This effort researches the concerns many organizations have that prevents them from sharing their Big Data Assets considering the associated risks. We show how some of these concerns can be addressed by creating an alliance organizing and maintaining trust amongst members of a group that see a particular common benefit.
We also consider a number of Big Data Sharing infrastructure models, implementing alliance rules using a common digital marketplace to administer and enforce them. SURF Camera 1. SURF Camera 2. Demo's Trusted Big Data Sharing; Researching alliances and infrastructure models across multiple autonomous organizations booth Real-time transformations on a 3D mesh in booth DockerMon: Bring your own container booth DockerMon: Bring your own container - video.
SCinet NRE. SCInet SC16 network pdf. Trusted Big Data Sharing; Researching alliances and infrastructure models across multiple autonomous organizations.
See: slides. See: ABM Animation. See: poster. See: media advisory. Attendees can see how the network is able to identify the attack origin, the type of attack and use advanced software capabilities to respond and defend autonomously. In the SC16 demo [4] the visitor selects the attack type and its origin, the system will respond and defend against this attack autonomously. The response includes the use of security VNF's that are deployed using ExoGeni infrastructure when required for analysis or mitigation, the underlying Software Defined Network routes the attack traffic to the VNF for analysis or mitigation.
The demo showed how Network Function Virtualization and Software Defined Networks can be useful in attack mitigation and how they can be used effectively in setting up autonomous responses to higher layer attacks. Koning et al. See: demo video. See: demo StarNet version. Real-time transformations on a 3D mesh. During this demonstration we will show real-time transformations on a 3D mesh, initiated from the depth data of a Kinect sensor pointed towards the user in the SURF booth, in VR.
