원문정보
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초록
영어
In this paper we consider the case where artificial neural network processing is securely
performed over the wireless sensor network. To do this, we point out major security threats
and countermeasures against them. Then, we revised Holenderski et al.’s decomposition
model to support secure computing. Moreover, we refine the original model to deal with some
boundary cases. The revised model shows that like the original model the horizontal
decomposition is better than the vertical decomposition and that the number of the allocated
lower neurons in each layer to each sensor node should be large for optimization.
목차
Abstract
1. Introduction
2. Summary of M. Holdenderski et al.’s work [4]
3. Security aspects in distributed learning of ANN in the sensor network
3.1. Classification of adversaries
4. Refinement of the M. Holdenderski et al.’s model
4.1. Refined version of M. Holdenderski et al.’s model
4.2. Security enhancement
5. Acknowledgment
6. Conclusion
7. Reference
1. Introduction
2. Summary of M. Holdenderski et al.’s work [4]
3. Security aspects in distributed learning of ANN in the sensor network
3.1. Classification of adversaries
4. Refinement of the M. Holdenderski et al.’s model
4.1. Refined version of M. Holdenderski et al.’s model
4.2. Security enhancement
5. Acknowledgment
6. Conclusion
7. Reference
저자정보
참고문헌
자료제공 : 네이버학술정보