Efficient Security Model for Pervasive Computing Using Multi-Layer Neural Network

At present, the internet of things has no standard system architecture. According to the requirements of universal sensing, reliable transmission, intelligent processing and the realization of human, human and the material, real-time communication between objects and things, the internet needs the open, hierarchical, extensible network architecture as the framework. The sensation equipment safe examination platform supports the platform through the open style scene examination to measure the equipment and provides the movement simulated environment, including each kind of movement and network environment and safety management center, turning on application gateway supports. It examines the knowledge library. Under this inspiration, this article proposes the novel security model based on the sparse neural network and wavelet analysis. The experiment indicates that the proposed model performs better compared with the other state-of-the-art algorithms.

Download Full-text

Deep Neural Network–Based Security Model for IoT Device Network

Deep Learning for Internet of Things Infrastructure ◽

10.1201/9781003032175-11 ◽

2021 ◽

pp. 223-243

Author(s):

Dukka Karun Kumar Reddy ◽

Janmenjoy Nayak ◽

Bighnaraj Naik ◽

G. M. Sai Pratyusha

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Security Model

Download Full-text

Safety Assessment of the General Overhead Traveling Crane Metal Structure Based on BP Neural Network

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.101-102.15 ◽

2011 ◽

Vol 101-102 ◽

pp. 15-20 ◽

Cited By ~ 1

Author(s):

Ge Ning Xu ◽

Qian Zhang

Keyword(s):

Neural Network ◽

Bp Neural Network ◽

Evaluation System ◽

Safety Assessment ◽

Safety Evaluation ◽

Metal Structure ◽

Assessment Model ◽

Security Model ◽

Network Training ◽

Training Samples

Safety assessment of bridge crane metal structure is widely needed. A general bridge safety assessment model of metal structure based on BP neural network is established. BP neural network is suitable for the problem that is not fully known and the adaptability of the dynamic system, and can facilitate the assignment and statistics of the safety evaluation system. Matlab7.0 software is used for the network training process. Through the training, samples to be tested were verified for the feasibility of the security model. The security model based on BP neural network for the general overhead traveling crane structure could provide a safety assessment and evaluation methods.

Download Full-text

SSRD+: A Privacy-aware Trust and Security Model for Resource Discovery in Pervasive Computing Environment

30th Annual International Computer Software and Applications Conference (COMPSAC'06) ◽

10.1109/compsac.2006.164 ◽

2006 ◽

Cited By ~ 4

Author(s):

Moushumi Sharmin ◽

Sheikh Ahamed ◽

Shameem Ahmed ◽

Haifeng Li

Keyword(s):

Pervasive Computing ◽

Resource Discovery ◽

Security Model ◽

Computing Environment

Download Full-text

Constructing Financial Information Security Model Based on PCA and Optimized BP Neural Network

IETE Journal of Research ◽

10.1080/03772063.2021.1978878 ◽

2021 ◽

pp. 1-7

Author(s):

Chu Zhang

Keyword(s):

Neural Network ◽

Information Security ◽

Bp Neural Network ◽

Financial Information ◽

Security Model ◽

Model Based

Download Full-text

Data Security Model Using Artificial Neural Networks and Database Fragmentation in Cloud Environment

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b3658.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 5972-5975

Keyword(s):

Neural Network ◽

Data Security ◽

Dynamic Environment ◽

Security Model ◽

Cloud Environment ◽

Secret Data ◽

Cloud Data ◽

The Neural Network ◽

Cloud Databases ◽

Artificial Neural

Data security is a one of the challenging issue in present scenario. In that one of the on demand service is cloud computing and it provides so many services for end users and also it provides a dynamic environment for end user to provide quality of services on data it leads to improve in the confidentiality of the data. The proposed work presents a new cloud data security model with the help of Artificial Neural Network. It improves the confidentiality and security in cloud environment. This proposed algorithm is implemented using dynamic hashing fragmented component. It is implemented for storing fragmented sensitive secret data. The neural network cryptographic proposed algorithm is used for data to deal with encryption process for secret and improve the confidentiality. This algorithm applied for various number of cloud databases and it shows high confidentiality on data security.

Download Full-text