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THESIS DEFENSE Department of Computer Science and Engineering, University of South Carolina Candidate: Aniqua Z. Baset Advisor: Dr. Wenyuan Xu Date: Monday, April 6, 2015 Time: 9:00am Place: Swearingen, 3A00 (Dean’s Conference Room) Abstract Modern Home Automation (HA) systems handle all aspects of daily home living. Security breaches in these systems, therefore, can affect the homeowners in various ways, ranging from creating harassments to causing physical harm. As HA systems become a common feature of modern households, the robustness of these systems against external attack demand a thorough study. In this work, we explore the vulnerabilities of the state-of-the-art HA systems and, study their potential effect on the privacy and security of the homeowners. We investigated the Control4 and SmartThings HA systems as typical representatives of the HA systems available in the market. The devices in these systems communicate wirelessly using the ZigBee protocol, a prominent wireless technology in the HA field. Therefore, our study and findings can be extended to a wide range of HAs in the market. We discovered several vulnerabilities in the systems that allowed us to execute eavesdropping, spoofing and DoS attacks. We observed that it is possible to infer the types, location and activities of the devices in the home exploiting the uncovered vulnerabilities, which may lead to tracking homeowners’ activities and routine. We were also able to control home devices by injecting spoofed messages. In the end, we discussed some defense strategies that can mitigate the security and privacy risks of the HA systems we studied as well as the HA systems in general.

WIC meeting. April 2nd, 6pm, room 3A75: Raghav Badiger, Entrepreneur and Start up Guru. More Information.

DISSERTATION DEFENSE Department of Computer Science and Engineering, University of South Carolina Candidate: Shuai Jiang Advisor: Dr. Jijun Tang Date: Thursday, April 2, 2015 Time: 3:00pm Place: Swearingen, 3A00 (Dean’s Conference Room) Abstract Genome rearrangements are evolutionary events that shuffle genomic material. Since large-scale rearrangements happen rarely and have dramatic effect on the genomes, the evolutionary history between two genomes usually corresponds to a shortest rearrangement scenario (minimal number of rearrangements) between them. However, there may exist multiple shortest rearrangement scenarios between two genomes, making it difficult to find the true history. Furthermore, there also exist "complex" rearrangement operations such as transpositions (that cut off a segment of a chromosome and insert it into some other place in the genome), whose effect on the shortest rearrangement scenario is still unclear. There exist several rearrangement models that simplify the rearrangement analysis, such as multi-break (also known as k-breaks, k=2,3) and Double-Cut-and-Join, none of which is biologically adequate for analysis of transpositions among other types of genome rearrangements. In the first part of this dissertation, we employ the multi-break rearrangement model to study the shortest rearrangement scenarios between two genomes. We show the appearance of transpositions in the shortest 2-break scenarios and derive the upper and lower bounds of their proportion in such scenarios. The results imply that transpositions may exist in large proportion in shortest 2-break scenarios. Then we prove that the introduction of a relative large weight to transpositions cannot achieve its purpose of bounding the proportion of transpositions in shortest 3-break scenarios. The ability of finding a shortest rearrangement scenario can be used for reconstruction of ancestral genomes from the given genomes, so that the total numbers of rearrangements between ancestral genomes and given genomes is minimal. This problem is known to be NP-complete even in the "simplest" case of three genome, called the genome median problem. Currently, there exist several tools for reconstruction of ancestral genomes, such as Multiple Genome Rearrangements and Ancestors (MGRA). Most of them are limited to genomes on the same set of genes with each gene present in a single copy in every genome. This limitation makes these tools inapplicable for many important biological datasets or degrades the resolution of ancestral reconstructions in others. Furthermore even if the given genomes are linear (i.e., consist only of linear chromosomes), the ancestral genomes reconstructed by existing tools may contain circular chromosomes, which is biologically inadequate. In the second part of this dissertation, we present a next-generation tool MGRA2 that extends MGRA functionality to support gene insertions and deletions, making it applicable for more complex genomic datasets. We also propose an algorithm that uses the existing solution for ancestral genome reconstruction problem to obtain linear ancestral genomes in some optimal way.

It's that time again! Our friends at Hackerrank are helping us with another Code-a-thon, and I want you to be there! I will be posting more specifics as I find them, but here is the setup: 3 tiers: Beginner (145) Intermediate (146) Expert (240+) Each tier has it's own set of questions and prizes. Not sure what time we will be starting yet, but it will be overnight (3/27 - 3/28) The more people we get the more likely we are to be able to do this again! Invite your friends and come out! More Information at event page.

THESIS DEFENSE Department of Computer Science and Engineering, University of South Carolina Candidate: Surya Bhatt Advisor: Dr. Csilla Farkas Date: Tuesday, March 24, 2015 Time: 2:00pm Place: Swearingen (3A75) Abstract There’s a significant increase in online consumer forums. When customers set out to buy a product they have a preconceived idea about it. They mostly form the idea/expectation from print, audio/video advertisements, online reviews and word of mouth. There have been previous researches on how user generated content can be used to determine the market structure insights [Meeyoung Cha et. al. 2007]. The audio analysis is divided into two parts. One is linguistic research which focuses on the language and content of the input. The second one is paralinguistic which focuses on how words are spoken (prosodic effects). Our research focuses on comparing Brand positioning maps based on consumer reviews with and without linguistic audio analysis of advertisements and reviews. Our goal is to show that this hybrid approach helps us analyze the effectiveness of advertising on brand positioning maps. This approach shall also help us in making association graphs for a brand using words of perception/opinion flowing with that brand/product. Which may in turn assist companies in improving the focus of their advertisements in order to persuade the required set of crowd and drive the public perception.

DISSERTATION DEFENSE Department of Computer Science and Engineering, University of South Carolina Candidate: Ping Liu Advisor: Dr. Yan Tong Date: Monday, March 23, 2015 Time: 2:30pm Place: Swearingen, 3A75 Abstract As being characterized by various configurations of facial muscular movements, facial expression is the most natural and powerful means for human communications. A robust and accurate facial expression recognition system, which is with capabilities to automatically recognize facial activities in given images/videos, has applications in a wide range of areas. However, developing such an automatic system encounters several challenges. As a standard pattern recognition problem, facial expressions recognition (FER) consists of three major modules in training: feature learning/extraction, feature selection, and classifier construction. This research aims to improve the first two modules respectively, and furthermore integrate them in an iterative and unified way to enhance the final recognition performance. In order to improve the performance of feature learning, novel log transformed sparse coding features with a spatial pyramid structure are proposed to characterize nonrigid facial muscular movements with head movements. To select the most distinctive features in recognizing facial expressions, a framework based on kernel theory is proposed to choose facial regions and analyze their contributions to different target expressions. Moreover, to unify the three training stages, a model taking advantage of both deep learning and boosting theory is proposed, with the capability of learning hierarchical underlying patterns that describe the given images and automatically selecting the most important facial regions for facial expression analysis. The proposed methods have been validated on public databases including spontaneous facial expression database, which is collected under realistic environment including face pose variations and occlusions. The experimental results show that the proposed methods yield significant improvements in recognizing facial expressions. More than that, the significant performance improvement in cross-database validation demonstrates the good generality of our proposed methods.

DISSERTATION DEFENSE Department of Computer Science and Engineering, University of South Carolina Emerging Wireless Sensor Networks in Intertidal Zones and for Tracking Targets Candidate: Miao Xu Advisor: Dr. Wenyuan Xu Date: Monday, March 23, 2015 Time: 10:00am Place: Swearingen (3A00, Deans Conference Room) Abstract Wireless sensor networks (WSNs), which consist of a large number of low-power, low-cost sensor nodes, are promising because they can continuously and remotely monitor our surroundings with few human involvements. For example, we have witnessed sensor applications that monitor the habitat environment of wild animals or monitor the health condition of infrastructures. These traditional WSNs are typically used as monitoring applications and deployed at various terrestrials. In this dissertation, however, we examine two different types of 0emerging sensor applications, which are WSNs deployed in intertidal zones (IT-WSNs) and WSNs deployed for tracking targets (TT-WSNs). Alternately submerged and laid bare by tides, the wireless channels in IT-WSNs are intermittent and could be unavailable up to 24 hours, which makes IT-WSNs unique compared with terrestrial WSNs. In the first part of this dissertation, we examine some problems that are caused by the influence of tides. First, we study the time synchronization problem in IT-WSNs. Due to the intermittent wireless channels, traditional resynchronization schemes cannot be directly applied to IT-WSNs. To prolong the resynchronization interval, we propose a temperature-aware compensation scheme that continuously adjusts the clock locally without any resynchronization messages. Second, we examine the low-power embedded systems for the sensor nodes in IT-WSNs. Battery powered, the nodes in WSNs typically employ duty-cycling schemes to reduce the average power. To further reduce the power consumption, we study the channel-aware features for radio transceivers given that the channels are intermittent. We also propose to develop an automation platform that automatically finds the most power saving configuration of IO pins. Finally, we investigate environment-aware MAC protocols in Part I. Many existing WSNs are proposed for monitoring physical phenomena, but few of them study the applications for tracking targets. In the second part of this dissertation, we examine the TT-WSNs that are deployed for tracking a target such as some endangered animals. Since the data exchanged in TT-WSNs are typically associated with the target's location information, the data privacy is important to the users. In addition, once deployed, the networks are typically left unattended, which makes the privacy issue even more challenging. Although many cryptography-based solutions have been proposed to solve the problem, we are interested in non-cryptography schemes because cryptography-based methods cannot cope with node compromise. Based on the observation that message content is important in TT-WSNs, we propose a content-aware data dissemination scheme for TT-WSNs to achieve better data privacy and higher data availability with less energy cost.