Firewalls are the cornerstones of the security infrastructure for most enterprises. They have been widely deployed for protecting private networks. The quality of the protection provided by a firewall directly depends on the quality of its policy (i.e., configuration). Due to the lack of tools for analyzing firewall policies, many firewalls used today have policy errors. A firewall policy error either creates security holes that will allow malicious traffic to sneak into a private network or blocks legitimate traffic and disrupts normal business processes, which in turn could lead to irreparable, if not tragic, consequences. A major cause of policy errors are policy changes. Firewall policies often need to be changed as networks evolve and new threats emerge. Users behind a firewall often request the firewall administrator to modify rules to allow or protect the operation of some services. In this article, we first present the theory and algorithms for firewall policy change-impact analysis. Our algorithms take as input a firewall policy and a proposed change, then output the accurate impact of the change. Thus, a firewall administrator can verify a proposed change before committing it. We implemented our firewall change-impact analysis algorithms, and tested them on both real-life and synthetic firewall policies. The experimental results show that our algorithms are effective in terms of ensuring firewall policy correctness and efficient in terms of computing the impact of policy changes. Thus, our tool can be practically used in the iterative process of firewall policy design and maintenance. Although the focus of this article is on firewalls, the change-impact analysis algorithms proposed in this article are not limited to firewalls. Rather, they can be applied to other rule-based systems, such as router access control lists (ACLs), as well.
Similarly REF presents the theory and algorithm for firewall policy change impact analysis for addition, deletion, modification and swapping of the firewall rules.
Firewall policy change-impact analysis
TOIT
Computer Science