Full metadata
Title
Towards Scalable Security State Management in The Cloud
Description
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.
Date Created
2023
Contributors
- Sabur, Abdulhakim (Author)
- Zhao, Ming (Thesis advisor)
- Xue, Guoliang (Committee member)
- Davulcu, Hasan (Committee member)
- Zhang, Yanchao (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
165 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.187520
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: Ph.D., Arizona State University, 2023
Field of study: Computer Engineering
System Created
- 2023-06-07 11:30:02
System Modified
- 2023-06-07 11:30:08
- 1 year 5 months ago
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