ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Security
Description
Access control is necessary for information assurance in many of today's applications such as banking and electronic health record. Access control breaches are critical security problems that can result from unintended and improper implementation of security policies. Security testing can help identify security vulnerabilities early and avoid unexpected expensive cost in handling breaches for security architects and security engineers. The process of security testing which involves creating tests that effectively examine vulnerabilities is a challenging task. Role-Based Access Control (RBAC) has been widely adopted to support fine-grained access control. However, in practice, due to its complexity including role management, role hierarchy with hundreds of roles, and their associated privileges and users, systematically testing RBAC systems is crucial to ensure the security in various domains ranging from cyber-infrastructure to mission-critical applications. In this thesis, we introduce i) a security testing technique for RBAC systems considering the principle of maximum privileges, the structure of the role hierarchy, and a new security test coverage criterion; ii) a MTBDD (Multi-Terminal Binary Decision Diagram) based representation of RBAC security policy including RHMTBDD (Role Hierarchy MTBDD) to efficiently generate effective positive and negative security test cases; and iii) a security testing framework which takes an XACML-based RBAC security policy as an input, parses it into a RHMTBDD representation and then generates positive and negative test cases. We also demonstrate the efficacy of our approach through case studies.
ContributorsGupta, Poonam (Author) / Ahn, Gail-Joon (Thesis advisor) / Collofello, James (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2014
Description
Most existing security decisions for both defending and attacking are made based on some deterministic approaches that only give binary answers. Even though these approaches can achieve low false positive rate for decision making, they have high false negative rates due to the lack of accommodations to new attack methods and defense techniques. In this dissertation, I study how to discover and use patterns with uncertainty and randomness to counter security challenges. By extracting and modeling patterns in security events, I am able to handle previously unknown security events with quantified confidence, rather than simply making binary decisions. In particular, I cope with the following four real-world security challenges by modeling and analyzing with pattern-based approaches: 1) How to detect and attribute previously unknown shellcode? I propose instruction sequence abstraction that extracts coarse-grained patterns from an instruction sequence and use Markov chain-based model and support vector machines to detect and attribute shellcode; 2) How to safely mitigate routing attacks in mobile ad hoc networks? I identify routing table change patterns caused by attacks, propose an extended Dempster-Shafer theory to measure the risk of such changes, and use a risk-aware response mechanism to mitigate routing attacks; 3) How to model, understand, and guess human-chosen picture passwords? I analyze collected human-chosen picture passwords, propose selection function that models patterns in password selection, and design two algorithms to optimize password guessing paths; and 4) How to identify influential figures and events in underground social networks? I analyze collected underground social network data, identify user interaction patterns, and propose a suite of measures for systematically discovering and mining adversarial evidence. By solving these four problems, I demonstrate that discovering and using patterns could help deal with challenges in computer security, network security, human-computer interaction security, and social network security.
ContributorsZhao, Ziming (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Huang, Dijiang (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2014
Description
In modern healthcare environments, there is a strong need to create an infrastructure that reduces time-consuming efforts and costly operations to obtain a patient's complete medical record and uniformly integrates this heterogeneous collection of medical data to deliver it to the healthcare professionals. As a result, healthcare providers are more willing to shift their electronic medical record (EMR) systems to clouds that can remove the geographical distance barriers among providers and patient. Even though cloud-based EMRs have received considerable attention since it would help achieve lower operational cost and better interoperability with other healthcare providers, the adoption of security-aware cloud systems has become an extremely important prerequisite for bringing interoperability and efficient management to the healthcare industry. Since a shared electronic health record (EHR) essentially represents a virtualized aggregation of distributed clinical records from multiple healthcare providers, sharing of such integrated EHRs may comply with various authorization policies from these data providers. In this work, we focus on the authorized and selective sharing of EHRs among several parties with different duties and objectives that satisfies access control and compliance issues in healthcare cloud computing environments. We present a secure medical data sharing framework to support selective sharing of composite EHRs aggregated from various healthcare providers and compliance of HIPAA regulations. Our approach also ensures that privacy concerns need to be accommodated for processing access requests to patients' healthcare information. To realize our proposed approach, we design and implement a cloud-based EHRs sharing system. In addition, we describe case studies and evaluation results to demonstrate the effectiveness and efficiency of our approach.
ContributorsWu, Ruoyu (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2012
Description
Smartphones are pervasive nowadays. They are supported by mobile platforms that allow users to download and run feature-rich mobile applications (apps). While mobile apps help users conveniently process personal data on mobile devices, they also pose security and privacy threats and put user's data at risk. Even though modern mobile platforms such as Android have integrated security mechanisms to protect users, most mechanisms do not easily adapt to user's security requirements and rapidly evolving threats. They either fail to provide sufficient intelligence for a user to make informed security decisions, or require great sophistication to configure the mechanisms for enforcing security decisions. These limitations lead to a situation where users are disadvantageous against emerging malware on modern mobile platforms. To remedy this situation, I propose automated and systematic approaches to address three security management tasks: monitoring, assessment, and confinement of mobile apps. In particular, monitoring apps helps a user observe and record apps' runtime behaviors as controlled under security mechanisms. Automated assessment distills intelligence from the observed behaviors and the security configurations of security mechanisms. The distilled intelligence further fuels enhanced confinement mechanisms that flexibly and accurately shape apps' behaviors. To demonstrate the feasibility of my approaches, I design and implement a suite of proof-of-concept prototypes that support the three tasks respectively.
ContributorsJing, Yiming (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Huang, Dijiang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2015