MINDPRES:一个混合原型系统,用于移动云用户层的全面数据保护
Noah Oghenefego Ogwara1, Krassie Petrova1, Mee Loong Bobby Yang1
1Department of Computer and Information Sciences, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, City Campus, Auckland 1010, New Zealand.
Sensors (Basel, Switzerland)
|February 13, 2025
概括
本研究介绍了MINDPRESS,该系统使用机器学习 (ML) 和随机方法来保护Android移动设备 (MDs) 在移动云计算 (MCC) 中. 它提供有效的,可扩展的安全性,而不会过载设备.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 移动计算 移动计算
背景情况:
- 移动云计算 (MCC) 为移动设备 (MD) 用户提供服务.
- 受损的MD对用户和其他MCC客户构成风险.
- 现有的安全措施需要加强分布式MCC环境.
研究的目的:
- 探索机器学习 (ML) 模型和随机方法,以确保MCC中的Android MD.
- 为分布式安全开发和验证一个原型系统 (MINDPRESS).
- 评估拟议的安全框架的可行性,可扩展性和性能.
主要方法:
- 开发了MINDPRESS,这是一个具有静态和混合组件的原型.
- 静态组件:基于设备的ML用于应用程序风险评估和基于云的随机风险评估.
- 混合组件:使用ML模型作为入侵检测和预防系统 (IDPS) 的实时应用程序行为监控.
主要成果:
- MINDPRESS展示了准确的静态和混合风险评估,与最近的研究可比.
- 绩效评估证实了拟议框架的可行性和可扩展性.
- 电力消耗分析显示,MINDPRESS在不导致设备过载的情况下运行.
结论:
- MINDPRESS提供了一个可行的和可扩展的框架来保护MCC中的数据和设备.
- 机器学习和随机方法的整合为移动云环境提供了强大的安全性.
- 这项研究有助于为移动云用户开发分布式安全系统.
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