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- All Subjects: Computer Science
- Creators: Doupe, Adam
Description
Mobile apps have improved human lifestyle in various aspects ranging from instant messaging to tele-health. In the current app development paradigm, apps are being developed individually and agnostic of each other. The goal of this thesis is to allow a new world where multiple apps communicate with each other to achieve synergistic benefits. To enable integration between apps, manual communication between developers is needed, which can be problematic on many levels. In order to promote app integration, a systematic approach towards data sharing between multiple apps is essential. However, current approaches to app integration require large code modifications to reap the benefits of shared data such as requiring developers to provide APIs or use large, invasive middlewares. In this thesis, a data sharing framework was developed providing a non-invasive interface between mobile apps for data sharing and integration. A separate app acts as a registry to allow apps to register database tables to be shared and query this information. Two health monitoring apps were developed to evaluate the sharing framework and different methods of data integration between apps to promote synergistic feedback. The health monitoring apps have shown non-invasive solutions can provide data sharing functionality without large code modifications and manual communication between developers.
ContributorsMilazzo, Joseph (Author) / Gupta, Sandeep K.S. (Thesis advisor) / Varsamopoulos, Georgios (Committee member) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2014
Description
With the increasing user demand for low latency, elastic provisioning of computing resources coupled with ubiquitous and on-demand access to real-time data, cloud computing has emerged as a popular computing paradigm to meet growing user demands. However, with the introduction and rising use of wear- able technology and evolving uses of smart-phones, the concept of Internet of Things (IoT) has become a prevailing notion in the currently growing technology industry. Cisco Inc. has projected a data creation of approximately 403 Zetabytes (ZB) by 2018. The combination of bringing benign devices and connecting them to the web has resulted in exploding service and data aggregation requirements, thus requiring a new and innovative computing platform. This platform should have the capability to provide robust real-time data analytics and resource provisioning to clients, such as IoT users, on-demand. Such a computation model would need to function at the edge-of-the-network, forming a bridge between the large cloud data centers and the distributed connected devices.
This research expands on the notion of bringing computational power to the edge- of-the-network, and then integrating it with the cloud computing paradigm whilst providing services to diverse IoT-based applications. This expansion is achieved through the establishment of a new computing model that serves as a platform for IoT-based devices to communicate with services in real-time. We name this paradigm as Gateway-Oriented Reconfigurable Ecosystem (GORE) computing. Finally, this thesis proposes and discusses the development of a policy management framework for accommodating our proposed computational paradigm. The policy framework is designed to serve both the hosted applications and the GORE paradigm by enabling them to function more efficiently. The goal of the framework is to ensure uninterrupted communication and service delivery between users and their applications.
This research expands on the notion of bringing computational power to the edge- of-the-network, and then integrating it with the cloud computing paradigm whilst providing services to diverse IoT-based applications. This expansion is achieved through the establishment of a new computing model that serves as a platform for IoT-based devices to communicate with services in real-time. We name this paradigm as Gateway-Oriented Reconfigurable Ecosystem (GORE) computing. Finally, this thesis proposes and discusses the development of a policy management framework for accommodating our proposed computational paradigm. The policy framework is designed to serve both the hosted applications and the GORE paradigm by enabling them to function more efficiently. The goal of the framework is to ensure uninterrupted communication and service delivery between users and their applications.
ContributorsDsouza, Clinton (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Dasgupta, Partha (Committee member) / Arizona State University (Publisher)
Created2015
Description
Android is currently the most widely used mobile operating system. The permission model in Android governs the resource access privileges of applications. The permission model however is amenable to various attacks, including re-delegation attacks, background snooping attacks and disclosure of private information. This thesis is aimed at understanding, analyzing and performing forensics on application behavior. This research sheds light on several security aspects, including the use of inter-process communications (IPC) to perform permission re-delegation attacks.
Android permission system is more of app-driven rather than user controlled, which means it is the applications that specify their permission requirement and the only thing which the user can do is choose not to install a particular application based on the requirements. Given the all or nothing choice, users succumb to pressures and needs to accept permissions requested. This thesis proposes a couple of ways for providing the users finer grained control of application privileges. The same methods can be used to evade the Permission Re-delegation attack.
This thesis also proposes and implements a novel methodology in Android that can be used to control the access privileges of an Android application, taking into consideration the context of the running application. This application-context based permission usage is further used to analyze a set of sample applications. We found the evidence of applications spoofing or divulging user sensitive information such as location information, contact information, phone id and numbers, in the background. Such activities can be used to track users for a variety of privacy-intrusive purposes. We have developed implementations that minimize several forms of privacy leaks that are routinely done by stock applications.
Android permission system is more of app-driven rather than user controlled, which means it is the applications that specify their permission requirement and the only thing which the user can do is choose not to install a particular application based on the requirements. Given the all or nothing choice, users succumb to pressures and needs to accept permissions requested. This thesis proposes a couple of ways for providing the users finer grained control of application privileges. The same methods can be used to evade the Permission Re-delegation attack.
This thesis also proposes and implements a novel methodology in Android that can be used to control the access privileges of an Android application, taking into consideration the context of the running application. This application-context based permission usage is further used to analyze a set of sample applications. We found the evidence of applications spoofing or divulging user sensitive information such as location information, contact information, phone id and numbers, in the background. Such activities can be used to track users for a variety of privacy-intrusive purposes. We have developed implementations that minimize several forms of privacy leaks that are routinely done by stock applications.
ContributorsGollapudi, Narasimha Aditya (Author) / Dasgupta, Partha (Thesis advisor) / Xue, Guoliang (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2014
Description
The increasing number of continually connected mobile persons has created an environment conducive to real time user data gathering for many uses both public and private in nature. Publicly, one can envision no longer requiring a census to determine the demographic composition of the country and its sub regions. The information provided is vastly more up to date than that of a census and allows civil authorities to be more agile and preemptive with planning. Privately, advertisers take advantage of a persons stated opinions, demographics, and contextual (where and when) information in order to formulate and present pertinent offers.
Regardless of its use this information can be sensitive in nature and should therefore be under the control of the user. Currently, a user has little say in the manner that their information is processed once it has been released. An ad-hoc approach is currently in use, where the location based service providers each maintain their own policy over personal information usage.
In order to allow more user control over their personal information while still providing for targeted advertising, a systematic approach to the release of the information is needed. It is for that reason we propose a User-Centric Context Aware Spatiotemporal Anonymization framework. At its core the framework will unify the current spatiotemporal anonymization with that of traditional anonymization so that user specified anonymization requirement is met or exceeded while allowing for more demographic information to be released.
Regardless of its use this information can be sensitive in nature and should therefore be under the control of the user. Currently, a user has little say in the manner that their information is processed once it has been released. An ad-hoc approach is currently in use, where the location based service providers each maintain their own policy over personal information usage.
In order to allow more user control over their personal information while still providing for targeted advertising, a systematic approach to the release of the information is needed. It is for that reason we propose a User-Centric Context Aware Spatiotemporal Anonymization framework. At its core the framework will unify the current spatiotemporal anonymization with that of traditional anonymization so that user specified anonymization requirement is met or exceeded while allowing for more demographic information to be released.
ContributorsSanchez, Michael Andrew (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Dasgupta, Partha (Committee member) / Arizona State University (Publisher)
Created2014
Description
Many web search improvements have been developed since the advent of the modern search engine, but one underrepresented area is the application of specific customizations to search results for educational web sites. In order to address this issue and improve the relevance of search results in automated learning environments, this work has integrated context-aware search principles with applications of preference based re-ranking and query modifications. This research investigates several aspects of context-aware search principles, specifically context-sensitive and preference based re-ranking of results which take user inputs as to their preferred content, and combines this with search query modifications which automatically search for a variety of modified terms based on the given search query, integrating these results into the overall re-ranking for the context. The result of this work is a novel web search algorithm which could be applied to any online learning environment attempting to collect relevant resources for learning about a given topic. The algorithm has been evaluated through user studies comparing traditional search results to the context-aware results returned through the algorithm for a given topic. These studies explore how this integration of methods could provide improved relevance in the search results returned when compared against other modern search engines.
ContributorsVan Egmond, Eric (Author) / Burleson, Winslow (Thesis advisor) / Syrotiuk, Violet (Thesis advisor) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2014
Description
The rate at which new malicious software (Malware) is created is consistently increasing each year. These new malwares are designed to bypass the current anti-virus countermeasures employed to protect computer systems. Security Analysts must understand the nature and intent of the malware sample in order to protect computer systems from these attacks. The large number of new malware samples received daily by computer security companies require Security Analysts to quickly determine the type, threat, and countermeasure for newly identied samples. Our approach provides for a visualization tool to assist the Security Analyst in these tasks that allows the Analyst to visually identify relationships between malware samples.
This approach consists of three steps. First, the received samples are processed by a sandbox environment to perform a dynamic behavior analysis. Second, the reports of the dynamic behavior analysis are parsed to extract identifying features which are matched against other known and analyzed samples. Lastly, those matches that are determined to express a relationship are visualized as an edge connected pair of nodes in an undirected graph.
This approach consists of three steps. First, the received samples are processed by a sandbox environment to perform a dynamic behavior analysis. Second, the reports of the dynamic behavior analysis are parsed to extract identifying features which are matched against other known and analyzed samples. Lastly, those matches that are determined to express a relationship are visualized as an edge connected pair of nodes in an undirected graph.
ContributorsHolmes, James Edward (Author) / Ahn, Gail-Joon (Thesis advisor) / Dasgupta, Partha (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2014
Description
Computational thinking, the creative thought process behind algorithmic design and programming, is a crucial introductory skill for both computer scientists and the population in general. In this thesis I perform an investigation into introductory computer science education in the United States and find that computational thinking is not effectively taught at either the high school or the college level. To remedy this, I present a new educational system intended to teach computational thinking called Genost. Genost consists of a software tool and a curriculum based on teaching computational thinking through fundamental programming structures and algorithm design. Genost's software design is informed by a review of eight major computer science educational software systems. Genost's curriculum is informed by a review of major literature on computational thinking. In two educational tests of Genost utilizing both college and high school students, Genost was shown to significantly increase computational thinking ability with a large effect size.
ContributorsWalliman, Garret (Author) / Atkinson, Robert (Thesis advisor) / Chen, Yinong (Thesis advisor) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2015
Description
Lots of previous studies have analyzed human tutoring at great depths and have shown expert human tutors to produce effect sizes, which is twice of that produced by an intelligent tutoring system (ITS). However, there has been no consensus on which factor makes them so effective. It is important to know this, so that same phenomena can be replicated in an ITS in order to achieve the same level of proficiency as expert human tutors. Also, to the best of my knowledge no one has looked at student reactions when they are working with a computer based tutor. The answers to both these questions are needed in order to build a highly effective computer-based tutor. My research focuses on the second question. In the first phase of my thesis, I analyzed the behavior of students when they were working with a step-based tutor Andes, using verbal-protocol analysis. The accomplishment of doing this was that I got to know of some ways in which students use a step-based tutor which can pave way for the creation of more effective computer-based tutors. I found from the first phase of the research that students often keep trying to fix errors by guessing repeatedly instead of asking for help by clicking the hint button. This phenomenon is known as hint refusal. Surprisingly, a large portion of the student's foundering was due to hint refusal. The hypothesis tested in the second phase of the research is that hint refusal can be significantly reduced and learning can be significantly increased if Andes uses more unsolicited hints and meta hints. An unsolicited hint is a hint that is given without the student asking for one. A meta-hint is like an unsolicited hint in that it is given without the student asking for it, but it just prompts the student to click on the hint button. Two versions of Andes were compared: the original version and a new version that gave more unsolicited and meta-hints. During a two-hour experiment, there were large, statistically reliable differences in several performance measures suggesting that the new policy was more effective.
ContributorsRanganathan, Rajagopalan (Author) / VanLehn, Kurt (Thesis advisor) / Atkinson, Robert (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2011
Description
Due to the shortcomings of modern Mobile Device Management solutions, businesses
have begun to incorporate forensics to analyze their mobile devices and respond
to any incidents of malicious activity in order to protect their sensitive data. Current
forensic tools, however, can only look a static image of the device being examined,
making it difficult for a forensic analyst to produce conclusive results regarding the
integrity of any sensitive data on the device. This research thesis expands on the
use of forensics to secure data by implementing an agent on a mobile device that can
continually collect information regarding the state of the device. This information is
then sent to a separate server in the form of log files to be analyzed using a specialized
tool. The analysis tool is able to look at the data collected from the device over time
and perform specific calculations, according to the user's specifications, highlighting
any correlations or anomalies among the data which might be considered suspicious
to a forensic analyst. The contribution of this paper is both an in-depth explanation
on the implementation of an iOS application to be used to improve the mobile forensics
process as well as a proof-of-concept experiment showing how evidence collected
over time can be used to improve the accuracy of a forensic analysis.
have begun to incorporate forensics to analyze their mobile devices and respond
to any incidents of malicious activity in order to protect their sensitive data. Current
forensic tools, however, can only look a static image of the device being examined,
making it difficult for a forensic analyst to produce conclusive results regarding the
integrity of any sensitive data on the device. This research thesis expands on the
use of forensics to secure data by implementing an agent on a mobile device that can
continually collect information regarding the state of the device. This information is
then sent to a separate server in the form of log files to be analyzed using a specialized
tool. The analysis tool is able to look at the data collected from the device over time
and perform specific calculations, according to the user's specifications, highlighting
any correlations or anomalies among the data which might be considered suspicious
to a forensic analyst. The contribution of this paper is both an in-depth explanation
on the implementation of an iOS application to be used to improve the mobile forensics
process as well as a proof-of-concept experiment showing how evidence collected
over time can be used to improve the accuracy of a forensic analysis.
ContributorsWhitaker, Jeremy (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Yau, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
Widespread adoption of smartphone based Mobile Medical Apps (MMAs) is opening new avenues for innovation, bringing MMAs to the forefront of low cost healthcare delivery. These apps often control human physiology and work on sensitive data. Thus it is necessary to have evidences of their trustworthiness i.e. maintaining privacy of health data, long term operation of wearable sensors and ensuring no harm to the user before actual marketing. Traditionally, clinical studies are used to validate the trustworthiness of medical systems. However, they can take long time and could potentially harm the user. Such evidences can be generated using simulations and mathematical analysis. These methods involve estimating the MMA interactions with human physiology. However, the nonlinear nature of human physiology makes the estimation challenging.
This research analyzes and develops MMA software while considering its interactions with human physiology to assure trustworthiness. A novel app development methodology is used to objectively evaluate trustworthiness of a MMA by generating evidences using automatic techniques. It involves developing the Health-Dev β tool to generate a) evidences of trustworthiness of MMAs and b) requirements assured code generation for vulnerable components of the MMA without hindering the app development process. In this method, all requests from MMAs pass through a trustworthy entity, Trustworthy Data Manager which checks if the app request satisfies the MMA requirements. This method is intended to expedite the design to marketing process of MMAs. The objectives of this research is to develop models, tools and theory for evidence generation and can be divided into the following themes:
• Sustainable design configuration estimation of MMAs: Developing an optimization framework which can generate sustainable and safe sensor configuration while considering interactions of the MMA with the environment.
• Evidence generation using simulation and formal methods: Developing models and tools to verify safety properties of the MMA design to ensure no harm to the human physiology.
• Automatic code generation for MMAs: Investigating methods for automatically
• Performance analysis of trustworthy data manager: Evaluating response time generating trustworthy software for vulnerable components of a MMA and evidences.performance of trustworthy data manager under interactions from non-MMA smartphone apps.
This research analyzes and develops MMA software while considering its interactions with human physiology to assure trustworthiness. A novel app development methodology is used to objectively evaluate trustworthiness of a MMA by generating evidences using automatic techniques. It involves developing the Health-Dev β tool to generate a) evidences of trustworthiness of MMAs and b) requirements assured code generation for vulnerable components of the MMA without hindering the app development process. In this method, all requests from MMAs pass through a trustworthy entity, Trustworthy Data Manager which checks if the app request satisfies the MMA requirements. This method is intended to expedite the design to marketing process of MMAs. The objectives of this research is to develop models, tools and theory for evidence generation and can be divided into the following themes:
• Sustainable design configuration estimation of MMAs: Developing an optimization framework which can generate sustainable and safe sensor configuration while considering interactions of the MMA with the environment.
• Evidence generation using simulation and formal methods: Developing models and tools to verify safety properties of the MMA design to ensure no harm to the human physiology.
• Automatic code generation for MMAs: Investigating methods for automatically
• Performance analysis of trustworthy data manager: Evaluating response time generating trustworthy software for vulnerable components of a MMA and evidences.performance of trustworthy data manager under interactions from non-MMA smartphone apps.
ContributorsBagade, Priyanka (Author) / Gupta, Sandeep K. S. (Thesis advisor) / Wu, Carole-Jean (Committee member) / Doupe, Adam (Committee member) / Zhang, Yi (Committee member) / Arizona State University (Publisher)
Created2015