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
The widespread adoption of mobile devices gives rise to new opportunities and challenges for authentication mechanisms. Many traditional authentication mechanisms become unsuitable for smart devices. For example, while password is widely used on computers as user identity authentication, inputting password on small smartphone screen is error-prone and not convenient. In the meantime, there are emerging demands for new types of authentication. Proximity authentication is an example, which is not needed for computers but quite necessary for smart devices. These challenges motivate me to study and develop novel authentication mechanisms specific for smart devices.
In this dissertation, I am interested in the special authentication demands of smart devices and about to satisfy the demands. First, I study how the features of smart devices affect user identity authentications. For identity authentication domain, I aim to design a continuous, forge-resistant authentication mechanism that does not interrupt user-device interactions. I propose a mechanism that authenticates user identity based on the user's finger movement patterns. Next, I study a smart-device-specific authentication, proximity authentication, which authenticates whether two devices are in close proximity. For prox- imity authentication domain, I aim to design a user-friendly authentication mechanism that can defend against relay attacks. In addition, I restrict the authenticated distance to the scale of near field, i.e., a few centimeters. My first design utilizes a user's coherent two-finger movement on smart device screen to restrict the distance. To achieve a fully-automated system, I explore acoustic communications and propose a novel near field authentication system.
In this dissertation, I am interested in the special authentication demands of smart devices and about to satisfy the demands. First, I study how the features of smart devices affect user identity authentications. For identity authentication domain, I aim to design a continuous, forge-resistant authentication mechanism that does not interrupt user-device interactions. I propose a mechanism that authenticates user identity based on the user's finger movement patterns. Next, I study a smart-device-specific authentication, proximity authentication, which authenticates whether two devices are in close proximity. For prox- imity authentication domain, I aim to design a user-friendly authentication mechanism that can defend against relay attacks. In addition, I restrict the authenticated distance to the scale of near field, i.e., a few centimeters. My first design utilizes a user's coherent two-finger movement on smart device screen to restrict the distance. To achieve a fully-automated system, I explore acoustic communications and propose a novel near field authentication system.
ContributorsLi, Lingjun (Author) / Xue, Guoliang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Ye, Jieping (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2014
Description
Cloud computing is known as a new and powerful computing paradigm. This new generation of network computing model delivers both software and hardware as on-demand resources and various services over the Internet. However, the security concerns prevent users from adopting the cloud-based solutions to fulfill the IT requirement for many business critical computing. Due to the resource-sharing and multi-tenant nature of cloud-based solutions, cloud security is especially the most concern in the Infrastructure as a Service (IaaS). It has been attracting a lot of research and development effort in the past few years.
Virtualization is the main technology of cloud computing to enable multi-tenancy.
Computing power, storage, and network are all virtualizable to be shared in an IaaS system. This important technology makes abstract infrastructure and resources available to users as isolated virtual machines (VMs) and virtual networks (VNs). However, it also increases vulnerabilities and possible attack surfaces in the system, since all users in a cloud share these resources with others or even the attackers. The promising protection mechanism is required to ensure strong isolation, mediated sharing, and secure communications between VMs. Technologies for detecting anomalous traffic and protecting normal traffic in VNs are also needed. Therefore, how to secure and protect the private traffic in VNs and how to prevent the malicious traffic from shared resources are major security research challenges in a cloud system.
This dissertation proposes four novel frameworks to address challenges mentioned above. The first work is a new multi-phase distributed vulnerability, measurement, and countermeasure selection mechanism based on the attack graph analytical model. The second work is a hybrid intrusion detection and prevention system to protect VN and VM using virtual machines introspection (VMI) and software defined networking (SDN) technologies. The third work further improves the previous works by introducing a VM profiler and VM Security Index (VSI) to keep track the security status of each VM and suggest the optimal countermeasure to mitigate potential threats. The final work is a SDN-based proactive defense mechanism for a cloud system using a reconfiguration model and moving target defense approaches to actively and dynamically change the virtual network configuration of a cloud system.
Virtualization is the main technology of cloud computing to enable multi-tenancy.
Computing power, storage, and network are all virtualizable to be shared in an IaaS system. This important technology makes abstract infrastructure and resources available to users as isolated virtual machines (VMs) and virtual networks (VNs). However, it also increases vulnerabilities and possible attack surfaces in the system, since all users in a cloud share these resources with others or even the attackers. The promising protection mechanism is required to ensure strong isolation, mediated sharing, and secure communications between VMs. Technologies for detecting anomalous traffic and protecting normal traffic in VNs are also needed. Therefore, how to secure and protect the private traffic in VNs and how to prevent the malicious traffic from shared resources are major security research challenges in a cloud system.
This dissertation proposes four novel frameworks to address challenges mentioned above. The first work is a new multi-phase distributed vulnerability, measurement, and countermeasure selection mechanism based on the attack graph analytical model. The second work is a hybrid intrusion detection and prevention system to protect VN and VM using virtual machines introspection (VMI) and software defined networking (SDN) technologies. The third work further improves the previous works by introducing a VM profiler and VM Security Index (VSI) to keep track the security status of each VM and suggest the optimal countermeasure to mitigate potential threats. The final work is a SDN-based proactive defense mechanism for a cloud system using a reconfiguration model and moving target defense approaches to actively and dynamically change the virtual network configuration of a cloud system.
ContributorsChung, Chun-Jen (Author) / Huang, Dijiang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Xue, Guoliang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2015
Description
A Virtual Private Network (VPN) is the traditional approach for an end-to-end secure connection between two endpoints. Most existing VPN solutions are intended for wired networks with reliable connections. In a mobile environment, network connections are less reliable and devices experience intermittent network disconnections due to either switching from one network to another or experiencing a gap in coverage during roaming. These disruptive events affects traditional VPN performance, resulting in possible termination of applications, data loss, and reduced productivity. Mobile VPNs bridge the gap between what users and applications expect from a wired network and the realities of mobile computing.
In this dissertation, MobiVPN, which was built by modifying the widely-used OpenVPN so that the requirements of a mobile VPN were met, was designed and developed. The aim in MobiVPN was for it to be a reliable and efficient VPN for mobile environments. In order to achieve these objectives, MobiVPN introduces the following features: 1) Fast and lightweight VPN session resumption, where MobiVPN is able decrease the time it takes to resume a VPN tunnel after a mobility event by an average of 97.19\% compared to that of OpenVPN. 2) Persistence of TCP sessions of the tunneled applications allowing them to survive VPN tunnel disruptions due to a gap in network coverage no matter how long the coverage gap is. MobiVPN also has mechanisms to suspend and resume TCP flows during and after a network disconnection with a packet buffering option to maintain the TCP sending rate. MobiVPN was able to provide fast resumption of TCP flows after reconnection with improved TCP performance when multiple disconnections occur with an average of 30.08\% increase in throughput in the experiments where buffering was used, and an average of 20.93\% of increased throughput for flows that were not buffered. 3) A fine-grained, flow-based adaptive compression which allows MobiVPN to treat each tunneled flow independently so that compression can be turned on for compressible flows, and turned off for incompressible ones. The experiments showed that the flow-based adaptive compression outperformed OpenVPN's compression options in terms of effective throughput, data reduction, and lesser compression operations.
In this dissertation, MobiVPN, which was built by modifying the widely-used OpenVPN so that the requirements of a mobile VPN were met, was designed and developed. The aim in MobiVPN was for it to be a reliable and efficient VPN for mobile environments. In order to achieve these objectives, MobiVPN introduces the following features: 1) Fast and lightweight VPN session resumption, where MobiVPN is able decrease the time it takes to resume a VPN tunnel after a mobility event by an average of 97.19\% compared to that of OpenVPN. 2) Persistence of TCP sessions of the tunneled applications allowing them to survive VPN tunnel disruptions due to a gap in network coverage no matter how long the coverage gap is. MobiVPN also has mechanisms to suspend and resume TCP flows during and after a network disconnection with a packet buffering option to maintain the TCP sending rate. MobiVPN was able to provide fast resumption of TCP flows after reconnection with improved TCP performance when multiple disconnections occur with an average of 30.08\% increase in throughput in the experiments where buffering was used, and an average of 20.93\% of increased throughput for flows that were not buffered. 3) A fine-grained, flow-based adaptive compression which allows MobiVPN to treat each tunneled flow independently so that compression can be turned on for compressible flows, and turned off for incompressible ones. The experiments showed that the flow-based adaptive compression outperformed OpenVPN's compression options in terms of effective throughput, data reduction, and lesser compression operations.
ContributorsAlshalan, Abdullah O. (Author) / Huang, Dijiang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Doupe, Adam (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2017
Description
The telephone network is used by almost every person in the modern world. With the rise of Internet access to the PSTN, the telephone network today is rife with telephone spam and scams. Spam calls are significant annoyances for telephone users, unlike email spam, spam calls demand immediate attention. They are not only significant annoyances but also result in significant financial losses in the economy. According to complaint data from the FTC, complaints on illegal calls have made record numbers in recent years. Americans lose billions to fraud due to malicious telephone communication, despite various efforts to subdue telephone spam, scam, and robocalls.
In this dissertation, a study of what causes the users to fall victim to telephone scams is presented, and it demonstrates that impersonation is at the heart of the problem. Most solutions today primarily rely on gathering offending caller IDs, however, they do not work effectively when the caller ID has been spoofed. Due to a lack of authentication in the PSTN caller ID transmission scheme, fraudsters can manipulate the caller ID to impersonate a trusted entity and further a variety of scams. To provide a solution to this fundamental problem, a novel architecture and method to authenticate the transmission of the caller ID is proposed. The solution enables the possibility of a security indicator which can provide an early warning to help users stay vigilant against telephone impersonation scams, as well as provide a foundation for existing and future defenses to stop unwanted telephone communication based on the caller ID information.
In this dissertation, a study of what causes the users to fall victim to telephone scams is presented, and it demonstrates that impersonation is at the heart of the problem. Most solutions today primarily rely on gathering offending caller IDs, however, they do not work effectively when the caller ID has been spoofed. Due to a lack of authentication in the PSTN caller ID transmission scheme, fraudsters can manipulate the caller ID to impersonate a trusted entity and further a variety of scams. To provide a solution to this fundamental problem, a novel architecture and method to authenticate the transmission of the caller ID is proposed. The solution enables the possibility of a security indicator which can provide an early warning to help users stay vigilant against telephone impersonation scams, as well as provide a foundation for existing and future defenses to stop unwanted telephone communication based on the caller ID information.
ContributorsTu, Huahong (Author) / Doupe, Adam (Thesis advisor) / Ahn, Gail-Joon (Thesis advisor) / Huang, Dijiang (Committee member) / Zhang, Yanchao (Committee member) / Zhao, Ziming (Committee member) / Arizona State University (Publisher)
Created2017
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
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
Description
Wireless sensor networks (WSN) and the communication and the security therein have been gaining further prominence in the tech-industry recently, with the emergence of the so called Internet of Things (IoT). The steps from acquiring data and making a reactive decision base on the acquired sensor measurements are complex and requires careful execution of several steps. In many of these steps there are still technological gaps to fill that are due to the fact that several primitives that are desirable in a sensor network environment are bolt on the networks as application layer functionalities, rather than built in them. For several important functionalities that are at the core of IoT architectures we have developed a solution that is analyzed and discussed in the following chapters.
The chain of steps from the acquisition of sensor samples until these samples reach a control center or the cloud where the data analytics are performed, starts with the acquisition of the sensor measurements at the correct time and, importantly, synchronously among all sensors deployed. This synchronization has to be network wide, including both the wired core network as well as the wireless edge devices. This thesis studies a decentralized and lightweight solution to synchronize and schedule IoT devices over wireless and wired networks adaptively, with very simple local signaling. Furthermore, measurement results have to be transported and aggregated over the same interface, requiring clever coordination among all nodes, as network resources are shared, keeping scalability and fail-safe operation in mind. Furthermore ensuring the integrity of measurements is a complicated task. On the one hand Cryptography can shield the network from outside attackers and therefore is the first step to take, but due to the volume of sensors must rely on an automated key distribution mechanism. On the other hand cryptography does not protect against exposed keys or inside attackers. One however can exploit statistical properties to detect and identify nodes that send false information and exclude these attacker nodes from the network to avoid data manipulation. Furthermore, if data is supplied by a third party, one can apply automated trust metric for each individual data source to define which data to accept and consider for mentioned statistical tests in the first place. Monitoring the cyber and physical activities of an IoT infrastructure in concert is another topic that is investigated in this thesis.
The chain of steps from the acquisition of sensor samples until these samples reach a control center or the cloud where the data analytics are performed, starts with the acquisition of the sensor measurements at the correct time and, importantly, synchronously among all sensors deployed. This synchronization has to be network wide, including both the wired core network as well as the wireless edge devices. This thesis studies a decentralized and lightweight solution to synchronize and schedule IoT devices over wireless and wired networks adaptively, with very simple local signaling. Furthermore, measurement results have to be transported and aggregated over the same interface, requiring clever coordination among all nodes, as network resources are shared, keeping scalability and fail-safe operation in mind. Furthermore ensuring the integrity of measurements is a complicated task. On the one hand Cryptography can shield the network from outside attackers and therefore is the first step to take, but due to the volume of sensors must rely on an automated key distribution mechanism. On the other hand cryptography does not protect against exposed keys or inside attackers. One however can exploit statistical properties to detect and identify nodes that send false information and exclude these attacker nodes from the network to avoid data manipulation. Furthermore, if data is supplied by a third party, one can apply automated trust metric for each individual data source to define which data to accept and consider for mentioned statistical tests in the first place. Monitoring the cyber and physical activities of an IoT infrastructure in concert is another topic that is investigated in this thesis.
ContributorsGentz, Reinhard Werner (Author) / Scaglione, Anna (Thesis advisor) / Zhang, Yanchao (Committee member) / Peisert, Sean (Committee member) / Ahn, Gail-Joon (Committee member) / Arizona State University (Publisher)
Created2017
Description
Cyber systems, including IoT (Internet of Things), are increasingly being used ubiquitously to vastly improve the efficiency and reduce the cost of critical application areas, such as finance, transportation, defense, and healthcare. Over the past two decades, computing efficiency and hardware cost have dramatically been improved. These improvements have made cyber systems omnipotent, and control many aspects of human lives. Emerging trends in successful cyber system breaches have shown increasing sophistication in attacks and that attackers are no longer limited by resources, including human and computing power. Most existing cyber defense systems for IoT systems have two major issues: (1) they do not incorporate human user behavior(s) and preferences in their approaches, and (2) they do not continuously learn from dynamic environment and effectively adapt to thwart sophisticated cyber-attacks. Consequently, the security solutions generated may not be usable or implementable by the user(s) thereby drastically reducing the effectiveness of these security solutions.
In order to address these major issues, a comprehensive approach to securing ubiquitous smart devices in IoT environment by incorporating probabilistic human user behavioral inputs is presented. The approach will include techniques to (1) protect the controller device(s) [smart phone or tablet] by continuously learning and authenticating the legitimate user based on the touch screen finger gestures in the background, without requiring users’ to provide their finger gesture inputs intentionally for training purposes, and (2) efficiently configure IoT devices through controller device(s), in conformance with the probabilistic human user behavior(s) and preferences, to effectively adapt IoT devices to the changing environment. The effectiveness of the approach will be demonstrated with experiments that are based on collected user behavioral data and simulations.
In order to address these major issues, a comprehensive approach to securing ubiquitous smart devices in IoT environment by incorporating probabilistic human user behavioral inputs is presented. The approach will include techniques to (1) protect the controller device(s) [smart phone or tablet] by continuously learning and authenticating the legitimate user based on the touch screen finger gestures in the background, without requiring users’ to provide their finger gesture inputs intentionally for training purposes, and (2) efficiently configure IoT devices through controller device(s), in conformance with the probabilistic human user behavior(s) and preferences, to effectively adapt IoT devices to the changing environment. The effectiveness of the approach will be demonstrated with experiments that are based on collected user behavioral data and simulations.
ContributorsBuduru, Arun Balaji (Author) / Yau, Sik-Sang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Davulcu, Hasan (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2016
Description
Wireless communication technologies have been playing an important role in modern society. Due to its inherent mobility property, wireless networks are more vulnerable to passive attacks than traditional wired networks. Anonymity, as an important issue in mobile network environment, serves as the first topic that leads to all the research work presented in this manuscript. Specifically, anonymity issue in Mobile Ad hoc Networks (MANETs) is discussed with details as the first section of research.
To thoroughly study on this topic, the presented work approaches it from an attacker's perspective. Under a perfect scenario, all the traffic in a targeted MANET exhibits the communication relations to a passive attacker. However, localization errors pose a significant influence on the accuracy of the derived communication patterns. To handle such issue, a new scheme is proposed to generate super nodes, which represent the activities of user groups in the target MANET. This scheme also helps reduce the scale of monitoring work by grouping users based on their behaviors.
The first part of work on anonymity in MANET leads to the thought on its major cause. The link-based communication pattern is a key contributor to the success of the traffic analysis attack. A natural way to circumvent such issue is to use link-less approaches. Information Centric Networking (ICN) is a typical instance of such kind. Its communication pattern is able to overcome the anonymity issue with MANET. However, it also comes with its own shortcomings. One of them is access control enforcement. To tackle this issue, a new naming scheme for contents transmitted in ICN networks is presented. This scheme is based on a new Attribute-Based Encryption (ABE) algorithm. It enforces access control in ICN with minimum requirements on additional network components.
Following the research work on ABE, an important function, delegation, exhibits a potential security issue. In traditional ABE schemes, Ciphertext-Policy ABE (CP-ABE), a user is able to generate a subset of authentic attribute key components for other users using delegation function. This capability is not monitored or controlled by the trusted third party (TTP) in the cryptosystem. A direct threat caused from this issue is that any user may intentionally or unintentionally lower the standards for attribute assignments. Unauthorized users/attackers may be able to obtain their desired attributes through a delegation party instead of directly from the TTP. As the third part of work presented in this manuscript, a three-level delegation restriction architecture is proposed. Furthermore, a delegation restriction scheme following this architecture is also presented. This scheme allows the TTP to have full control on the delegation function of all its direct users.
To thoroughly study on this topic, the presented work approaches it from an attacker's perspective. Under a perfect scenario, all the traffic in a targeted MANET exhibits the communication relations to a passive attacker. However, localization errors pose a significant influence on the accuracy of the derived communication patterns. To handle such issue, a new scheme is proposed to generate super nodes, which represent the activities of user groups in the target MANET. This scheme also helps reduce the scale of monitoring work by grouping users based on their behaviors.
The first part of work on anonymity in MANET leads to the thought on its major cause. The link-based communication pattern is a key contributor to the success of the traffic analysis attack. A natural way to circumvent such issue is to use link-less approaches. Information Centric Networking (ICN) is a typical instance of such kind. Its communication pattern is able to overcome the anonymity issue with MANET. However, it also comes with its own shortcomings. One of them is access control enforcement. To tackle this issue, a new naming scheme for contents transmitted in ICN networks is presented. This scheme is based on a new Attribute-Based Encryption (ABE) algorithm. It enforces access control in ICN with minimum requirements on additional network components.
Following the research work on ABE, an important function, delegation, exhibits a potential security issue. In traditional ABE schemes, Ciphertext-Policy ABE (CP-ABE), a user is able to generate a subset of authentic attribute key components for other users using delegation function. This capability is not monitored or controlled by the trusted third party (TTP) in the cryptosystem. A direct threat caused from this issue is that any user may intentionally or unintentionally lower the standards for attribute assignments. Unauthorized users/attackers may be able to obtain their desired attributes through a delegation party instead of directly from the TTP. As the third part of work presented in this manuscript, a three-level delegation restriction architecture is proposed. Furthermore, a delegation restriction scheme following this architecture is also presented. This scheme allows the TTP to have full control on the delegation function of all its direct users.
ContributorsLi, Bing (Author) / Huang, Dijiang (Thesis advisor) / Xue, Guoliang (Committee member) / Ahn, Gail-Joon (Committee member) / Zhang, Yanchao (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