基于异质源的随机数生成 多传感器网络中的融合
Jinxin Zhang1,2, Meng Wu3
1Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223000, China.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
这项研究引入了一种新的方法,用于为传感器网络安全生成高质量的随机数字. 通过融合混乱电路和环境意识,它增强了密钥生成和保护数据隐私.
科学领域:
- 网络安全 网络安全
- 信息系统信息系统信息系统
- 传感器网络 传感器网络
背景情况:
- 信息系统的安全性在很大程度上依赖于强大的密钥系统.
- 大规模异质传感器网络中的低质量密钥危及数据安全和用户隐私.
- 高质量的随机数字对于生成不可预测和安全的密钥至关重要.
研究的目的:
- 为满足在多传感器网络安全中对高质量的随机数字的需求.
- 为池提出一个新的设计,以提高随机数生成.
- 提高传感器网络的安全基础.
主要方法:
- 开发了用于池建设的新设计方法.
- 融合混沌电路与环境意识,用于源.
- 在传感器网络中分析了潜在的随机源事件.
- 利用传感器设备意识技术来提取真正的随机事件.
主要成果:
- 设计了一个高质量的池建设方案.
- 实现了高质量的源的异质融合.
- 与传统的随机池设计相比,证明了更高的性能.
- 满足了随机源的数量需求.
结论:
- 拟议的方案显著提高了源的质量.
- 这种方法确保了多传感器网络的强大安全基础.
- 它有效地解决了在复杂的传感器环境中随机数生成的挑战.
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