conference Presentation
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Dinesh Verma, Elisa Bertino, Seraphin Calo, Chris Williams, Chris Simpkin, "The generative policy approach for dynamic collaboration in coalition environments", Proc. SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 106350W (4 May 2018); doi: 10.1117/12.2303720; https://doi.org/10.1117/12.2303720
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