Quantitative Security Risk Assessment of Enterprise Networks [electronic resource] /
Ou, Xinming.author.
Singhal, Anoop.author.
Protection of enterprise networks from malicious intrusions is critical to the economy and security of our nation. This article gives an overview of the techniques and challenges for security risk analysis of enterprise networks. A standard model for security analysis will enable us to answer questions such as "are we more secure than yesterday" or "how does the security of one network configuration compare with another one". In this article, we will present a methodology for quantitative security risk analysis that is based on the model of attack graphs and the Common Vulnerability Scoring System (CVSS). Our techniques analyze all attack paths through a network, for an attacker to reach certain goal(s).
Description based upon print version of record.
Includes bibliographical references.
The Need for Quantifying Security -- Attack Graph Techniques -- The Common Vulnerability Scoring System (CVSS) -- Security Risk Analysis of Enterprise Networks Using Attack Graphs -- Conclusion.
Protection of enterprise networks from malicious intrusions is critical to the economy and security of our nation. This article gives an overview of the techniques and challenges for security risk analysis of enterprise networks. A standard model for security analysis will enable us to answer questions such as "are we more secure than yesterday" or "how does the security of one network configuration compare with another one". In this article, we will present a methodology for quantitative security risk analysis that is based on the model of attack graphs and the Common Vulnerability Scoring System (CVSS). Our techniques analyze all attack paths through a network, for an attacker to reach certain goal(s).
Computer security.
Computer communication systems.
Computer software-Reusability.
Computer system failures.
Systems and Data Security.
Computer Communication Networks.
Performance and Reliability.
System Performance and Evaluation.
SpringerBriefs in Computer Science