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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
ABSTRACT This study evaluated the LoseIt Smart Phone app by Fit Now Inc. for nutritional quality among users during an 8 week behavioral modification weight loss protocol. All participants owned smart phones and were cluster randomized to either a control group using paper and pencil record keeping, a memo grou

ABSTRACT This study evaluated the LoseIt Smart Phone app by Fit Now Inc. for nutritional quality among users during an 8 week behavioral modification weight loss protocol. All participants owned smart phones and were cluster randomized to either a control group using paper and pencil record keeping, a memo group using a memo function on their smart phones, or the LoseIt app group which was composed of the participants who owned iPhones. Thirty one participants completed the study protocol: 10 participants from the LoseIt app group, 10 participants from the memo group, and 11 participants from the paper and pencil group. Food records were analyzed using Food Processor by ESHA and the nutritional quality was scored using the Healthy Eating Index - 2005 (HEI-2005). Scores were compared using One-Way ANOVA with no significant changes in any category across all groups. Non-parametric statistics were then used to determine changes between combined memo and paper and pencil groups and the LoseIt app group as the memo and paper and pencil group received live counseling at biweekly intervals and the LoseIt group did not. No significant difference was found in HEI scores across all categories, however a trend was noted for total HEI score with higher scores among the memo and paper and pencil group participants p=0.091. Conclusion, no significant difference was detected between users of the smart phone app LoseIt and memo and paper and pencil groups. More research is needed to determine the impact of in-person counseling versus user feedback provided with the LoseIt smart phone app.
ContributorsCowan, David Kevin (Author) / Johnston, Carol (Thesis advisor) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Mayol-Kreiser, Sandra (Committee member) / Arizona State University (Publisher)
Created2011
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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

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
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Description
Background: Smartphone diet tracking applications (apps) are increasing in popularity but may not adequately address the important concerns of proper intake and of diet quality. Two novel weight loss apps were designed based on the popular dietary frameworks: MyPlate and FoodLists. MyPlate, the dietary guidelines put forth by

Background: Smartphone diet tracking applications (apps) are increasing in popularity but may not adequately address the important concerns of proper intake and of diet quality. Two novel weight loss apps were designed based on the popular dietary frameworks: MyPlate and FoodLists. MyPlate, the dietary guidelines put forth by the U.S. government, encourages a balanced diet from five primary food groups, but does not specify intake limits. The Food Lists set upper intake limits on all food groups except vegetables, and these guidelines extend to include fats, sweets, and alcohol.

Objective: The purpose of this randomized controlled trial was to determine whether adherence to a weight loss app providing intake limits and more food group detail (the Food Lists app) facilitated more weight loss and better diet quality than adherence to a weight loss app based on the MyPlate platform. An additional objective was to examine whether higher app adherence would lead to greater weight loss.

Design: Thirty seven adults from a campus population were recruited, randomized, and instructed to follow either the Food Lists app (N=20) or the MyPlate app (N=17) for eight weeks. Subjects received one 15 minute session of diet and app training at baseline, and their use of the app was tracked daily. Body mass was measured at baseline and post-test.

Participants/setting: Healthy adults from a university campus population in downtown Phoenix, Arizona with BMI 24 to 40, medically stable, and who owned a smartphone.

Main outcome measures: Outcome measures included weight change, days of adherence, and diet quality change. Secondary measures included BMI, fat %, and waist circumference.

Statistical analysis: Descriptive statistics (means and standard errors); Repeated measures ANOVAs analyzing weight, diet quality, and BMI; Pearson and Spearman correlations analyzing adherence and weight loss.

Results: Repeated measures ANOVAs and correlations revealed no significant mean differences in primary outcome variables of weight loss, adherence, or diet quality (P=0.140; P=0.790; P=0.278). However, there was a significant mean reduction of BMI favoring the group using the Food Lists app (P=0.041).

Conclusion: The findings strengthen the idea that intake limits and food group detail may be associated with weight loss. Further investigation is warranted to determine whether longer use of the Food Lists app can produce more significant dieting successes and encourage healthier behavioral outcomes.
ContributorsScholtz, Cameron (Author) / Johnston, Carol (Thesis advisor) / Mayol-Kreiser, Sandra (Committee member) / Hekler, Eric (Committee member) / Arizona State University (Publisher)
Created2016
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Description
While various collision warning studies in driving have been conducted, only a handful of studies have investigated the effectiveness of warnings with a distracted driver. Across four experiments, the present study aimed to understand the apparent gap in the literature of distracted drivers and warning effectiveness, specifically by studying various

While various collision warning studies in driving have been conducted, only a handful of studies have investigated the effectiveness of warnings with a distracted driver. Across four experiments, the present study aimed to understand the apparent gap in the literature of distracted drivers and warning effectiveness, specifically by studying various warnings presented to drivers while they were operating a smart phone. Experiment One attempted to understand which smart phone tasks, (text vs image) or (self-paced vs other-paced) are the most distracting to a driver. Experiment Two compared the effectiveness of different smartphone based applications (app’s) for mitigating driver distraction. Experiment Three investigated the effects of informative auditory and tactile warnings which were designed to convey directional information to a distracted driver (moving towards or away). Lastly, Experiment Four extended the research into the area of autonomous driving by investigating the effectiveness of different auditory take-over request signals. Novel to both Experiment Three and Four was that the warnings were delivered from the source of the distraction (i.e., by either the sound triggered at the smart phone location or through a vibration given on the wrist of the hand holding the smart phone). This warning placement was an attempt to break the driver’s attentional focus on their smart phone and understand how to best re-orient the driver in order to improve the driver’s situational awareness (SA). The overall goal was to explore these novel methods of improved SA so drivers may more quickly and appropriately respond to a critical event.
ContributorsMcNabb, Jaimie Christine (Author) / Gray, Dr. Rob (Thesis advisor) / Branaghan, Dr. Russell (Committee member) / Becker, Dr. Vaughn (Committee member) / Arizona State University (Publisher)
Created2017