ETDs

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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Automated testing for RBAC policies

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…

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
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VIPLE Extensions in Robotic Simulation, Quadrotor Control Platform, and Machine Learning for Multirotor Activity Recognition

Description
Machine learning tutorials often employ an application and runtime specific solution for a given problem in which users are expected to have a broad understanding of data analysis and software programming. This thesis focuses on designing and implementing a new, hands-on approach to teaching machine learning by streamlining the process…

Machine learning tutorials often employ an application and runtime specific solution for a given problem in which users are expected to have a broad understanding of data analysis and software programming. This thesis focuses on designing and implementing a new, hands-on approach to teaching machine learning by streamlining the process of generating Inertial Movement Unit (IMU) data from multirotor flight sessions, training a linear classifier, and applying said classifier to solve Multi-rotor Activity Recognition (MAR) problems in an online lab setting. MAR labs leverage cloud computing and data storage technologies to host a versatile environment capable of logging, orchestrating, and visualizing the solution for an MAR problem through a user interface. MAR labs extends Arizona State University’s Visual IoT/Robotics Programming Language Environment (VIPLE) as a control platform for multi-rotors used in data collection. VIPLE is a platform developed for teaching computational thinking, visual programming, Internet of Things (IoT) and robotics application development. As a part of this education platform, this work also develops a 3D simulator capable of simulating the programmable behaviors of a robot within a maze environment and builds a physical quadrotor for use in MAR lab experiments.
ContributorsDe La Rosa, Matthew Lee (Author) / Chen, Yinong (Thesis advisor) / Collofello, James (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2018