A Method for Scoping Multi-Level Visibility of IoT Services in Enterprise Environments PROJECT TITLE : An Approach for Multi-Level Visibility Scoping of IoT Services in Enterprise Environments ABSTRACT: In the Internet of Things, it is necessary for a user's device (for example, a smartphone) to first discover what services are offered by nearby devices before the user can issue commands to access those services. Service visibility scoping in large-scale, heterogeneous enterprise environments has multiple features that set it apart from other types of scoping. These features include proximity-based interactions, differentiated visibility according to the natures of the device and the user, and frequent user churns that result in revocation. They render the solutions that are already in place completely insufficient. We propose Argus, a distributed algorithm that provides three different levels of fine-grained visibility scoping in parallel: I Level 1 public visibility, in which services are identically visible to everyone; ii) Level 2 differentiated visibility, in which service visibility depends on users' non-sensitive attributes; and iii) Level 3 covert visibility, in which service visibility depends on users' sensitive attributes that are never explicitly disclosed. Extensive research and testing have demonstrated the following: I Argus is a secure system; ii) its Level 2 is 10 times as scalable and computationally efficient as work using attribute-based encryption; iii) its Level 3 is 10 times as efficient as work using paring-based cryptography; iii) it is quick and agile for a satisfying user experience, requiring only 0.25 seconds to discover 20 level 1 devices, and 0.63 seconds for level 2 or level 3 devices Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest A Photo Crowdsourcing Framework Based on Edge Computing for Real-Time 3D Reconstruction A Stochastic ON-OFF Queueing Mobility Model for Software-Defined Vehicle Networks is analyzed.