Distributed Security Policy Analysis

Christian Pitscheider, Prof. Antonio Lioy
Computer networks have become an important part of modern society, and computer network security is crucial for their correct and continuous operation. The security aspects of computer networks are defined by network security policies. The term policy, in general, is defined as "a definite goal, course or method of action to guide and determine present and future decisions" [1] . In the context of computer networks, a policy is "a set of rules to administer, manage, and control access to
more » ... resources" [2] . Network security policies are enforced by special network appliances, so called security controls. Different types of security policies are enforced by different types of security controls. Network security policies are hard to manage, and errors are quite common. The problem exists because network administrators do not have a good overview of the network, the defined policies and the interaction between them. Researchers have proposed different techniques for network security policy analysis, which aim to identify errors within policies so that administrators can correct them. There are three different solution approaches: anomaly analysis, reachability analysis and policy comparison. Anomaly analysis searches for potential semantic errors within policy rules, and can also be used to identify possible policy optimizations. Reachability analysis evaluates allowed communication within a computer network and can determine if a certain host can reach a service or a set of services. Policy comparison compares two or more network security policies and represents the differences between them in an intuitive way. Although research in this field has been carried out for over a decade, there is still no clear answer on how to reduce policy errors. The different analysis techniques have their pros and cons, but none of them is a sufficient solution. More precisely, they are mainly complements to each other, as one analysis technique finds policy errors which remain unknown to another. Therefore, to be able to have a complete analysis of the computer network, multiple models must be instantiated. An analysis model that can perform all types of analysis techniques is desirable and has three main advantages. Firstly, the model can cover the greatest number of possible policy errors. Secondly, the computational overhead of instantiating the model is required II only once. Thirdly, research effort is reduced because improvements and extensions to the model are applied to all three analysis types at the same time. Fourthly, new algorithms can be evaluated by comparing their performance directly to each other. This work proposes a new analysis model which is capable of performing all three analysis techniques. Security policies and the network topology are represented by the so-called Geometric-Model. The Geometric-Model is a formal model based on the set theory and geometric interpretation of policy rules. Policy rules are defined according to the condition-action format: if the condition holds then the action is applied. A security policy is expressed as a set of rules, a resolution strategy which selects the action when more than one rule applies, external data used by the resolution strategy and a default action in case no rule applies. This work also introduces the concept of Equivalent-Policy, which is calculated on the network topology and the policies involved. All analysis techniques are performed on it with a much higher performance. A precomputation phase is required for two reasons. Firstly, security policies which modify the traffic must be transformed to gain linear behaviour. Secondly, there are much fewer rules required to represent the global behaviour of a set of policies than the sum of the rules in the involved policies. The analysis model can handle the most common security policies and is designed to be extensible for future security policy types. As already mentioned the Geometric-Model can represent all types of security policies, but the calculation of the Equivalent-Policy has some small dependencies on the details of different policy types. Therefore, the computation of the Equivalent-Policy must be tweaked to support new types. Since the model and the computation of the Equivalent-Policy was designed to be extendible, the effort required to introduce a new security policy type is minimal. The anomaly analysis can be performed on computer networks containing different security policies. The policy comparison can perform an Implementation-verification among high-level security requirements and an entire computer network containing different security policies. The policy comparison can perform a Change-impact-analysis of an entire network containing different security policies. The proposed model is implemented in a working prototype, and a performance evaluation has been performed. The performance of the implementation is more than sufficient for real scenarios. Although the calculation of the Equivalent-Policy requires a significant amount of time, it is still manageable and is required only once. The execution of the different analysis techniques is fast, and generally the results are calculated in real time. The implementation also exposes an API for future integration in different frameworks or software packages. Based on the API, a complete tool was implemented, with a graphical user interface and additional features.
doi:10.6092/polito/porto/2644186 fatcat:56mh3ubu4bfjjoxqtphnpfvyaq