大数据环境下证据提取技术综述

S. H. Mokhtar, Gopinath Muruti, Z. Ibrahim, Fiza Abdul Rahim, Hairoladenan Kasim
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引用次数: 0

摘要

在数据量大、种类多、速度快的信息时代,需要一种新的技术来处理这些数据。公司不再依赖传统的工具和技术来满足和处理数据。不仅限于如何存储和处理数据,他们还希望获得数据的洞察力,以优化业务流程并获得更大的利润。为了满足这些需求,必须对大数据应用良好的分析方法,从这些数据集中提取价值和知识。虽然计算机工程师正在研究这部分,但这些有价值的数据也在其他地方被关注。在我们不知情的情况下,新的攻击和企图正在某些地方开发,以破坏数据的安全性、隐私性和完整性。本文旨在分析不同的分析方法和工具,这些方法和工具可以在可操作的时间内应用于大数据环境,同时提取入侵证据,以便将结果提交给适合数字取证过程的法庭。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Evidence Extraction Techniques in Big Data Environment
Today, information era where data is being generated at high in volume, variety, and velocity, a new technology is needed to cope with such data. Companies are no longer depends on the traditional tools and techniques to cater and handle data. Not only ending on how to store and process the data, they also wanted to gain insight of the data to optimize business process and gain a larger profit. To satisfy these requirements, a good analytic method must be applied to big data in order to extract value and knowledge from these data sets. While computer engineers are working on that part, this valuable data is also being eyed somewhere else. New attacks and attempts to taint the security, privacy, and integrity of the data are being developed somewhere without we knowing. This paper aims to analyze different analytics methods and tools, which can be applied in big data environment, in actionable time while at the same time extract evidence of intrusion in order for the results to be presented in a court of law fitting a digital forensic process.
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