CS Theses & Dissertations 2017

For 2017 graduation dates (in alphabetical order by last name):

An intelligent multi-agent based detection framework for classification of android malware
Alam, Mohammed Shahidul
DOI : 10.14288/1.0340265
URI : http://hdl.handle.net/2429/59914
Degree : Doctor of Philosophy - PhD
Graduation Date : 2017-02

Smartphones play an important role in our day to day activities. Some of them include monitoring our health such as eating habits, sleep patterns and exercise schedule. The Android mobile operating system developed by Google is currently the most popular operating system for such smart devices. It is also the most vulnerable device due to its open nature of software installation, ability to dynamically load code during runtime, and lack of updates to known vulnerabilities even on popular versions of the system. Thus, securing such devices from malware that targets user privacy and monetary resources is paramount. In this thesis, we developed a context-aware multi-agent based framework targeted towards protecting Android devices. A malware detection technique has to be context-aware due to limited battery resources of mobile devices. In some cases however, battery utilization might become secondary. This includes scenarios where detection accuracy is given a higher priority over battery utilization. Thus, a detection framework has to be intelligent and flexible. To reach this goal, our framework relies on building multiple scalable context based models, and observing the behaviour patterns of Android devices by comparing to relevant pre-built models. We make use of machine learning classifiers that are more scalable to help classify features that could be used to detect malware by behaviour analysis. In this framework, the expensive analysis components utilizing machine learning algorithms are pushed to server side, while agents on the Android client are used mainly for context-aware feature gathering to transmit the information to server side classifiers for analysis, and to receive classification results from the server side agents.

Feature Recommender : a large-scale in-situ study of proactive software feature recommendations
Ardekani, Kamyar
DOI : 10.14288/1.0339868
URI : http : //hdl.handle.net/2429/59761
Degree : Master of Science - MSc
Graduation Date : 2017-02

Cross-platform data integrity and confidentiality with graduated access control
Chen, Feifan
DOI: 10.14288/1.0340667
UR I: http://hdl.handle.net/2429/60265
Degree : Master of Science - MSc
Graduation Date : 2017-02

Extending systems with virtual hardware aggregation
Cully, Brendan
DOI : 10.14288/1.0342739
URI : http : //hdl.handle.net/2429/60579
Degree : Doctor of Philosophy - PhD
Graduation Date : 2017-05

Hardware has physical limitations. It has fixed performance limits, and may fail. Applications suffer from the limitations of the physical hardware on which they run. Making applications able to take advantage of multiple hardware instances to avoid these limitations is complex. Since this effort must be expended for every application, it is impractical for most of them. In this thesis, we show that we can aggregate multiple physical machines at the virtual machine interface, allowing them to transcend the limitations of single machines without changing the applications themselves.

Improve classification on infrequent discourse relations via training data enrichment
Jiang, Kailang
DOI : 10.14288/1.0340024
URI : http : //hdl.handle.net/2429/59844
Degree : Master of Science - MSc
Graduation Date : 2017-02

Distributed linear programming with Apache Spark
Mohyedin Kermani, Ehsan
DOI : 10.14288/1.0340337
URI : http://hdl.handle.net/2429/59990
Degree : Master of Science - MSc
Graduation Date : 2017-02

Efficient feasibility checking in reverse clock auctions for radio spectrum
Newman, Neil
DOI : 10.14288/1.0340850
URI : http : //hdl.handle.net/2429/60376
Degree : Master of Science - MSc
Graduation Date : 2017-02

Haptic experience design : tools, techniques, and process
Schneider, Oliver Stirling
DOI : 10.14288/1.0340617
URI : http : //hdl.handle.net/2429/60233
Degree : Doctor of Philosophy - PhD
Graduation Date : 2017-02

Haptic technology, which engages the sense of touch, offers promising benefits for a variety of interactions including low-attention displays, emotionally-aware interfaces, and augmented media experiences. Despite an increasing presence of physical devices in commercial and research applications, there is still little support for the design of engaging haptic sensations. Previous literature has focused on the significant challenges of technological capabilities or physical realism rather than on supporting experience design. In this dissertation, we study how to design, build, and evaluate interactive software to support haptic experience design (HaXD). We define HaXD and iteratively design three vibrotactile effect authoring tools, each a case study covering a different user population, vibrotactile device, and design challenge, and use them to observe specific aspects of HaXD with their target users. We make these in-depth findings more robust in two ways :  generalizing results to a breadth of use cases with focused design projects, and grounding them with expert haptic designers through interviews and a workshop. Our findings 1) describe HaXD, including processes, strategies, and challenges; and 2) present guidelines on designing, building, and evaluating interactive software that facillitates HaXD. When characterizing HaXD processes, strategies, and challenges, we show that experience design is already practiced with haptic technology, but faces unique considerations compared to other modalities. We identify four design activities that must be explicitly supported :  sketching, refining, browsing, and sharing. We find and develop strategies to accommodate the wide variety of haptic devices. We articulate approaches for designing meaning with haptic experiences, and finally, highlight a need for supporting adaptable interfaces. When informing the design, implementation, and evaluation of HaXD tools, we discover critical features, including a need for improved online deployment and community support. We present steps to develop both existing and future research software into a mature suite of HaXD tools, and reflect upon evaluation methods. By characterizing HaXD and informing supportive tools, we make a first step towards establishing HaXD as its own field, akin to graphic and sound design.

Not able to resist the urge : social insider attacks on Facebook
Usmani, Wali Ahmed
DOI : 10.14288/1.0340682
URI : http : //hdl.handle.net/2429/60294
Degree : Master of Science - MSc
Graduation Date : 2017-02

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