Network data analysis for security standard compliance

点击翻译按钮获取中文摘要

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.