面向地震大数据处理的Hadoop联合安全平台

Shiladitya Bhattacharjee, Lukman A. B. Rahim
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引用次数: 0

摘要

地震大数据勘探的重要性,特别是在油气行业,是不可或缺的。当数据量非常大时,对此类复杂数据的处理就显得尤为关键。如今,通过网络处理地震大数据非常普遍。因此,在不安全的通道上传输这些庞大的复杂数据时,其安全性同样重要。因此,任何一种安全算法在复杂大地震数据上的应用,在任何行业都是不现实的。为了解决这些问题,已经进行了大量的研究。然而,现有的相关研究尚未提出统一的解决方案。因此,本研究工作确定了一个独特的统一平台,使用Hadoop和Hive的集成进行并行处理和高级索引,以更快地执行大型复杂数据。同时,采用低复椭圆曲线加密(ECC),从数据保密性和完整性方面保证数据安全。结果表明,与其他安全组合相比,所提出的集成技术在产生更高吞吐量方面具有更高的时间效率。它进一步表明,它产生了低百分比的数据丢失和更高的熵值以及雪崩效应,这证明了它能够提供更高的数据机密性和完整性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hadoop Allied Security Platform for Seismic Big Data Processing
The importance of seismic big data exploration, especially in gas and oil industries, is indispensable. The processing of such complex data becomes more critical when its size is extremely large. These days the dispose of seismic big data over the network is notably common. Hence, the security of this huge complex data is equally important during its transportation over an insecure channel. Consequently, the application of any security algorithm on complex big seismic data makes it impractical for adopting it in any industry. Numerous researches have been conducted to resolve these issues. However, any unified solution has not been proclaimed by the exiting related studies. Therefore, this research work affirms a unique unified platform that uses the integration of Hadoop and Hive for parallel processing and advanced indexing for faster execution of large complex data. At the same time, it uses a low complex elliptic curve cryptography (ECC) to ensure data security in terms of data confidentiality and integrity. The result shows that the proposed integrated technique offers higher time efficiency in terms of producing higher Throughput than other security combinations. It further shows it produces a low percentage of Data Loss and higher Entropy Value as well as Avalanche Effect which justifies its ability to offer higher data confidentiality and integrity.
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