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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- Creators: Ahn, Gail-Joon
Description
With the advent of technologies such as web services, service oriented architecture and cloud computing, modern organizations have to deal with policies such as Firewall policies to secure the networks, XACML (eXtensible Access Control Markup Language) policies for controlling the access to critical information as well as resources. Management of these policies is an extremely important task in order to avoid unintended security leakages via illegal accesses, while maintaining proper access to services for legitimate users. Managing and maintaining access control policies manually over long period of time is an error prone task due to their inherent complex nature. Existing tools and mechanisms for policy management use different approaches for different types of policies. This research thesis represents a generic framework to provide an unified approach for policy analysis and management of different types of policies. Generic approach captures the common semantics and structure of different access control policies with the notion of policy ontology. Policy ontology representation is then utilized for effectively analyzing and managing the policies. This thesis also discusses a proof-of-concept implementation of the proposed generic framework and demonstrates how efficiently this unified approach can be used for analysis and management of different types of access control policies.
ContributorsKulkarni, Ketan (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2011
Description
In order to catch the smartest criminals in the world, digital forensics examiners need a means of collaborating and sharing information with each other and outside experts that is not prohibitively difficult. However, standard operating procedures and the rules of evidence generally disallow the use of the collaboration software and techniques that are currently available because they do not fully adhere to the dictated procedures for the handling, analysis, and disclosure of items relating to cases. The aim of this work is to conceive and design a framework that provides a completely new architecture that 1) can perform fundamental functions that are common and necessary to forensic analyses, and 2) is structured such that it is possible to include collaboration-facilitating components without changing the way users interact with the system sans collaboration. This framework is called the Collaborative Forensic Framework (CUFF). CUFF is constructed from four main components: Cuff Link, Storage, Web Interface, and Analysis Block. With the Cuff Link acting as a mediator between components, CUFF is flexible in both the method of deployment and the technologies used in implementation. The details of a realization of CUFF are given, which uses a combination of Java, the Google Web Toolkit, Django with Apache for a RESTful web service, and an Ubuntu Enterprise Cloud using Eucalyptus. The functionality of CUFF's components is demonstrated by the integration of an acquisition script designed for Android OS-based mobile devices that use the YAFFS2 file system. While this work has obvious application to examination labs which work under the mandate of judicial or investigative bodies, security officers at any organization would benefit from the improved ability to cooperate in electronic discovery efforts and internal investigations.
ContributorsMabey, Michael Kent (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2011
Description
In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in unencrypted forms to remote machines owned and operated by third-party service providers, there are risks of unauthorized use of the users' sensitive data by service providers. Although there are many techniques for protecting users' data from outside attackers, currently there is no effective way to protect users' sensitive data from service providers. In this dissertation, an approach is presented to protecting the confidentiality of users' data from service providers, and ensuring that service providers cannot collect users' confidential data while the data is processed or stored in cloud computing systems. The approach has four major features: (1) separation of software service providers and infrastructure service providers, (2) hiding the information of the owners of data, (3) data obfuscation, and (4) software module decomposition and distributed execution. Since the approach to protecting users' data confidentiality includes software module decomposition and distributed execution, it is very important to effectively allocate the resource of servers in SBS to each of the software module to manage the overall performance of workflows in SBS. An approach is presented to resource allocation for SBS to adaptively allocating the system resources of servers to their software modules in runtime in order to satisfy the performance requirements of multiple workflows in SBS. Experimental results show that the dynamic resource allocation approach can substantially increase the throughput of a SBS and the optimal resource allocation can be found in polynomial time
ContributorsAn, Ho Geun (Author) / Yau, Sik-Sang (Thesis advisor) / Huang, Dijiang (Committee member) / Ahn, Gail-Joon (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2012
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
Access control is one of the most fundamental security mechanisms used in the design and management of modern information systems. However, there still exists an open question on how formal access control models can be automatically analyzed and fully realized in secure system development. Furthermore, specifying and managing access control policies are often error-prone due to the lack of effective analysis mechanisms and tools. In this dissertation, I present an Assurance Management Framework (AMF) that is designed to cope with various assurance management requirements from both access control system development and policy-based computing. On one hand, the AMF framework facilitates comprehensive analysis and thorough realization of formal access control models in secure system development. I demonstrate how this method can be applied to build role-based access control systems by adopting the NIST/ANSI RBAC standard as an underlying security model. On the other hand, the AMF framework ensures the correctness of access control policies in policy-based computing through automated reasoning techniques and anomaly management mechanisms. A systematic method is presented to formulate XACML in Answer Set Programming (ASP) that allows users to leverage off-the-shelf ASP solvers for a variety of analysis services. In addition, I introduce a novel anomaly management mechanism, along with a grid-based visualization approach, which enables systematic and effective detection and resolution of policy anomalies. I further evaluate the AMF framework through modeling and analyzing multiparty access control in Online Social Networks (OSNs). A MultiParty Access Control (MPAC) model is formulated to capture the essence of multiparty authorization requirements in OSNs. In particular, I show how AMF can be applied to OSNs for identifying and resolving privacy conflicts, and representing and reasoning about MPAC model and policy. To demonstrate the feasibility of the proposed methodology, a suite of proof-of-concept prototype systems is implemented as well.
ContributorsHu, Hongxin (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Dasgupta, Partha (Committee member) / Ye, Nong (Committee member) / Arizona State University (Publisher)
Created2012
Description
Detecting cyber-attacks in cyber systems is essential for protecting cyber infrastructures from cyber-attacks. It is very difficult to detect cyber-attacks in cyber systems due to their high complexity. The accuracy of the attack detection in the cyber systems depends heavily on the completeness of the collected sensor information. In this thesis, two approaches are presented: one to detecting attacks in completely observable cyber systems, and the other to estimating types of states in partially observable cyber systems for attack detection in cyber systems. These two approaches are illustrated using three large data sets of network traffic because the packet-level information of the network traffic data provides details about the cyber systems.
The approach to attack detection in cyber systems is based on a multimodal artificial neural network (MANN) using the collected network traffic data from completely observable cyber systems for training and testing. Since the training of MANN is computationally intensive, to reduce the computational overhead, an efficient feature selection algorithm using the genetic algorithm is developed and incorporated in this approach.
In order to detect attacks in cyber systems in partially observable environments, an approach to estimating the types of states in partially observable cyber systems, which is the first phase of attack detection in cyber systems in partially observable environments, is presented. The types of states of such cyber systems are useful to detecting cyber-attacks in such cyber systems. This approach involves the use of a convolutional neural network (CNN), and unsupervised learning with elbow method and k-means clustering algorithm.
The approach to attack detection in cyber systems is based on a multimodal artificial neural network (MANN) using the collected network traffic data from completely observable cyber systems for training and testing. Since the training of MANN is computationally intensive, to reduce the computational overhead, an efficient feature selection algorithm using the genetic algorithm is developed and incorporated in this approach.
In order to detect attacks in cyber systems in partially observable environments, an approach to estimating the types of states in partially observable cyber systems, which is the first phase of attack detection in cyber systems in partially observable environments, is presented. The types of states of such cyber systems are useful to detecting cyber-attacks in such cyber systems. This approach involves the use of a convolutional neural network (CNN), and unsupervised learning with elbow method and k-means clustering algorithm.
ContributorsGuha, Sayantan (Author) / Yau, Stephen S. (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016
Description
The recent years have witnessed a rapid development of mobile devices and smart devices. As more and more people are getting involved in the online environment, privacy issues are becoming increasingly important. People’s privacy in the digital world is much easier to leak than in the real world, because every action people take online would leave a trail of information which could be recorded, collected and used by malicious attackers. Besides, service providers might collect users’ information and analyze them, which also leads to a privacy breach. Therefore, preserving people’s privacy is very important in the online environment.
In this dissertation, I study the problems of preserving people’s identity privacy and loca- tion privacy in the online environment. Specifically, I study four topics: identity privacy in online social networks (OSNs), identity privacy in anonymous message submission, lo- cation privacy in location based social networks (LBSNs), and location privacy in location based reminders. In the first topic, I propose a system which can hide users’ identity and data from untrusted storage site where the OSN provider puts users’ data. I also design a fine grained access control mechanism which prevents unauthorized users from accessing the data. Based on the secret sharing scheme, I construct a shuffle protocol that disconnects the relationship between members’ identities and their submitted messages in the topic of identity privacy in anonymous message submission. The message is encrypted on the mem- ber side and decrypted on the message collector side. The collector eventually gets all of the messages but does not know who submitted which message. In the third topic, I pro- pose a framework that hides users’ check-in information from the LBSN. Considering the limited computation resources on smart devices, I propose a delegatable pseudo random function to outsource computations to the much more powerful server while preserving privacy. I also implement efficient revocations. In the topic of location privacy in location based reminders, I propose a system to hide users’ reminder locations from an untrusted cloud server. I propose a cross based approach and an improved bar based approach, re- spectively, to represent a reminder area. The reminder location and reminder message are encrypted before uploading to the cloud server, which then can determine whether the dis- tance between the user’s current location and the reminder location is within the reminder distance without knowing anything about the user’s location information and the content of the reminder message.
In this dissertation, I study the problems of preserving people’s identity privacy and loca- tion privacy in the online environment. Specifically, I study four topics: identity privacy in online social networks (OSNs), identity privacy in anonymous message submission, lo- cation privacy in location based social networks (LBSNs), and location privacy in location based reminders. In the first topic, I propose a system which can hide users’ identity and data from untrusted storage site where the OSN provider puts users’ data. I also design a fine grained access control mechanism which prevents unauthorized users from accessing the data. Based on the secret sharing scheme, I construct a shuffle protocol that disconnects the relationship between members’ identities and their submitted messages in the topic of identity privacy in anonymous message submission. The message is encrypted on the mem- ber side and decrypted on the message collector side. The collector eventually gets all of the messages but does not know who submitted which message. In the third topic, I pro- pose a framework that hides users’ check-in information from the LBSN. Considering the limited computation resources on smart devices, I propose a delegatable pseudo random function to outsource computations to the much more powerful server while preserving privacy. I also implement efficient revocations. In the topic of location privacy in location based reminders, I propose a system to hide users’ reminder locations from an untrusted cloud server. I propose a cross based approach and an improved bar based approach, re- spectively, to represent a reminder area. The reminder location and reminder message are encrypted before uploading to the cloud server, which then can determine whether the dis- tance between the user’s current location and the reminder location is within the reminder distance without knowing anything about the user’s location information and the content of the reminder message.
ContributorsZhao, Xinxin (Author) / Xue, Guoliang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Huang, Dijiang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2015
Description
Access control has been historically recognized as an effective technique for ensuring that computer systems preserve important security properties. Recently, attribute-based
access control (ABAC) has emerged as a new paradigm to provide access mediation
by leveraging the concept of attributes: observable properties that become relevant under a certain security context and are exhibited by the entities normally involved in the mediation process, namely, end-users and protected resources. Also recently, independently-run organizations from the private and public sectors have recognized the benefits of engaging in multi-disciplinary research collaborations that involve sharing sensitive proprietary resources such as scientific data, networking capabilities and computation time and have recognized ABAC as the paradigm that suits their needs for restricting the way such resources are to be shared with each other. In such a setting, a robust yet flexible access mediation scheme is crucial to guarantee participants are granted access to such resources in a safe and secure manner.
However, no consensus exists either in the literature with respect to a formal model that clearly defines the way the components depicted in ABAC should interact with each other, so that the rigorous study of security properties to be effectively pursued. This dissertation proposes an approach tailored to provide a well-defined and formal definition of ABAC, including a description on how attributes exhibited by different independent organizations are to be leveraged for mediating access to shared resources, by allowing for collaborating parties to engage in federations for the specification, discovery, evaluation and communication of attributes, policies, and access mediation decisions. In addition, a software assurance framework is introduced to support the correct construction of enforcement mechanisms implementing our approach by leveraging validation and verification techniques based on software assertions, namely, design by contract (DBC) and behavioral interface specification languages (BISL). Finally, this dissertation also proposes a distributed trust framework that allows for exchanging recommendations on the perceived reputations of members of our proposed federations, in such a way that the level of trust of previously-unknown participants can be properly assessed for the purposes of access mediation.
access control (ABAC) has emerged as a new paradigm to provide access mediation
by leveraging the concept of attributes: observable properties that become relevant under a certain security context and are exhibited by the entities normally involved in the mediation process, namely, end-users and protected resources. Also recently, independently-run organizations from the private and public sectors have recognized the benefits of engaging in multi-disciplinary research collaborations that involve sharing sensitive proprietary resources such as scientific data, networking capabilities and computation time and have recognized ABAC as the paradigm that suits their needs for restricting the way such resources are to be shared with each other. In such a setting, a robust yet flexible access mediation scheme is crucial to guarantee participants are granted access to such resources in a safe and secure manner.
However, no consensus exists either in the literature with respect to a formal model that clearly defines the way the components depicted in ABAC should interact with each other, so that the rigorous study of security properties to be effectively pursued. This dissertation proposes an approach tailored to provide a well-defined and formal definition of ABAC, including a description on how attributes exhibited by different independent organizations are to be leveraged for mediating access to shared resources, by allowing for collaborating parties to engage in federations for the specification, discovery, evaluation and communication of attributes, policies, and access mediation decisions. In addition, a software assurance framework is introduced to support the correct construction of enforcement mechanisms implementing our approach by leveraging validation and verification techniques based on software assertions, namely, design by contract (DBC) and behavioral interface specification languages (BISL). Finally, this dissertation also proposes a distributed trust framework that allows for exchanging recommendations on the perceived reputations of members of our proposed federations, in such a way that the level of trust of previously-unknown participants can be properly assessed for the purposes of access mediation.
ContributorsRubio Medrano, Carlos Ernesto (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Zhao, Ziming (Committee member) / Santanam, Raghu (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016
Description
Passwords are ubiquitous and are poised to stay that way due to their relative usability, security and deployability when compared with alternative authentication schemes. Unfortunately, humans struggle with some of the assumptions or requirements that are necessary for truly strong passwords. As administrators try to push users towards password complexity and diversity, users still end up using predictable mangling patterns on old passwords and reusing the same passwords across services; users even inadvertently converge on the same patterns to a surprising degree, making an attacker’s job easier. This work explores using machine learning techniques to pick out strong passwords from weak ones, from a dataset of 10 million passwords, based on how structurally similar they were to the rest of the set.
ContributorsTodd, Margaret Nicole (Author) / Xue, Guoliang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016
Description
Software-Defined Networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane, which allows network administrators to consolidate common network services into a centralized module named SDN controller. Applications’ policies are transformed into standardized network rules in the data plane via SDN controller. Even though this centralization brings a great flexibility and programmability to the network, network rules generated by SDN applications cannot be trusted because there may exist malicious SDN applications, and insecure network flows can be made due to complex relations across network rules. In this dissertation, I investigate how to identify and resolve these security violations in SDN caused by the combination of network rules and applications’ policies. To this end, I propose a systematic policy management framework that better protects SDN itself and hardens existing network defense mechanisms using SDN.
More specifically, I discuss the following four security challenges in this dissertation: (1) In SDN, generating reliable network rules is challenging because SDN applications cannot be trusted and have complicated dependencies each other. To address this problem, I analyze applications’ policies and remove those dependencies by applying grid-based policy decomposition mechanism; (2) One network rule could accidentally affect others (or by malicious users), which lead to creating of indirect security violations. I build systematic and automated tools that analyze network rules in the data plane to detect a wide range of security violations and resolve them in an automated fashion; (3) A fundamental limitation of current SDN protocol (OpenFlow) is a lack of statefulness, which is extremely important to several security applications such as stateful firewall. To bring statelessness to SDN-based environment, I come up with an innovative stateful monitoring scheme by extending existing OpenFlow specifications; (4) Existing honeynet architecture is suffering from its limited functionalities of ’data control’ and ’data capture’. To address this challenge, I design and implement an innovative next generation SDN-based honeynet architecture.
More specifically, I discuss the following four security challenges in this dissertation: (1) In SDN, generating reliable network rules is challenging because SDN applications cannot be trusted and have complicated dependencies each other. To address this problem, I analyze applications’ policies and remove those dependencies by applying grid-based policy decomposition mechanism; (2) One network rule could accidentally affect others (or by malicious users), which lead to creating of indirect security violations. I build systematic and automated tools that analyze network rules in the data plane to detect a wide range of security violations and resolve them in an automated fashion; (3) A fundamental limitation of current SDN protocol (OpenFlow) is a lack of statefulness, which is extremely important to several security applications such as stateful firewall. To bring statelessness to SDN-based environment, I come up with an innovative stateful monitoring scheme by extending existing OpenFlow specifications; (4) Existing honeynet architecture is suffering from its limited functionalities of ’data control’ and ’data capture’. To address this challenge, I design and implement an innovative next generation SDN-based honeynet architecture.
ContributorsHan, Wonkyu (Author) / Ahn, Gail-Joon (Thesis advisor) / Zhao, Ziming (Thesis advisor) / Doupe, Adam (Committee member) / Huang, Dijiang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2016