在Android中轻量级的加密勒索软件检测基于反应性蜂蜜文件监控
José A Gómez-Hernández1, Pedro García-Teodoro1
1Network Engineering & Security Group (NESG), School of Computer Science and Telecommunications Engineering (ETSIIT), C/Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain.
Sensors (Basel, Switzerland)
|May 11, 2024
概括
本研究介绍了Android设备的高效勒索软件检测工具,利用陷文件和反应式监控. 它为移动安全提供了高精度和高性能,克服了资源密集型机器学习方法的局限性.
科学领域:
- 网络安全和信息安全 网络安全和信息安全
- 移动设备安全 移动设备安全
- 恶意软件检测 恶意软件检测
背景情况:
- 勒索软件对全球个人和组织构成重大威胁.
- 移动和物联网设备越来越多地成为目标,需要定制的安全解决方案.
- 现有的基于机器学习的勒索软件缓解方案通常对移动平台来说过于资源密集.
研究的目的:
- 为Android平台开发一个有效和高效的勒索软件检测工具.
- 解决当前移动安全解决方案中高计算成本和资源消耗的局限性.
- 为移动操作系统适应先前开发的蜂蜜文件检测解决方案.
主要方法:
- 针对Android的勒索软件检测工具的实施.
- 在目标文件系统中战略部署陷文件.
- 使用FileObserver服务来早期检测可疑的文件访问模式.
主要成果:
- 开发的工具在Android设备上显示了针对勒索软件的高检测准确度.
- 该解决方案在资源消耗和性能方面表现出显著的效率.
- 实验结果验证了陷文件和反应性监测方法的有效性.
结论:
- 提议的勒索软件检测方法对于资源有限的Android环境是可行的和实用的.
- 将陷文件与反应式监控相结合,为计算上昂贵的机器学习模型提供了可行的替代方案.
- 这种方法增强了移动安全,防止勒索软件日益增长的威胁.
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