Computer Engineering Commons^™

Digital Forensics For Investigating Control-Logic Attacks In Industrial Control Systems, Nauman Zubair

University of New Orleans Theses and Dissertations

Programmable logic controllers (PLC) are required to handle physical processes and thus crucial in critical infrastructures like power grids, nuclear facilities, and gas pipelines. Attacks on PLCs can have disastrous consequences, considering attacks like Stuxnet and TRISIS. Those attacks are examples of exploits where the attacker aims to inject into a target PLC malicious control logic, which engineering software compiles as a reliable code. When investigating a security incident, acquiring memory can provide valuable insight such as runtime system activities and memory-based artifacts which may contain the attacker's footprints. The existing memory acquisition tools for PLCs require a hardware-level debugging …

Parallel Algorithms For Scalable Graph Mining: Applications On Big Data And Machine Learning, Naw Safrin Sattar

University of New Orleans Theses and Dissertations

Parallel computing plays a crucial role in processing large-scale graph data. Complex network analysis is an exciting area of research for many applications in different scientific domains e.g., sociology, biology, online media, recommendation systems and many more. Graph mining is an area of interest with diverse problems from different domains of our daily life. Due to the advancement of data and computing technologies, graph data is growing at an enormous rate, for example, the number of links in social networks is growing every millisecond. Machine/Deep learning plays a significant role for technological accomplishments to work with big data in modern …

Ocean Wave Prediction And Characterization For Intelligent Maritime Transportation, Pujan Pokhrel

University of New Orleans Theses and Dissertations

The national Earth System Prediction (ESPC) initiative aims to develop the predictions
for the next generation predictions of atmosphere, ocean, and sea-ice interactions in the scale of days to decades. This dissertation seeks to demonstrate the methods we can use to improve the ESPC models, especially the ocean prediction model. In the application side of the weather forecasts, this dissertation explores imitation learning with constraints to solve combinatorial optimization problems, focusing on the weather routing of surface vessels. Prediction of ocean waves is essential for various purposes, including vessel routing, ocean energy harvesting, agriculture, etc. Since the machine learning approaches …

Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen

University of New Orleans Theses and Dissertations

Data reconstruction is significantly improved in terms of speed and accuracy by reliable data encoding fragment classification. To date, work on this problem has been successful with file structures of low entropy that contain sparse data, such as large tables or logs. Classifying compressed, encrypted, and random data that exhibit high entropy is an inherently difficult problem that requires more advanced classification approaches. We explore the ability of convolutional neural networks and word embeddings to classify deflate data encoding of high entropy file fragments after establishing ground truth using controlled datasets. Our model is designed to either successfully classify file …

Analysis Of Human Affect And Bug Patterns To Improve Software Quality And Security, Md Rakibul Islam

University of New Orleans Theses and Dissertations

The impact of software is ever increasing as more and more systems are being software operated. Despite the usefulness of software, many instances software failures have been causing tremendous losses in lives and dollars. Software failures take place because of bugs (i.e., faults) in the software systems. These bugs cause the program to malfunction or crash and expose security vulnerabilities exploitable by malicious hackers.

Studies confirm that software defects and vulnerabilities appear in source code largely due to the human mistakes and errors of the developers. Human performance is impacted by the underlying development process and human affects, such as …

Scalable Community Detection Using Distributed Louvain Algorithm, Naw Safrin Sattar

University of New Orleans Theses and Dissertations

Community detection (or clustering) in large-scale graph is an important problem in graph mining. Communities reveal interesting characteristics of a network. Louvain is an efficient sequential algorithm but fails to scale emerging large-scale data. Developing distributed-memory parallel algorithms is challenging because of inter-process communication and load-balancing issues. In this work, we design a shared memory-based algorithm using OpenMP, which shows a 4-fold speedup but is limited to available physical cores. Our second algorithm is an MPI-based parallel algorithm that scales to a moderate number of processors. We also implement a hybrid algorithm combining both. Finally, we incorporate dynamic load-balancing in …

Stackcbpred: A Stacking Based Prediction Of Protein-Carbohydrate Binding Sites From Sequence, Suraj Gattani

University of New Orleans Theses and Dissertations

Carbohydrate-binding proteins play vital roles in many vital biological processes and study of these interactions, at residue level, are useful in treating many critical diseases. Analyzing the local sequential environments of the binding and non-binding regions to predict the protein-carbohydrate binding sites is one of the challenging problems in molecular and computational biology. Prediction of such binding sites, directly from sequences, using computational methods, can be useful to fast annotate the binding sites and guide the experimental process. Because the number of carbohydrate-binding residues is significantly lower than non-carbohydrate-binding residues, most of the methods developed are biased towards over predicting …

Improved Iterative Truncated Arithmetic Mean Filter, Prathyusha Surampudi Venkata

University of New Orleans Theses and Dissertations

This thesis discusses image processing and filtering techniques with emphasis on Mean filter, Median filter, and different versions of the Iterative Truncated Arithmetic Mean (ITM) filter. Specifically, we review in detail the ITM algorithms (ITM1 and ITM2) proposed by Xudong Jiang. Although filtering is capable of reducing noise in an image, it usually also results in smoothening or some other form of distortion of image edges and file details. Therefore, maintaining a proper trade off between noise reduction and edge/detail distortion is key. In this thesis, an improvement over Xudong Jiang’s ITM filters, namely ITM3, has been proposed and tested …

User's Manual For Tardigrade Risk Assessment, Alexis M. Shook

University of New Orleans Theses and Dissertations

This user-guide provides instructions for operating Tardigrade 1.1.3, a cybersecurity software for Nollysoft, LLC. This guide instructs users step-by-step on how to set security controls, risk assessments, and administrative maintenance. Tardigrade 1.1.3 is a Risk Assessment Enterprise that evaluates the risk level of corporations and offers solutions to any security gaps within an organization. Tardigrade 1.1.3 is a role-based software that operates through three modules, Cybersecurity Assessment, Internal Control, and Security Requirement Traceability Matrix.

Remote Monitoring Of Cherry Wetness Using A Leaf Wetness Sensor And A Wireless Sensor Network, Shyla Clark

University of New Orleans Theses and Dissertations

To get the best prices, sweet cherry growers must supply blemish-free fruit. Unfortunately, mature cherries have a fragile composition, rendering them susceptible to damage from heat, wind, birds, and rain. Rain is particularly devastating, because cherries split when they absorb too much water. Since rainstorms are common in the otherwise arid regions where most cherries are grown, growers must have a system for quickly deploying rain removal methods. The current industry solution relies on human observation and implementation, which is error-prone and costly. This project proposes an automated cherry wetness system using a Decagon Devices leaf wetness sensor (LWS) and …

Advanced Text Analytics And Machine Learning Approach For Document Classification, Chaitanya Anne

University of New Orleans Theses and Dissertations

Text classification is used in information extraction and retrieval from a given text, and text classification has been considered as an important step to manage a vast number of records given in digital form that is far-reaching and expanding. This thesis addresses patent document classification problem into fifteen different categories or classes, where some classes overlap with other classes for practical reasons. For the development of the classification model using machine learning techniques, useful features have been extracted from the given documents. The features are used to classify patent document as well as to generate useful tag-words. The overall objective …

Improving A Particle Swarm Optimization-Based Clustering Method, Sharif Shahadat

University of New Orleans Theses and Dissertations

This thesis discusses clustering related works with emphasis on Particle Swarm Optimization (PSO) principles. Specifically, we review in detail the PSO clustering algorithm proposed by Van Der Merwe & Engelbrecht, the particle swarm clustering (PSC) algorithm proposed by Cohen & de Castro, Szabo’s modified PSC (mPSC), and Georgieva & Engelbrecht’s Cooperative-Multi-Population PSO (CMPSO). In this thesis, an improvement over Van Der Merwe & Engelbrecht’s PSO clustering has been proposed and tested for standard datasets. The improvements observed in those experiments vary from slight to moderate, both in terms of minimizing the cost function, and in terms of run time.

Spice: A Software Tool For Studying End-User’S Insecure Cyber Behavior And Personality-Traits, Anjila Tamrakar

University of New Orleans Theses and Dissertations

Insecure cyber behavior of end users may expose their computers to cyber-attack. A first step to improve their cyber behavior is to identify their tendency toward insecure cyber behavior. Unfortunately, not much work has been done in this area. In particular, the relationship between end users cyber behavior and their personality traits is much less explored. This paper presents a comprehensive review of a newly developed, easily configurable, and flexible software SPICE for psychologist and cognitive scientists to study personality traits and insecure cyber behavior of end users. The software utilizes well-established cognitive methods (such as dot-probe) to identify number …

A Study Of Three Paradigms For Storing Geospatial Data: Distributed-Cloud Model, Relational Database, And Indexed Flat File, Matthew A. Toups

University of New Orleans Theses and Dissertations

Geographic Information Systems (GIS) and related applications of geospatial data were once a small software niche; today nearly all Internet and mobile users utilize some sort of mapping or location-aware software. This widespread use reaches beyond mere consumption of geodata; projects like OpenStreetMap (OSM) represent a new source of geodata production, sometimes dubbed “Volunteered Geographic Information.” The volume of geodata produced and the user demand for geodata will surely continue to grow, so the storage and query techniques for geospatial data must evolve accordingly.

This thesis compares three paradigms for systems that manage vector data. Over the past few decades …

Api-Based Acquisition Of Evidence From Cloud Storage Providers, Andres E. Barreto

University of New Orleans Theses and Dissertations

Cloud computing and cloud storage services, in particular, pose a new challenge to digital forensic investigations. Currently, evidence acquisition for such services still follows the traditional approach of collecting artifacts on a client device. In this work, we show that such an approach not only requires upfront substantial investment in reverse engineering each service, but is also inherently incomplete as it misses prior versions of the artifacts, as well as cloud-only artifacts that do not have standard serialized representations on the client.

In this work, we introduce the concept of API-based evidence acquisition for cloud services, which addresses these concerns …

A Balanced Secondary Structure Predictor, Md Nasrul Islam

University of New Orleans Theses and Dissertations

Secondary structure (SS) refers to the local spatial organization of the polypeptide backbone atoms of a protein. Accurate prediction of SS is a vital clue to resolve the 3D structure of protein. SS has three different components- helix (H), beta (E) and coil (C). Most SS predictors are imbalanced as their accuracy in predicting helix and coil are high, however significantly low in the beta. The objective of this thesis is to develop a balanced SS predictor which achieves good accuracies in all three SS components. We proposed a novel approach to solve this problem by combining a genetic algorithm …

An Empirical Study Of Semantic Similarity In Wordnet And Word2vec, Abram Handler

University of New Orleans Theses and Dissertations

This thesis performs an empirical analysis of Word2Vec by comparing its output to WordNet, a well-known, human-curated lexical database. It finds that Word2Vec tends to uncover more of certain types of semantic relations than others -- with Word2Vec returning more hypernyms, synonomyns and hyponyms than hyponyms or holonyms. It also shows the probability that neighbors separated by a given cosine distance in Word2Vec are semantically related in WordNet. This result both adds to our understanding of the still-unknown Word2Vec and helps to benchmark new semantic tools built from word vectors.

Analysis And Detection Of Heap-Based Malwares Using Introspection In A Virtualized Environment, Salman Javaid

University of New Orleans Theses and Dissertations

Malware detection and analysis is a major part of computer security. There is an arm race between security experts and malware developers to develop various techniques to secure computer systems and to find ways to circumvent these security methods. In recent years process heap-based attacks have increased significantly. These attacks exploit the system under attack via the heap, typically by using a heap spraying attack. The main drawback with existing techniques is that they either consume too many resources or are complicated to implement. Our work in this thesis focuses on new methods which offloads process heap analysis for guest …

Efficient Fpga Architectures For Separable Filters And Logarithmic Multipliers And Automation Of Fish Feature Extraction Using Gabor Filters, Arjun Kumar Joginipelly

University of New Orleans Theses and Dissertations

Convolution and multiplication operations in the filtering process can be optimized by minimizing the resource utilization using Field Programmable Gate Arrays (FPGA) and separable filter kernels. An FPGA architecture for separable convolution is proposed to achieve reduction of on-chip resource utilization and external memory bandwidth for a given processing rate of the convolution unit.

Multiplication in integer number system can be optimized in terms of resources, operation time and power consumption by converting to logarithmic domain. To achieve this, a method altering the filter weights is proposed and implemented for error reduction. The results obtained depict significant error reduction when …

Forensic Analysis Of Whatsapp On Android Smartphones, Neha S. Thakur

University of New Orleans Theses and Dissertations

Android forensics has evolved over time offering significant opportunities and exciting challenges. On one hand, being an open source platform Android is giving developers the freedom to contribute to the rapid growth of the Android market whereas on the other hand Android users may not be aware of the security and privacy implications of installing these applications on their phones. Users may assume that a password-locked device protects their personal information, but applications may retain private information on devices, in ways that users might not anticipate. In this thesis we will be concentrating on one such application called 'WhatsApp', a …

Data Exploration Interface For Digital Forensics, Varun Dontula

University of New Orleans Theses and Dissertations

The fast capacity growth of cheap storage devices presents an ever-growing problem of scale for digital forensic investigations. One aspect of scale problem in the forensic process is the need for new approaches to visually presenting and analyzing large amounts of data. Current generation of tools universally employ three basic GUI components—trees, tables, and viewers—to present all relevant information. This approach is not scalable as increasing the size of the input data leads to a proportional increase in the amount of data presented to the analyst.

We present an alternative approach, which leverages data visualization techniques to provide a more …