The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform

Deying Li - One of the best experts on this subject based on the ideXlab platform.

  • MSN - A Low Computational Complexity Authentication Scheme in Underwater Wireless Sensor Network
    2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2015
    Co-Authors: Chi Yuan, Wenping Chen, Deying Li
    Abstract:

    Underwater Wireless Sensor Networks (UWSNs) are vulnerable to attack because of the broadcast nature of the transmission. The sensor nodes in UWSN are highly constrained in terms of computational capabilities and communication bandwidth. Authentication schemes for ground WSNs might not be applicable for UWSNs due to their less computation and communication capacity. Thus, it is necessary to design special schemes tailored to underwater environments. In this paper, a low computational complexity authentication scheme is proposed. By using Vandermonde Matrix, we replace the Matrix multiplication by Matrix Addition to greatly reduce the computation overhead. Moreover, our scheme is self-correctable and irreversible which further enhances the security of the UWSNs. Experiment results indicate our algorithm has advantages in energy and time consumption over traditional RSA and Blom's scheme.

  • A Low Computational Complexity Authentication Scheme in Underwater Wireless Sensor Network
    2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2015
    Co-Authors: Chi Yuan, Wenping Chen, Deying Li
    Abstract:

    Underwater Wireless Sensor Networks (UWSNs) are vulnerable to attack because of the broadcast nature of the transmission. The sensor nodes in UWSN are highly constrained in terms of computational capabilities and communication bandwidth. Authentication schemes for ground WSNs might not be applicable for UWSNs due to their less computation and communication capacity. Thus, it is necessary to design special schemes tailored to underwater environments. In this paper, a low computational complexity authentication scheme is proposed. By using Vandermonde Matrix, we replace the Matrix multiplication by Matrix Addition to greatly reduce the computation overhead. Moreover, our scheme is self-correctable and irreversible which further enhances the security of the UWSNs. Experiment results indicate our algorithm has advantages in energy and time consumption over traditional RSA and Blom's scheme.

Makan Fardad - One of the best experts on this subject based on the ideXlab platform.

Chi Yuan - One of the best experts on this subject based on the ideXlab platform.

  • MSN - A Low Computational Complexity Authentication Scheme in Underwater Wireless Sensor Network
    2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2015
    Co-Authors: Chi Yuan, Wenping Chen, Deying Li
    Abstract:

    Underwater Wireless Sensor Networks (UWSNs) are vulnerable to attack because of the broadcast nature of the transmission. The sensor nodes in UWSN are highly constrained in terms of computational capabilities and communication bandwidth. Authentication schemes for ground WSNs might not be applicable for UWSNs due to their less computation and communication capacity. Thus, it is necessary to design special schemes tailored to underwater environments. In this paper, a low computational complexity authentication scheme is proposed. By using Vandermonde Matrix, we replace the Matrix multiplication by Matrix Addition to greatly reduce the computation overhead. Moreover, our scheme is self-correctable and irreversible which further enhances the security of the UWSNs. Experiment results indicate our algorithm has advantages in energy and time consumption over traditional RSA and Blom's scheme.

  • A Low Computational Complexity Authentication Scheme in Underwater Wireless Sensor Network
    2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2015
    Co-Authors: Chi Yuan, Wenping Chen, Deying Li
    Abstract:

    Underwater Wireless Sensor Networks (UWSNs) are vulnerable to attack because of the broadcast nature of the transmission. The sensor nodes in UWSN are highly constrained in terms of computational capabilities and communication bandwidth. Authentication schemes for ground WSNs might not be applicable for UWSNs due to their less computation and communication capacity. Thus, it is necessary to design special schemes tailored to underwater environments. In this paper, a low computational complexity authentication scheme is proposed. By using Vandermonde Matrix, we replace the Matrix multiplication by Matrix Addition to greatly reduce the computation overhead. Moreover, our scheme is self-correctable and irreversible which further enhances the security of the UWSNs. Experiment results indicate our algorithm has advantages in energy and time consumption over traditional RSA and Blom's scheme.

Snigdhansu Chatterje - One of the best experts on this subject based on the ideXlab platform.

  • probabilistic Matrix Addition
    International Conference on Machine Learning, 2011
    Co-Authors: Amrudin Agovic, Arindam Banerjee, Snigdhansu Chatterje
    Abstract:

    We introduce Probabilistic Matrix Addition (PMA) for modeling real-valued data matrices by simultaneously capturing covariance structure among rows and among columns. PMA additively combines two latent matrices drawn from two Gaussian Processes respectively over rows and columns. The resulting joint distribution over the observed Matrix does not factorize over entries, rows, or columns, and can thus capture intricate dependencies in the Matrix. Exact inference in PMA is possible, but involves inversion of large matrices, and can be computationally prohibitive. Efficient approximate inference is possible due to the sparse dependency structure among latent variables. We propose two families of approximate inference algorithms for PMA based on Gibbs sampling and MAP inference. We demonstrate the effectiveness of PMA for missing value prediction and multi-label classification problems.

  • ICML - Probabilistic Matrix Addition
    2011
    Co-Authors: Amrudin Agovic, Arindam Banerjee, Snigdhansu Chatterje
    Abstract:

    We introduce Probabilistic Matrix Addition (PMA) for modeling real-valued data matrices by simultaneously capturing covariance structure among rows and among columns. PMA additively combines two latent matrices drawn from two Gaussian Processes respectively over rows and columns. The resulting joint distribution over the observed Matrix does not factorize over entries, rows, or columns, and can thus capture intricate dependencies in the Matrix. Exact inference in PMA is possible, but involves inversion of large matrices, and can be computationally prohibitive. Efficient approximate inference is possible due to the sparse dependency structure among latent variables. We propose two families of approximate inference algorithms for PMA based on Gibbs sampling and MAP inference. We demonstrate the effectiveness of PMA for missing value prediction and multi-label classification problems.

Wenping Chen - One of the best experts on this subject based on the ideXlab platform.

  • MSN - A Low Computational Complexity Authentication Scheme in Underwater Wireless Sensor Network
    2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2015
    Co-Authors: Chi Yuan, Wenping Chen, Deying Li
    Abstract:

    Underwater Wireless Sensor Networks (UWSNs) are vulnerable to attack because of the broadcast nature of the transmission. The sensor nodes in UWSN are highly constrained in terms of computational capabilities and communication bandwidth. Authentication schemes for ground WSNs might not be applicable for UWSNs due to their less computation and communication capacity. Thus, it is necessary to design special schemes tailored to underwater environments. In this paper, a low computational complexity authentication scheme is proposed. By using Vandermonde Matrix, we replace the Matrix multiplication by Matrix Addition to greatly reduce the computation overhead. Moreover, our scheme is self-correctable and irreversible which further enhances the security of the UWSNs. Experiment results indicate our algorithm has advantages in energy and time consumption over traditional RSA and Blom's scheme.

  • A Low Computational Complexity Authentication Scheme in Underwater Wireless Sensor Network
    2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN), 2015
    Co-Authors: Chi Yuan, Wenping Chen, Deying Li
    Abstract:

    Underwater Wireless Sensor Networks (UWSNs) are vulnerable to attack because of the broadcast nature of the transmission. The sensor nodes in UWSN are highly constrained in terms of computational capabilities and communication bandwidth. Authentication schemes for ground WSNs might not be applicable for UWSNs due to their less computation and communication capacity. Thus, it is necessary to design special schemes tailored to underwater environments. In this paper, a low computational complexity authentication scheme is proposed. By using Vandermonde Matrix, we replace the Matrix multiplication by Matrix Addition to greatly reduce the computation overhead. Moreover, our scheme is self-correctable and irreversible which further enhances the security of the UWSNs. Experiment results indicate our algorithm has advantages in energy and time consumption over traditional RSA and Blom's scheme.