Modern distributed business applications are embedding an increasing degree of automation and dynamism, from dynamic offer-chain management, enterprise federations, and virtual collaborations to dynamic service interactions across organizations. Such dynamism ends up in new challenges in security and dependability. In Service-Oriented Architecture (SOA), collaborating services might belong to different security realms however typically need to be engaged dynamically at runtime. If a cross-realm authentication relationship can not be generated dynamically at runtime between heterogeneous security realms, it's technically difficult to enable dynamic business processes through secure collaborations between services. A potential solution to the current drawback is to generate a trust relationship across security realms therefore that a user can use the credential within the native security realm to obtain the credentials to access resources in a remote realm. However, the method of generating such types of trust relationships between two disjoint security realms is very advanced and time consuming, which could involve a large range of additional operations for credential conversion and require collaborations in multiple security realms. In this paper, we propose a new cross-realm authentication protocol for dynamic service interactions. This protocol will not need credential conversion or institution of authentication ways.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : A Novel Dynamic Model Capturing Spatial and Temporal Patterns for Facial Expression Analysis ABSTRACT: Incorporating spatial and temporal patterns present in facial behavior should substantially improve facial
PROJECT TITLE : Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images ABSTRACT: The use of kinetic modeling (KM) on a voxel level in dynamic PET pictures frequently results in large amounts of noise,
PROJECT TITLE : Robust Unsupervised Multi-view Feature Learning with Dynamic Graph ABSTRACT: By modeling the affinity associations with a graph to lower the dimension, graph-based multi-view feature learning algorithms learn a
PROJECT TITLE : Deep Tone Mapping Operator for High Dynamic Range Images ABSTRACT: The need for a rapid tone mapping operator (TMO) capable of adapting to a wide range of high dynamic range (HDR) content on low dynamic range (LDR)
PROJECT TITLE : Dynamic Scene Deblurring by Depth Guided Model ABSTRACT: Object movement, depth fluctuation, and camera shake are the most common causes of dynamic scene blur. For the most part, present approaches use picture

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry