The Experts below are selected from a list of 21351 Experts worldwide ranked by ideXlab platform

Kenneth Van Surksum - One of the best experts on this subject based on the ideXlab platform.

Pei-song Shen - One of the best experts on this subject based on the ideXlab platform.

  • A Real-time Security Situation Assessment System Designed for Cloud Platform
    DEStech Transactions on Computer Science and Engineering, 2017
    Co-Authors: Wang Zhenling, Rui Xue, Chi Chen, Pei-song Shen
    Abstract:

    Security situation assessment is an effective way to analyze the situation of Cloud Platform, which helps administrator understand the current Cloud Platform security status and develop policies to reduce risks in time. However, the existing researches for security situation assessment mostly focus on network security situation assessment. The proposed methods for network are not so suitable for Cloud Platform. For the first time, we propose a security situation assessment system for Cloud Platform. In consideration of diversity, heterogeneous, multi-source of data in Cloud Platform security assessment, we use the Cloud computing security indicator system to construct a multi-source heterogeneous data fusion method which is used to assess the situation of Cloud Platform. In detail, we utilize big data processing tools and real-time data processing tools to transform the multi-source and heterogeneous data of Cloud Platform into the situational indicators of each protection level, which are further used to calculate the overall security situation in real time. The accuracy and practicability of the security situation assessment system are verified on real-word Cloud Platform in our experiments.

Chao Yan - One of the best experts on this subject based on the ideXlab platform.

  • CGC - A Selection Strategy Supporting Service Outsourcing in Cloud Platform
    2012 Second International Conference on Cloud and Green Computing, 2012
    Co-Authors: Chao Yan
    Abstract:

    As a natural evolution of Services Computing, Cloud Computing has provided a promising way, for delivering flexible and cheap computing resources, via Cloud Platform. However, the computing resources held by a Cloud Platform are usually limited, compared with the nearly unlimited resource requirements from various end users. In this situation, seeking for the appropriate computing resources from the outer Cloud Platform, i.e., outsourced resources, has become a promising remedy for Cloud Platform with limited computing resources. While the outsourced resources are usually of diverse sources, various service quality levels, and different structures, which bring a big challenge for the selection of outsourced resources. In view of this challenge, a selection strategy, named OS34CP (Outsourced Service Selection Strategy for Cloud Platform, OS34CP), is provided to help the service outsourcing process, in Cloud Platform. Finally, related work and comparison analysis are also made, to demonstrate the advantages of OS34CP, for dealing with the service outsourcing problem in Cloud Platform.

Yugang Wang - One of the best experts on this subject based on the ideXlab platform.

  • A Novel Cloud Platform for Service Robots
    IEEE Access, 2019
    Co-Authors: Fengyu Zhou, Yugang Wang
    Abstract:

    With the development of computer technology and artificial intelligence (AI), service robots are widely used in our daily life. While the manufacturing cost of the robots is too expensive for most small technology companies. The biggest technical limitations are the design of the robot service and the resources sharing of the robot groups. As far as we know, there is no complete and open-source service robot Cloud service Platform. To solve the above problems, in this paper, a novel robot Cloud Platform called Cloud robotics intelligent Cloud Platform (CRICP) is designed, which consists of gateway layer, an interface layer, service pool, and algorithm layer. Gateway layer mainly solves the problem of robot access control and service invocation requests scheduling. In addition, a standardized access method is proposed to overcome the problem that heterogeneous service robots cannot access the Cloud Platform. Interface layer is responsible for protocol injection, including motoring protocol, a management protocol, and other algorithms invocation protocol or service invocation interfaces protocol. Service Pool consists of different kinds of robot services which could scale based on the historical data analysis. In Algorithm layer, we can implement machine learning (ML) algorithm, deep learning (DL) algorithm, distributed algorithm, and so on. Finally, voice recognition service invocation experiment and Cloud service dynamic scaling test are taken as an example to verify the availability and accuracy of our Platform. Moreover, the compared results with a local framework and SOA also verifies the superiority of our Platform.

Rogério De Lemos - One of the best experts on this subject based on the ideXlab platform.

  • Self-adaptive authorisation in OpenStack Cloud Platform
    Journal of Internet Services and Applications, 2018
    Co-Authors: Carlos Eduardo Da Silva, Thomás Diniz, Nelio Cacho, Rogério De Lemos
    Abstract:

    Although major advances have been made in protection of Cloud Platforms against malicious attacks, little has been done regarding the protection of these Platforms against insider threats. This paper looks into this challenge by introducing self-adaptation as a mechanism to handle insider threats in Cloud Platforms, and this will be demonstrated in the context of OpenStack. OpenStack is a popular Cloud Platform that relies on Keystone, its identity management component, for controlling access to its resources. The use of self-adaptation for handling insider threats has been motivated by the fact that self-adaptation has been shown to be quite effective in dealing with uncertainty in a wide range of applications. Insider threats have become a major cause for concern since legitimate, though malicious, users might have access, in case of theft, to a large amount of information. The key contribution of this paper is the definition of an architectural solution that incorporates self-adaptation into OpenStack Keystone in order to handle insider threats. For that, we have identified and analysed several insider threats scenarios in the context of the OpenStack Cloud Platform, and have developed a prototype that was used for experimenting and evaluating the impact of these scenarios upon the self-adaptive authorisation system for the Cloud Platforms.