Digital Communications and Networking Commons^™

A Memory-Centric Customizable Domain-Specific Fpga Overlay For Accelerating Machine Learning Applications, Atiyehsadat Panahi

Graduate Theses and Dissertations

Low latency inferencing is of paramount importance to a wide range of real time and userfacing Machine Learning (ML) applications. Field Programmable Gate Arrays (FPGAs) offer unique advantages in delivering low latency as well as energy efficient accelertors for low latency inferencing. Unfortunately, creating machine learning accelerators in FPGAs is not easy, requiring the use of vendor specific CAD tools and low level digital and hardware microarchitecture design knowledge that the majority of ML researchers do not possess. The continued refinement of High Level Synthesis (HLS) tools can reduce but not eliminate the need for hardware-specific design knowledge. The designs …

A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur

Graduate Theses and Dissertations

Rapid and accurate damage assessment is crucial to minimize downtime in critical infrastructure. Dependency on modern technology requires fast and consistent techniques to prevent damage from spreading while also minimizing the impact of damage on system users. One technique to assist in assessment is data lineage, which involves tracing a history of dependencies for data items. The goal of this thesis is to present one novel model and an algorithm that uses data lineage with the goal of being fast and accurate. In function this model operates as a directed graph, with the vertices being data items and edges representing …

Modeling Damage Spread, Assessment, And Recovery Of Critical Systems, Justin Burns

Graduate Theses and Dissertations

Critical infrastructure systems have recently become more vulnerable to attacks on their data systems through internet connectivity. If an attacker is successful in breaching a system’s defenses, it is imperative that operations are restored to the system as quickly as possible. This thesis focuses on damage assessment and recovery following an attack. A literature review is first conducted on work done in both database protection and critical infrastructure protection, then the thesis defines how damage affects the relationships between data and software. Then, the thesis proposes a model using a graph construction to show the cascading affects within a system …

Signal Processing And Data Analysis For Real-Time Intermodal Freight Classification Through A Multimodal Sensor System., Enrique J. Sanchez Headley

Graduate Theses and Dissertations

Identifying freight patterns in transit is a common need among commercial and municipal entities. For example, the allocation of resources among Departments of Transportation is often predicated on an understanding of freight patterns along major highways. There exist multiple sensor systems to detect and count vehicles at areas of interest. Many of these sensors are limited in their ability to detect more specific features of vehicles in traffic or are unable to perform well in adverse weather conditions. Despite this limitation, to date there is little comparative analysis among Laser Imaging and Detection and Ranging (LIDAR) sensors for freight detection …

Privacy-Preserving Cloud-Assisted Data Analytics, Wei Bao

Graduate Theses and Dissertations

Nowadays industries are collecting a massive and exponentially growing amount of data that can be utilized to extract useful insights for improving various aspects of our life. Data analytics (e.g., via the use of machine learning) has been extensively applied to make important decisions in various real world applications. However, it is challenging for resource-limited clients to analyze their data in an efficient way when its scale is large. Additionally, the data resources are increasingly distributed among different owners. Nonetheless, users' data may contain private information that needs to be protected.

Cloud computing has become more and more popular in …

Securing Fog Federation From Behavior Of Rogue Nodes, Mohammed Saleh H. Alshehri

Graduate Theses and Dissertations

As the technological revolution advanced information security evolved with an increased need for confidential data protection on the internet. Individuals and organizations typically prefer outsourcing their confidential data to the cloud for processing and storage. As promising as the cloud computing paradigm is, it creates challenges; everything from data security to time latency issues with data computation and delivery to end-users. In response to these challenges CISCO introduced the fog computing paradigm in 2012. The intent was to overcome issues such as time latency and communication overhead and to bring computing and storage resources close to the ground and the …

Development Of A Reference Design For Intrusion Detection Using Neural Networks For A Smart Inverter, Ammar Mohammad Khan

Graduate Theses and Dissertations

The purpose of this thesis is to develop a reference design for a base level implementation of an intrusion detection module using artificial neural networks that is deployed onto an inverter and runs on live data for cybersecurity purposes, leveraging the latest deep learning algorithms and tools. Cybersecurity in the smart grid industry focuses on maintaining optimal standards of security in the system and a key component of this is being able to detect cyberattacks. Although researchers and engineers aim to design such devices with embedded security, attacks can and do still occur. The foundation for eventually mitigating these attacks …

Extracting Social Network From Literary Prose, Tarana Tasmin Bipasha

Graduate Theses and Dissertations

This thesis develops an approach to extract social networks from literary prose, namely, Jane Austen’s published novels from eighteenth- and nineteenth- century. Dialogue interaction plays a key role while we derive the networks, thus our technique relies upon our ability to determine when two characters are in conversation. Our process involves encoding plain literary text into the Text Encoding Initiative’s (TEI) XML format, character name identification, conversation and co-occurrence detection, and social network construction. Previous work in social network construction for literature have focused on drama, specifically manually TEI-encoded Shakespearean plays in which character interactions are much easier to track …

Smart Surge Irrigation Using Microcontroller Based Embedded Systems And Internet Of Things, Prashant Dinkar Borhade

Graduate Theses and Dissertations

Surge Irrigation is a type of furrow irrigation and one of many efficient irrigation techniques. It is one of the economical techniques and requires minimum labor for monitoring it. In surge irrigation, water is applied intermittently to a field to achieve uniform distribution of water along the furrows, which is important while irrigating, as it ensures that there is enough water near the root zone of the crop. The uneven distribution can cause a loss in crop productivity.

Surge irrigation uses a surge valve, which is an electro-mechanical device that irrigates a field. The commercial surge valves available on the …

Securing Soft Ips Against Hardware Trojan Insertion, Thao Phuong Le

Graduate Theses and Dissertations

Due to the increasing complexity of hardware designs, third-party hardware Intellectual Property (IP) blocks are often incorporated in order to alleviate the burden on hardware designers. However, the prevalence use of third-party IPs has raised security concerns such as Trojans inserted by attackers. Hardware Trojans in these soft IPs are extremely difficult to detect through functional testing and no single detection methodology has been able to completely address this issue. Based on a Register-Transfer Level (RTL) and gate-level soft IP analysis method named Structural Checking, this dissertation presents a hardware Trojan detection methodology and tool by detailing the implementation of …

Operating System Identification By Ipv6 Communication Using Machine Learning Ensembles, Adrian Ordorica

Graduate Theses and Dissertations

Operating system (OS) identification tools, sometimes called fingerprinting tools, are essential for the reconnaissance phase of penetration testing. While OS identification is traditionally performed by passive or active tools that use fingerprint databases, very little work has focused on using machine learning techniques. Moreover, significantly more work has focused on IPv4 than IPv6. We introduce a collaborative neural network ensemble that uses a unique voting system and a random forest ensemble to deliver accurate predictions. This approach uses IPv6 features as well as packet metadata features for OS identification. Our experiment shows that our approach is valid and we achieve …

Automatic User Profile Construction For A Personalized News Recommender System Using Twitter, Shiva Theja Reddy Gopidi

Graduate Theses and Dissertations

Modern society has now grown accustomed to reading online or digital news. However, the huge corpus of information available online poses a challenge to users when trying to find relevant articles. A hybrid system “Personalized News Recommender Using Twitter’ has been developed to recommend articles to a user based on the popularity of the articles and also the profile of the user. The hybrid system is a fusion of a collaborative recommender system developed using tweets from the “Twitter” public timeline and a content recommender system based the user’s past interests summarized in their conceptual user profile. In previous work, …

Reducing Multiple Access Interference In Broadband Multi-User Wireless Networks, Ali Nayef Alqatawneh

Graduate Theses and Dissertations

This dissertation is devoted to developing multiple access interference (MAI) reduction techniques for multi-carrier multi-user wireless communication networks.

In multi-carrier code division multiple access (MC-CDMA) systems, a full multipath diversity can be achieved by transmitting one symbol over multiple orthogonal subcarriers by means of spreading codes. However, in frequency selective fading channels, orthogonality among users can be destroyed leading to MAI. MAI represents the main obstacle to support large number of users in multi-user wireless systems. Consequently, MAI reduction becomes a main challenge when designing multi-carrier multi-user wireless networks. In this dissertation, first, we study MC-CDMA systems with different existing …

An Innovative Approach Towards Applying Chaum Mixing To Sms, Matthew Patrick Rothmeyer

Graduate Theses and Dissertations

Currently there are few user-friendly applications for anonymous communication across multiple platforms, leaving data that is often both personal and private vulnerable to malicious activity. Mobile devices such as smartphones are prime candidates for such an application as they are pervasive and have standardized communication protocols. Through the application of mixing techniques, these devices can provide anonymity for groups of individuals numbering 30 to 40 members. In this work, a Chaum mix inspired, smartphone based network that uses the Short Message Service (SMS) is described first in theory and then in implementation. This system leverages both techniques used by current …

Attitudes And Behaviors In Online Communities: Empirical Studies Of The Effects Of Social, Community, And Individual Characteristics, Richard Kumi

Graduate Theses and Dissertations

Online communities and communities of practice bring people together to promote and support shared goals and exchange information. Personal interactions are important to many of these communities and one of the important outcomes of personal interactions in online communities and communities of practice is user-generated content. The three essays in the current study examines behavior motivation in online communities and communities of practice to understand how Social and personal psychological factors, and user-generated influence attitudes, intentions and behaviors in online communities.

The first essay addresses two research questions. First, how does Social capital influence exchange and combination behaviors in online …

Identifying Emerging Researchers Using Social Network Analysis, Syed Masum Billah

Graduate Theses and Dissertations

Finding rising stars in academia early in their careers has many implications when hiring new faculty, applying for promotion, and/or requesting grants. Typically, the impact and productivity of a researcher are assessed by a popular measurement called the h-index that grows linearly with the academic age of a researcher. Therefore, h-indices of researchers in the early stages of their careers are almost uniformly low, making it difficult to identify those who will, in future, emerge as influential leaders in their field. To overcome this problem, we make use of Social network analysis to identify young researchers most likely to become …

Analysis Of Social Networks In A Virtual World, Gregory Thomas Stafford

Graduate Theses and Dissertations

As three-dimensional virtual environments become both more prevalent and more fragmented, studying how users are connected via their avatars and how they benefit from the virtual world community has become a significant area of research. An in-depth analysis of virtual world Social networks is needed to evaluate how users interact in virtual worlds, to better understand the impact of avatar Social networks on the virtual worlds, and to improve future online Social networks.

Our current efforts are focused on building and exploring the Social network aspects of virtual worlds. In this thesis, we build a Social network of avatars based …

Extending The Hybridthread Smp Model For Distributed Memory Systems, Eugene Anthony Cartwright Iii

Graduate Theses and Dissertations

Memory Hierarchy is of growing importance in system design today. As Moore's Law allows system designers to include more processors within their designs, data locality becomes a priority. Traditional multiprocessor systems on chip (MPSoC) experience difficulty scaling as the quantity of processors increases. This challenge is common behavior of memory accesses in a shared memory environment and causes a decrease in memory bandwidth as processor numbers increase. In order to provide the necessary levels of scalability, the computer architecture community has sought to decentralize memory accesses by distributing memory throughout the system. Distributed memory offers greater bandwidth due to decoupled …

Location-Aware Traffic Management On Mobile Phones, Sarath Krishna Mandava

Graduate Theses and Dissertations

The growing number of mobile phone users is a primary cause of congestion in cellular networks. Therefore, cellular network providers have turned to expensive and differentiated data plans. Unfortunately, as the number of smartphone users keeps increasing, changing data plans only provides a temporary solution. A more permanent solution is offloading 3G traffic to networks in orthogonal frequency bands. One such plausible network is open Wi-Fi, which is free by definition. As Wi-Fi networks become ubiquitous, there are several areas where there is simultaneous Wi-Fi and 3G coverage. In this thesis, we study the feasibility of offloading 3G traffic to …

Application Of The Empirical Mode Decomposition On The Characterization And Forecasting Of The Arrival Data Of An Enterprise Cluster, Linh Bao Ngo

Graduate Theses and Dissertations

Characterization and forecasting are two important processes in capacity planning. While they are closely related, their approaches have been different. In this research, a decomposition method called Empirical Mode Decomposition (EMD) has been applied as a preprocessing tool in order to bridge the input of both characterization and forecasting processes of the job arrivals of an enterprise cluster. Based on the facts that an enterprise cluster follows a standard preset working schedule and that EMD has the capability to extract hidden patterns within a data stream, we have developed a set of procedures that can preprocess the data for characterization …