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Numerous studies have examined the attachments individuals have to the places they visit, and that those attachments are formed through experiencing a place in person. This study is unique in that it examines pre-trip place attachment formation via the use of mobile technology and social media. It proposes that media

Numerous studies have examined the attachments individuals have to the places they visit, and that those attachments are formed through experiencing a place in person. This study is unique in that it examines pre-trip place attachment formation via the use of mobile technology and social media. It proposes that media experienced through the use of a participant's smartphone can foster the development of positive emotions, which in turn, facilitates greater mental imagery processing that ultimately influences pre-trip place attachment formation. An experimental design was constructed to examine how text and video on a destination's Facebook page influences an individual's emotions, mental imagery, and subsequently attachment to that destination. Specifically, a 2 (narrative text vs. descriptive text) x 2 (short, fast-paced video vs. long, slow-paced video) between-subjects design was used. A total of 343 usable participant responses were included in the analysis. The data was then analyzed through a two-step process using structural equation modeling. Results revealed no significant influence of textual or video media on emotions although the choice in text has a greater influence on emotions than choice in video. Additionally, emotions had a significant impact on mental imagery. Finally, mental imagery processing had a significant impact on only the social bonding dimension of place attachment. In conclusion, while media had no significant impact on emotions, the effect of previous traveler's retelling of personal accounts on the emotions of potential travelers researching a destination should be examined more closely. Further, the study participants had no prior experience with the destination, yet emotions influenced mental imagery, which also influenced social bonding. Thus further research should be conducted to better understand how potential traveler's image of a destination can be affected by the stories or others.
ContributorsPlunkett, Daniel (Author) / Budruk, Megha (Thesis advisor) / Lee, Woojin (Thesis advisor) / Wetmore, Jameson (Committee member) / Wise, Greg (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis addresses the ever increasing threat of botnets in the smartphone domain and focuses on the Android platform and the botnets using Online Social Networks (OSNs) as Command and Control (C&C;) medium. With any botnet, C&C; is one of the components on which the survival of botnet depends. Individual

This thesis addresses the ever increasing threat of botnets in the smartphone domain and focuses on the Android platform and the botnets using Online Social Networks (OSNs) as Command and Control (C&C;) medium. With any botnet, C&C; is one of the components on which the survival of botnet depends. Individual bots use the C&C; channel to receive commands and send the data. This thesis develops active host based approach for identifying the presence of bot based on the anomalies in the usage patterns of the user before and after the bot is installed on the user smartphone and alerting the user to the presence of the bot. A profile is constructed for each user based on the regular web usage patterns (achieved by intercepting the http(s) traffic) and implementing machine learning techniques to continuously learn the user's behavior and changes in the behavior and all the while looking for any anomalies in the user behavior above a threshold which will cause the user to be notified of the anomalous traffic. A prototype bot which uses OSN s as C&C; channel is constructed and used for testing. Users are given smartphones(Nexus 4 and Galaxy Nexus) running Application proxy which intercepts http(s) traffic and relay it to a server which uses the traffic and constructs the model for a particular user and look for any signs of anomalies. This approach lays the groundwork for the future host-based counter measures for smartphone botnets using OSN s as C&C; channel.
ContributorsKilari, Vishnu Teja (Author) / Xue, Guoliang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Dasgupta, Partha (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Continuous monitoring of sensor data from smart phones to identify human activities and gestures, puts a heavy load on the smart phone's power consumption. In this research study, the non-Euclidean geometry of the rich sensor data obtained from the user's smart phone is utilized to perform compressive analysis and efficient

Continuous monitoring of sensor data from smart phones to identify human activities and gestures, puts a heavy load on the smart phone's power consumption. In this research study, the non-Euclidean geometry of the rich sensor data obtained from the user's smart phone is utilized to perform compressive analysis and efficient classification of human activities by employing machine learning techniques. We are interested in the generalization of classical tools for signal approximation to newer spaces, such as rotation data, which is best studied in a non-Euclidean setting, and its application to activity analysis. Attributing to the non-linear nature of the rotation data space, which involve a heavy overload on the smart phone's processor and memory as opposed to feature extraction on the Euclidean space, indexing and compaction of the acquired sensor data is performed prior to feature extraction, to reduce CPU overhead and thereby increase the lifetime of the battery with a little loss in recognition accuracy of the activities. The sensor data represented as unit quaternions, is a more intrinsic representation of the orientation of smart phone compared to Euler angles (which suffers from Gimbal lock problem) or the computationally intensive rotation matrices. Classification algorithms are employed to classify these manifold sequences in the non-Euclidean space. By performing customized indexing (using K-means algorithm) of the evolved manifold sequences before feature extraction, considerable energy savings is achieved in terms of smart phone's battery life.
ContributorsSivakumar, Aswin (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2014
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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 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.
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
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Description
A benchmark suite that is representative of the programs a processor typically executes is necessary to understand a processor's performance or energy consumption characteristics. The first contribution of this work addresses this need for mobile platforms with MobileBench, a selection of representative smartphone applications. In smartphones, like any other

A benchmark suite that is representative of the programs a processor typically executes is necessary to understand a processor's performance or energy consumption characteristics. The first contribution of this work addresses this need for mobile platforms with MobileBench, a selection of representative smartphone applications. In smartphones, like any other portable computing systems, energy is a limited resource. Based on the energy characterization of a commercial widely-used smartphone, application cores are found to consume a significant part of the total energy consumption of the device. With this insight, the subsequent part of this thesis focuses on the portion of energy that is spent to move data from the memory system to the application core's internal registers. The primary motivation for this work comes from the relatively higher power consumption associated with a data movement instruction compared to that of an arithmetic instruction. The data movement energy cost is worsened esp. in a System on Chip (SoC) because the amount of data received and exchanged in a SoC based smartphone increases at an explosive rate. A detailed investigation is performed to quantify the impact of data movement

on the overall energy consumption of a smartphone device. To aid this study, microbenchmarks that generate desired data movement patterns between different levels of the memory hierarchy are designed. Energy costs of data movement are then computed by measuring the instantaneous power consumption of the device when the micro benchmarks are executed. This work makes an extensive use of hardware performance counters to validate the memory access behavior of microbenchmarks and to characterize the energy consumed in moving data. Finally, the calculated energy costs of data movement are used to characterize the portion of energy that MobileBench applications spend in moving data. The results of this study show that a significant 35% of the total device energy is spent in data movement alone. Energy is an increasingly important criteria in the context of designing architectures for future smartphones and this thesis offers insights into data movement energy consumption.
ContributorsPandiyan, Dhinakaran (Author) / Wu, Carole-Jean (Thesis advisor) / Shrivastava, Aviral (Committee member) / Lee, Yann-Hang (Committee member) / Arizona State University (Publisher)
Created2014
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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

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.
ContributorsGollapudi, Narasimha Aditya (Author) / Dasgupta, Partha (Thesis advisor) / Xue, Guoliang (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Dietary counseling from a registered dietitian has been shown in previous studies to aid in weight loss for those receiving counseling. With the increasing use of smartphone diet/weight loss applications (app), this study sought to investigate if an iPhone diet app providing feedback from a registered dietitian improved weight loss

Dietary counseling from a registered dietitian has been shown in previous studies to aid in weight loss for those receiving counseling. With the increasing use of smartphone diet/weight loss applications (app), this study sought to investigate if an iPhone diet app providing feedback from a registered dietitian improved weight loss and bio-markers of health. Twenty-four healthy adults who owned iPhones (BMI > 24 kg/m2) completed this trial. Participants were randomly assigned to one of three app groups: the MyDietitian app with daily feedback from a registered dietitian (n=7), the MyDietitian app without feedback (n=7), and the MyPlate feedback control app (n=10). Participants used their respective diet apps daily for 8-weeks while their weight loss, adherence to self-monitoring, blood bio-markers of health, and physical activity were monitored. All of the groups had a significant reduction in waist and hip circumference (p<0.001), a reduction in A1c (p=0.002), an increase in HDL cholesterol levels (p=0.012), and a reduction in calories consumed (p=0.022) over the duration of the trial. Adherence to diet monitoring via the apps did not differ between groups during the study. Body weight did not change during the study for any groups. However, when the participants were divided into low (<50% of days) or high adherence (>50% of days) groups, irrespective of study group, the high adherence group had a significant reduction in weight when compared to the low adherence group (p=0.046). These data suggest that diet apps may be useful tools for self-monitoring and even weight loss, but that the value appears to be the self-monitoring process and not the app specifically.
ContributorsThompson-Felty, Claudia (Author) / Johnston, Carol (Thesis advisor) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Levinson, Simin (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Dietary self-monitoring has been shown to be a predictor of weight loss success and is a prevalent part of behavioral weight control programs. As more weight loss applications have become available on smartphones, this feasibility study investigated whether the use of a smartphone application, or a smartphone memo feature would

Dietary self-monitoring has been shown to be a predictor of weight loss success and is a prevalent part of behavioral weight control programs. As more weight loss applications have become available on smartphones, this feasibility study investigated whether the use of a smartphone application, or a smartphone memo feature would improve dietary self-monitoring over the traditional paper-and-pencil method. The study also looked at whether the difference in methods would affect weight loss. Forty-seven adults (BMI 25 to 40 kg/m2) completed an 8-week study focused on tracking the difference in adherence to a self-monitoring protocol and subsequent weight loss. Participants owning iPhones (n=17) used the 'Lose It' application (AP) for diet and exercise tracking and were compared to smartphone participants who recorded dietary intake using a memo (ME) feature (n=15) on their phone and participants using the traditional paper-and-pencil (PA) method (n=15). There was no significant difference in completion rates between groups with an overall completion rate of 85.5%. The overall mean adherence to self-monitoring for the 8-week period was better in the AP group than the PA group (p = .024). No significant difference was found between the AP group and ME group (p = .148), or the ME group and the PA group (p = .457). Weight loss for the 8 week study was significant for all groups (p = .028). There was no significant difference in weight loss between groups. Number of days recorded regardless of group assignment showed a weak correlation to weight loss success (p = .068). Smartphone owners seeking to lose weight should be encouraged by the potential success associated with dietary tracking using a smartphone app as opposed to the traditional paper-and-pencil method.
ContributorsCunningham, Barbara (Author) / Wharton, Christopher (Christopher Mack), 1977- (Thesis advisor) / Johnston, Carol (Committee member) / Hall, Richard (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The purpose of this study was to gather qualitative data on different and novel methods used to self-monitor diet and exercise during a weight loss study. Participants who used either a traditional paper and pencil method or a smart phone weight loss app for diet and exercise tracking were recruited

The purpose of this study was to gather qualitative data on different and novel methods used to self-monitor diet and exercise during a weight loss study. Participants who used either a traditional paper and pencil method or a smart phone weight loss app for diet and exercise tracking were recruited for focus groups. Focus group discussions centered on the liked and disliked aspects of recording, perceived behavior changes, and suggestions for improved self-monitoring. Focus groups were organized based on the method of self-monitoring. The app group tracked calorie intake and expenditure via the "Lose It" app on their smart phones. The paper & pencil group recorded exercise and food intake in a journal and self-regulated diet based on recommended servings from each food group (or exchange lists). Focus group sessions were audio-recorded, transcribed and coded by the researcher and an independent coder. Results indicated that app participants liked the convenience, affordability, and user-friendly features, but wanted more nutrition advice. App participants liked self-managing their diet, not restricting certain foods or food groups and allowing for indulgences by balancing calories and exercise. Also, they desired an accurate estimation of energy expenditure from an app, based on individual characteristics (i.e., gender and age). Participants who recorded on paper liked the size for a visual layout of food entries, but desired a technology-enhanced method with an auto-calculation of calorie intake and expenditure. They also suggested increased accountability and opportunities for social support would enhance self-monitoring. Overall, an ideal technology-assisted self-monitoring app or program would be free and include an auto-calculation of calorie intake, a gender- and age- specific estimation of calories expended, easy entry of foods from a large database, the ability to enter whole recipes, nutrition information and recommendations, and be available via phone, tablet or computer (based on personal preference).
ContributorsSterner, Danielle (Author) / Wharton, Christopher (Christopher Mack), 1977- (Thesis advisor) / Johnston, Carol (Committee member) / Hall, Richard (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Windows based mobile application for m-health and environmental monitoring sensor devices were developed and tested. With the number of smartphone users exponentially increasing, the applications developed for m-health and environmental monitoring devices are easy to reach the general public, if the applications are simple, user-friendly and personalized. The sensing device

Windows based mobile application for m-health and environmental monitoring sensor devices were developed and tested. With the number of smartphone users exponentially increasing, the applications developed for m-health and environmental monitoring devices are easy to reach the general public, if the applications are simple, user-friendly and personalized. The sensing device uses Bluetooth to communicate with the smartphone, providing mobility to the user. Since the device is small and hand-held, the user can put his smartphone in his pocket, connected to the device in his hand and can move anywhere with it. The data processing performed in the applications is verified against standard off the shelf software, the results of the tests are discussed in this document. The user-interface is very simple and doesn't require many inputs from the user other than during the initial setting when they have to enter their personal information for the records. The m-health application can be used by doctors as well as by patients. The response of the application is very quick and hence the patients need not wait for a long time to see the results. The environmental monitoring device has a real-time plot displayed on the screen of the smartphone showing concentrations of total volatile organic compounds and airborne particle count in the environment at the location of the device. The programming was done with Microsoft Visual Studio and was written on VB.NET platform. On the applications, the smartphone receives data as raw binary bytes from the device via Bluetooth and this data is processed to obtain the final result. The final result is the concentration of Nitric Oxide in ppb in the Asthma Analyzer device. In the environmental monitoring device, the final result is the concentration of total Volatile Organic Compounds and the count of airborne Particles.
ContributorsGanesan, Srisivapriya (Author) / Tao, Nongjian (Thesis advisor) / Zhang, Yanchao (Committee member) / Tsow, Tsing (Committee member) / Arizona State University (Publisher)
Created2012