Network data analysis for security standard compliance

网络数据分析以确保安全标准合规性

• 批准号: 477517-2015
• 负责人: Bertossi, Leopoldo
• 金额: $ 1.82万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=578949
• 关键词: Network; data; analysis; security; standard

Cyber-security standards enable organizations to practice safe security techniques to protect their information against cyber attacks. These standards provide a general and broad overview of information security but they usually include network security as a special practice. The standards require organizations to take proactive measures to detect network anomalies, attacks and other vulnerabilities that can cause harm to their sensitive information. Therefore, compliance to such network security standards is one of the greatest challenges faced by organizations today. In this research, we aim to design techniques to use different data sources (e.g. network packets obtained from traffic monitoring, log-files and system configuration) for cyber-security purposes, specifically for analyzing network security standard compliance. We start with the design and implementation of a well-organized data storage system for facilitating rapid data access. Then, we focus on different family of mathematical and analytical techniques such as graph-theoretical methods, machine learning and data-mining techniques to accurately characterize and measure the structure of the networks and to operate in massive amounts of data and distinguish between harmless anomalies and malicious attacks.

网络安全标准使组织能够实践安全的安全技术，以保护其信息免受网络攻击。这些标准提供了信息安全的一般和广泛的概述，但它们通常包括网络安全作为一个特殊的做法。这些标准要求组织采取积极主动的措施，以检测可能对其敏感信息造成损害的网络异常、攻击和其他漏洞。因此，遵守这些网络安全标准是当今组织面临的最大挑战之一。 在这项研究中，我们的目标是设计技术，使用不同的数据源（例如从流量监控，日志文件和系统配置获得的网络数据包）的网络安全目的，特别是分析网络安全标准的合规性。我们从设计和实现一个组织良好的数据存储系统，以促进快速的数据访问。然后，我们专注于不同的数学和分析技术，如图论方法，机器学习和数据挖掘技术，以准确地描述和测量网络的结构，并在大量数据中操作，并区分无害的异常和恶意攻击。