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Cross tenant access control model for cloud computingSharing of resources on the cloud can be achieved on a large scale since it is cost effective and location independent. Despite the hype surrounding cloud computing, organizations are still reluctant to deploy their businesses in the cloud computing environment due to concerns in secure resource sharing. In this paper, we propose a cloud resource mediation service offered by cloud service providers, which plays the role of trusted third party among its different tenants. This paper formally specifies the resource sharing mechanism between two different tenants in the presence of our proposed cloud resource mediation service. The correctness of permission activation and delegation mechanism among different tenants using four distinct algorithms (Activation, Delegation, Forward Revocation and Backward Revocation) is also demonstrated using formal verification. The performance analysis suggest that sharing of resources can be performed securely and efficiently across different tenants of the cloud.

Cross tenant access control model for cloud computing


  • Zhao et al. propose a cross-domain single sign on authentication protocol for cloud users, whose security was also proven mathematically. In the approach, the CSP is responsible for verifying the user’s identity and making access control decisions.
  • As computing resources are being shared between tenants and used in an on-demand manner, both known and zeroday system security vulnerabilities could be exploited by the attackers (e.g. using side-channel and timing attacks).
  • In existing, a fine grained data-level access control model (FDACM) designed to provide role-based and data-based access control for multi-tenant applications was presented. Relatively lightweight expressions were used to represent complex policy rules.


  • Traditional access control models, such as role based access control, are generally unable to adequately deal with cross-tenant resource access requests.
  • Specification level security is difficult to achieve at the user and provider ends.
  • The security of the approach was not provided.


  • We use model checking to exhaustively explore the system and verify the finite state concurrent systems. Specifically, we use High Level Petri Nets (HLPN) and Z language for the modeling and analysis of the CTAC model.
  • We present a CTAC model for collaboration, and the CRMS to facilitate resource sharing amongst various tenants and their users.
  • We also present four different algorithms in the CTAC model, namely: activation, delegation, forward revocation and backward revocation.
  • We then provide a detailed presentation of modeling, analysis and automated verification of the CTAC model using the Bounded Model Checking technique with SMTLIB and Z3 solver, in order to demonstrate the correctness and security of the CTAC model.


  • HLPN provides graphical and mathematical representations of the system, which facilitates the analysis of its reactions to a given input. Therefore, we are able to understand the links between different system entities and how information is processed.
  • We then verify the model by translating the HLPN using bounded model checking. For this purpose, we use Satisfiability Modulo Theories Library (SMT-Lib) and solver. We remark that such formal verification has previously been used to evaluate security protocols


System : Pentium Dual Core.
Hard Disk : 120 GB.
Monitor : 15” LED
Input Devices : Keyboard, Mouse
Ram : 1 GB


Operating system : Windows 7.
Coding Language : JAVA/J2EE
Tool : Netbeans 7.2.1
Database : MYSQL

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The passenger flow counting research of subway video based on image processing.

In view of the traditional transportation passenger flow statistics methods are rough statistics on passenger flow, and it can’t get statistical data of passenger flow in a certain period of time immediately, so the passenger flow counting method of subway video based on image processing is proposed. Firstly take the characters obtained by the background subtraction method in the video as the statistical target, and then extract of the human figure outline and do the morphology processing, finally use the method of the connected domain to achieve the statistical effect of the intelligent number. Experimental results show that, the number of statistics is very accurate.

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Study of Corona Activity using an Image Processing Approach

In the present work, behaviour of corona discharges on the polymeric insulating sample, generated from a multiple needle electrode in the presence of normal air and fog (mist) condition, is studied with the aid of an image processing technique. The development of streamers is closely monitored using the high-resolution digital single lens reflection camera. The corona streamers were found to be concentrated in the presence of fog whereas without the fog, streamers spread was wider. A physical model is proposed to explain the observed phenomenon. The obtained digital corona images are processed in the YCbCr color space to effectively extract corona generated plasma using color thresholding method. The streamer spread angle is then calculated by applying the Hough transform technique. The results indicate that streamer spread angle in the presence of fog to be approximately 60% lower than that without fog.

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Artificial intelligence in routing protocol :

The inclusion of artificial intelligence (AI) in routing protocol can improve the performance of routing protocols. Including artificial intelligence in a routing protocol using Software Defined Networks (SDN) is one of the most interesting research topic that is currently being investigated. Nowadays the application of AI over routing protocols is only applied to real devices, especially in wireless sensor nodes. In this paper, we present a new proposal to implement an intelligent routing protocol in a SDN topology. The intelligent routing protocol is based on the reinforcement learning process that allows choosing the best data transmission paths according to the best criteria and based on the network status.

Artificial intelligence in routing protocol


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Energy Profiling Tool for Smartphones

As the limited battery lifetime remains a major factor restricting the applicability of a smartphone, Energy Profiling Tool is trending area now, so significant research efforts have been devoted to understand the energy consumption in smartphones. Existing energy modelling methods can account energy drain in a fine-grained manner and provide well designed human-battery interfaces for users to characterise energy usage of every app in smartphones. However, in this paper, we demonstrate that there are still pitfalls in current Android energy modelling approaches, leaving collateral energy consumption unaccounted. The existence of collateral energy consumption becomes a serious energy bug. In particular, those energy bugs could be exploited to launch a new class of energy attacks, which deplete battery life and sidestep the supervision of current energy accounting. To unveil collateral energy bugs, we propose E-Android to accurately profile energy consumption of a smartphone in a comprehensive manner.


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