针对多设备多案例的数字取证调查的Cloudlet解决方案

Siyakha N. Mthunzi, E. Benkhelifa, Y. Jararweh, M. Al-Ayyoub
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引用次数: 4

摘要

多个设备所有权成倍地增加了数据的数量和种类,对数字取证调查产生了不利影响。几位作者提出了减少数据的方法,试图加强调查过程的数据采集和处理阶段。其他工作旨在利用云计算看似无限的资源来利用调查。然而,这种做法无意中影响了法医证据的可信度及其在法庭上的可采性,并降低了法医程序的效率。在本文中,我们提出了一种新颖的方法,通过专注于增加计算和延迟能力来利用当前进程。为了实现这一目标,我们提出了一种基于云的数字取证(DF)方法来补充现有的云计算系统。基于它们与终端设备和远程DF调查团队的接近性,我们提出的解决方案有效地解决了云替代方案所带来的低延迟挑战。此外,将cloudlet解决方案配置为数据计数器的唯一保管人,可确保调查人员保持对其数据的控制,从而可以维护全面的证据线索。最后,还提出了一种基于云的DF资源优化方法,以方便资源的上下扩展,以应对各种数据大小、多设备和并发多情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloudlet solution for digital forensic investigation of multiple cases of multiple devices
Multiple device ownership exponentially increases the volume and variety of data, with detrimental implications to digital forensic investigations. Several authors have proposed data reduction approaches in attempts to enhance the data acquisition and processing phases of the investigation process. Other works have aimed to take advantage of cloud computing's seemingly unlimited resources to leverage investigations. However, such approaches inadvertently affect the credibility of forensic evidence and its admissibility in a court of law, and degrade the efficiency of forensic processes. In this paper, we propose a novel approach which leverages current processes by focusing on augmenting computational and latency capabilities. To achieve this, we motivate a cloudlet-based digital forensic (DF) approach to complement existing cloud computing systems. Based on their proximity to end-devices and remote DF investigation teams, our proposed solution effectively tackles low latency challenges present with the cloud alternative. In addition, configuring the cloudlet solution as the sole custodian of data counters ensures that investigators remain in control of their data, and hence can maintain a comprehensive evidence trail. Finally, have also proposed a cloudlet-based DF resource optimization approach to facilitate upward and downward scaling of resources to cope with a variety of data sizes, multiple devices, and concurrent multiple cases.
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