Modern data center networks require efficient and scalable security analysis approaches that can analyze the relationship between the vulnerabilities. Utilizing the Attack Representation Methods (ARMs) and Attack Graphs (AGs) enables the security administrator to understand the cloud network’s current security situation at the low-level. However, the AG approach suffers from scalability challenges. It relies on the connectivity between the services and the vulnerabilities associated with the services to allow the system administrator to realize its security state. In addition, the security policies created by the administrator can have conflicts among them, which is often detected in the data plane of the Software Defined Networking (SDN) system. Such conflicts can cause security breaches and increase the flow rules processing delay. This dissertation addresses these challenges with novel solutions to tackle the scalability issue of Attack Graphs and detect security policy conflictsin the application plane before they are transmitted into the data plane for final installation. Specifically, it introduces a segmentation-based scalable security state (S3) framework for the cloud network. This framework utilizes the well-known divide-and-conquer approach to divide the large network region into smaller, manageable segments. It follows a well-known segmentation approach derived from the K-means clustering algorithm to partition the system into segments based on the similarity between the services. Furthermore, the dissertation presents unified intent rules that abstract the network administration from the underlying network controller’s format. It develops a networking service solution to use a bounded formal model for network service compliance checking that significantly reduces the complexity of flow rule conflict checking at the data plane level. The solution can be expended from a single SDN domain to multiple SDN domains and hybrid networks by applying network service function chaining (SFC) for inter-domain policy management.

With the increasing complexity of computing systems and the rise in the number of risks and vulnerabilities, it is necessary to provide a scalable security situation awareness tool to assist the system administrator in protecting the critical assets, as well as managing the security state of the system. There are many methods to provide security states' analysis and management. For instance, by using a Firewall to manage the security state, and/or a graphical analysis tools such as attack graphs for analysis.

Attack Graphs are powerful graphical security analysis tools as they provide a visual representation of all possible attack scenarios that an attacker may take to exploit system vulnerabilities. The attack graph's scalability, however, is a major concern for enumerating all possible attack scenarios as it is considered an NP-complete problem. There have been many research work trying to come up with a scalable solution for the attack graph. Nevertheless, non-practical attack graph based solutions have been used in practice for realtime security analysis.

In this thesis, a new framework, namely 3S (Scalable Security Sates) analysis framework is proposed, which present a new approach of utilizing Software-Defined Networking (SDN)-based distributed firewall capabilities and the concept of stateful data plane to construct scalable attack graphs in near-realtime, which is a practical approach to use attack graph for realtime security decisions. The goal of the proposed work is to control reachability information between different datacenter segments to reduce the dependencies among vulnerabilities and restrict the attack graph analysis in a relative small scope. The proposed framework is based on SDN's programmable capabilities to adjust the distributed firewall policies dynamically according to security situations during the running time. It apply white-list-based security policies to limit the attacker's capability from moving or exploiting different segments by only allowing uni-directional vulnerability dependency links between segments. Specifically, several test cases will be presented with various attack scenarios and analyze how distributed firewall and stateful SDN data plan can significantly reduce the security states construction and analysis. The proposed approach proved to achieve a percentage of improvement over 61% in comparison with prior modules were SDN and distributed firewall are not in use.