大数据网络安全分析系统架构策略研究综述
Architectural Tactics for Big Data Cybersecurity Analytic Systems: A Review
摘要：
内容：大数据网络安全分析旨在通过使用大数据工具和技术分析安全事件数据来保护网络，计算机和数据免受未经授权的访问。虽然文献中已经报道了大量的大数据网络安全分析系统，但缺乏从架构角度对文献进行系统和全面的审查。目的：本文报告了一项系统性综述，旨在确定大数据网络安全分析系统最常报告的质量属性和架构策略。方法：采用系统性文献综述（SLR）方法，对74篇按照明确标准筛选的原始文献进行综述。结果如下：我们的发现有两个方面：（i）确定12个最常报告的质量属性，并说明其对大数据网络安全分析系统的重要性;（ii）确定和编纂17个架构策略，以解决通常与大数据网络安全分析系统相关的质量属性。确定的策略包括六个性能策略，四个准确性策略，两个可扩展性策略，三个可靠性策略，以及一个安全性和可用性策略。结论：我们的研究结果表明，（a）尽管互操作性、可修改性、适应性、通用性、隐蔽性和隐私保证很重要，这些质量属性在文献中缺乏明确的架构支持（b）需要进行实证调查，以评估编纂的架构策略的影响（c）应投入大量的研究工作来探索该行业-（d）学术界和工业界之间普遍缺乏有效的合作，以支持大数据网络安全分析系统领域。
英文摘要：
Context: Big Data Cybersecurity Analytics is aimed at protecting networks, computers, and data from unauthorized access by analysing security event data using big data tools and technologies. Whilst a plethora of Big Data Cybersecurity Analytic Systems have been reported in the literature, there is a lack of a systematic and comprehensive review of the literature from an architectural perspective. Objective: This paper reports a systematic review aimed at identifying the most frequently reported quality attributes and architectural tactics for Big Data Cybersecurity Analytic Systems. Method: We used Systematic Literature Review (SLR) method for reviewing 74 primary studies selected using well-defined criteria. Results: Our findings are twofold: (i) identification of 12 most frequently reported quality attributes and the justification for their significance for Big Data Cybersecurity Analytic Systems; and (ii) identification and codification of 17 architectural tactics for addressing the quality attributes that are commonly associated with Big Data Cybersecurity Analytic systems. The identified tactics include six performance tactics, four accuracy tactics, two scalability tactics, three reliability tactics, and one security and usability tactic each. Conclusion: Our findings have revealed that (a) despite the significance of interoperability, modifiability, adaptability, generality, stealthiness, and privacy assurance, these quality attributes lack explicit architectural support in the literature (b) empirical investigation is required to evaluate the impact of codified architectural tactics (c) a good deal of research effort should be invested to explore the trade-offs and dependencies among the identified tactics and (d) there is a general lack of effective collaboration between academia and industry for supporting the field of Big Data Cybersecurity Analytic Systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
