基于大数据技术的高级威胁检测

IF 0.2 Q4 POLITICAL SCIENCE
Madhvaraj M. Shetty, D. Manjaiah
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引用次数: 1

摘要

今天,不断增加的网络威胁显然表明,目前的对策不足以防御它。借助巨大的生成数据,大数据为各行各业带来了变革潜力。虽然许多人将其用于更好的操作,但其中一些人注意到,它还可以通过提供更广泛的漏洞和风险视图来用于安全性。与此同时,深度学习通过提供预测分析解决方案而成为关键角色。深度学习和大数据分析正在成为数据科学的两大热点。威胁情报变得越来越有效。由于它是基于收集到的有关活动威胁的数据量,因此许多独立供应商结成了合作伙伴关系。在本章中,我们将探讨大数据和大数据分析及其好处。我们简要概述了深度分析,最后介绍了协作威胁检测。我们还对标准的一些方面和关键功能进行了探讨。最后,我们介绍了协作威胁检测的好处和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advanced Threat Detection Based on Big Data Technologies
Today constant increase in number of cyber threats apparently shows that current countermeasures are not enough to defend it. With the help of huge generated data, big data brings transformative potential for various sectors. While many are using it for better operations, some of them are noticing that it can also be used for security by providing broader view of vulnerabilities and risks. Meanwhile, deep learning is coming up as a key role by providing predictive analytics solutions. Deep learning and big data analytics are becoming two high-focus of data science. Threat intelligence becoming more and more effective. Since it is based on how much data collected about active threats, this reason has taken many independent vendors into partnerships. In this chapter, we explore big data and big data analytics with its benefits. And we provide a brief overview of deep analytics and finally we present collaborative threat Detection. We also investigate some aspects of standards and key functions of it. We conclude by presenting benefits and challenges of collaborative threat detection.
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来源期刊
CiteScore
1.80
自引率
40.00%
发文量
20
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