Computer Engineering Commons^™

Bytewise Approximate Matching: The Good, The Bad, And The Unknown, Vikram S. Harichandran, Frank Breitinger, Ibrahim Baggili

Journal of Digital Forensics, Security and Law

Hash functions are established and well-known in digital forensics, where they are commonly used for proving integrity and file identification (i.e., hash all files on a seized device and compare the fingerprints against a reference database). However, with respect to the latter operation, an active adversary can easily overcome this approach because traditional hashes are designed to be sensitive to altering an input; output will significantly change if a single bit is flipped. Therefore, researchers developed approximate matching, which is a rather new, less prominent area but was conceived as a more robust counterpart to traditional hashing. Since the conception …

Security Analysis Of Mvhash-B Similarity Hashing, Donghoon Chang, Somitra Sanadhya, Monika Singh

Journal of Digital Forensics, Security and Law

In the era of big data, the volume of digital data is increasing rapidly, causing new challenges for investigators to examine the same in a reasonable amount of time. A major requirement of modern forensic investigation is the ability to perform automatic filtering of correlated data, and thereby reducing and focusing the manual effort of the investigator. Approximate matching is a technique to find “closeness” between two digital artifacts. mvHash-B is a well-known approximate matching scheme used for finding similarity between two digital objects and produces a ‘score of similarity’ on a scale of 0 to 100. However, no security …

An Automated Approach For Digital Forensic Analysis Of Heterogeneous Big Data, Hussam Mohammed, Nathan Clarke, Fudong Li

Journal of Digital Forensics, Security and Law

The major challenges with big data examination and analysis are volume, complex interdependence across content, and heterogeneity. The examination and analysis phases are considered essential to a digital forensics process. However, traditional techniques for the forensic investigation use one or more forensic tools to examine and analyse each resource. In addition, when multiple resources are included in one case, there is an inability to cross-correlate findings which often leads to inefficiencies in processing and identifying evidence. Furthermore, most current forensics tools cannot cope with large volumes of data. This paper develops a novel framework for digital forensic analysis of heterogeneous …

On Efficiency Of Distributed Password Recovery, Radek Hranický, Martin Holkovič, Petr Matoušek

Journal of Digital Forensics, Security and Law

One of the major challenges in digital forensics today is data encryption. Due to the leaked information about unlawful sniffing, many users decided to protect their data by encryption. In case of criminal activities, forensic experts are challenged how to decipher suspect's data that are subject to investigation. A common method how to overcome password-based protection is a brute force password recovery using GPU-accelerated hardware. This approach seems to be expensive. This paper presents an alternative approach using task distribution based on BOINC platform. The cost, time and energy efficiency of this approach is discussed and compared to the GPU-based …

Towards Syntactic Approximate Matching - A Pre-Processing Experiment, Doowon Jeong, Frank Breitinger, Hari Kang, Sangjin Lee

Journal of Digital Forensics, Security and Law

Over the past few years the popularity of approximate matching algorithms (a.k.a. fuzzy hashing) has increased. Especially within the area of bytewise approximate matching, several algorithms were published, tested and improved. It has been shown that these algorithms are powerful, however they are sometimes too precise for real world investigations. That is, even very small commonalities (e.g., in the header of a le) can cause a match. While this is a desired property, it may also lead to unwanted results. In this paper we show that by using simple pre-processing, we signicantly can in uence the outcome. Although our test …

Revealing Malicious Contents Hidden In The Internet, Muhammad Nazmus Sakib

Theses and Dissertations

In this age of ubiquitous communication in which we can stay constantly connected with the rest of the world, for most of the part, we have to be grateful for one particular invention - the Internet. But as the popularity of Internet connectivity grows, it has become a very dangerous place where objects of malicious content and intent can be hidden in plain sight. In this dissertation, we investigate different ways to detect and capture these malicious contents hidden in the Internet. First, we propose an automated system that mimics high-risk browsing activities such as clicking on suspicious online ads, …

Mitigating Interference During Virtual Machine Live Migration Through Storage Offloading, Morgan S. Stuart

Theses and Dissertations

Today's cloud landscape has evolved computing infrastructure into a dynamic, high utilization, service-oriented paradigm. This shift has enabled the commoditization of large-scale storage and distributed computation, allowing engineers to tackle previously untenable problems without large upfront investment. A key enabler of flexibility in the cloud is the ability to transfer running virtual machines across subnets or even datacenters using live migration. However, live migration can be a costly process, one that has the potential to interfere with other applications not involved with the migration. This work investigates storage interference through experimentation with real-world systems and well-established benchmarks. In order to …

Mainframe Relevance In Modern It: How A 50+ Year Old Computing Platform Can Still Play A Key Role In Today’S Businesses, Ian Thomas Newcombe

Honors Theses and Capstones

No abstract provided.

Using Adaptive Thresholding And Skewness Correction To Detect Gray Areas In Melanoma In Situ Images, Jason R. Hagerty

Masters Theses

"The incidence of melanoma in situ (MIS) is growing significantly. Detection at the MIS stage provides the highest cure rate for melanoma, but reliable detection of MIS with dermoscopy alone is not yet possible. Adjunct dermoscopic instrumentation using digital image analysis may allow more accurate detection of MIS. Gray areas are a critical component of MIS diagnosis, but automatic detection of these areas remains difficult because similar gray areas are also found in benign lesions. This paper proposes a novel adaptive thresholding technique for automatically detecting gray areas specific to MIS. The proposed model uses only MIS dermoscopic images to …

Numerical Analysis Of Flexural Slip During Viscoelastic Buckle Folding, Davi Rodrigues Damasceno

Masters Theses

"Flexural slip is considered to be an important folding mechanism contributing in the development of different folds such as chevron, and kink-band buckle folds. Various filed studies have provided a general conceptual and qualitative understanding of flexural slip. However, quantitative evidence of the importance of the flexural slip mechanism during fold evolution is sparse, as the actual amount of surface parallel displacement, and timing, is difficult to measure accurately, due to the lack of suitable strain markers.

In this study 2D finite element analysis is used to overcome these disadvantages and to simulate flexural slip during viscoelastic buckle folding. Variations …

Monitoring Voip Speech Quality For Chopped And Clipped Speech, Andrew Hines, Jan Skoglund, Anil C. Kokaram, Naomi Harte

Articles

No abstract provided.

A New Educational Mobile Devices Platform For Social Inclusion In Tanzania, Fredrick Mtenzi

Articles

Abstract— It is evident that advances in technology has led to improvement in societal wellbeing. In this paper we demonstrate how mobile phones are used in providing reliable and quality education to students in disadvantaged areas of Tanzania. The main contribution is on leveraging on the success that Tanzania has had on using mobile banking to the un-banked population. These lessons are adapted to the education sector, where clever/smart integration of existing disruptive technologies such as mobile phones and social networks are be used to provide access to high quality educational contents. Further, the paper shows how educational content can …

Modeling Mental Workload Via Rule-Based Expert System: A Comparison With Nasa-Tlx & Workload Profile, Lucas Rizzo, Sarah Jane Delany, Pierpaolo Dondio, Luca Longo

Conference papers

In the last few decades several fields have made use of the construct of human mental workload (MWL) for system and task design as well as for assessing human performance. Despite this interest, MWL remains a nebulous concept with multiple definitions and measurement techniques. State-of-the-art models of MWL are usually ad-hoc, considering different pools of pieces of evidence aggregated with different inference strategies. In this paper the aim is to deploy a rule-based expert system as a more structured approach to model and infer MWL. This expert system is built upon a knowledge-base of an expert and transates into computable …

Kicm: A Knowledge-Intensive Context Model, Fredrick Mtenzi, Denis Lupiana

Conference papers

A context model plays a significant role in developing context-aware architectures and consequently on realizing context-awareness, which is important in today's dynamic computing environments. These architectures monitor and analyse their environments to enable context-aware applications to effortlessly and appropriately respond to users' computing needs. These applications make the use of computing devices intuitive and less intrusive. A context model is an abstract and simplified representation of the real world, where the users and their computing devices interact. It is through a context model that knowledge about the real world can be represented in and reasoned by a context-aware architecture. This …

Representation And Analysis Of Multi-Modal, Nonuniform Time Series Data: An Application To Survival Prognosis Of Oncology Patients In An Outpatient Setting, Jennifer Winikus

Dissertations, Master's Theses and Master's Reports

The representation of nonuniform, multi-modal, time-limited time series data is complex and explored through the use of discrete representation, dimensionality reduction with segmentation based techniques, and with behavioral representation approaches. These explorations are done with a focus on an outpatient oncology setting with the classification and regression analysis being used for length of survival prognosis. Each decision of representation and analysis is not independent, with implications of each decision in method for how the data is represented and then which analysis technique is used. One unique aspect of the work is the use of outpatient clinical data for patients, which …

An Autoencoder-Based Image Descriptor For Image Matching And Retrieval, Chenyang Zhao

Browse all Theses and Dissertations

Local image features are used in many computer vision applications. Many point detectors and descriptors have been proposed in recent years; however, creation of effective descriptors is still a topic of research. The Scale Invariant Feature Transform (SIFT) developed by David Lowe is widely used in image matching and image retrieval. SIFT detects interest points in an image based on Scale-Space analysis, which is invariant to change in image scale. A SIFT descriptor contains gradient information about an image patch centered at a point of interest. SIFT is found to provide a high matching rate, is robust to image transformations; …

Intelligent Caching To Mitigate The Impact Of Web Robots On Web Servers, Howard Nathan Rude

Browse all Theses and Dissertations

With an ever increasing amount of data that is shared and posted on the Web, the desire and necessity to automatically glean this information has led to an increase in the sophistication and volume of software agents called web robots or crawlers. Recent measurements, including our own across the entire logs of Wright State University Web servers over the past two years, suggest that at least 60\% of all requests originate from robots rather than humans. Web robots display different statistical and behavioral patterns in their traffic compared to humans, yet present Web server optimizations presume that traffic exhibits predominantly …

Transformation Model With Constraints For High Accuracy Of 2d-3d Building Registration In Aerial Imagery, Guoqing Zhou, Qingli Luo, Wenhan Xie, Tao Yue, Jingjin Huang, Yuzhong Shen

Computational Modeling & Simulation Engineering Faculty Publications

This paper proposes a novel rigorous transformation model for 2D-3D registration to address the difficult problem of obtaining a sufficient number of well-distributed ground control points (GCPs) in urban areas with tall buildings. The proposed model applies two types of geometric constraints, co-planarity and perpendicularity, to the conventional photogrammetric collinearity model. Both types of geometric information are directly obtained from geometric building structures, with which the geometric constraints are automatically created and combined into the conventional transformation model. A test field located in downtown Denver, Colorado, is used to evaluate the accuracy and reliability of the proposed method. The comparison …

Applying Dijkstra Algorithm For Solving Neutrosophic Shortest Path Problem, Florentin Smarandache, Luige Vladareanu, Said Broumi, Assia Bakali, Muhammad Akram

Branch Mathematics and Statistics Faculty and Staff Publications

The selection of shortest path problem is one the classic problems in graph theory. In literature, many algorithms have been developed to provide a solution for shortest path problem in a network. One of common algorithms in solving shortest path problem is Dijkstra’s algorithm. In this paper, Dijkstra’s algorithm has been redesigned to handle the case in which most of parameters of a network are uncertain and given in terms of neutrosophic numbers. Finally, a numerical example is given to explain the proposed algorithm.

Can You Hack It? Validating Predictors For It Boot Camps, Courtney Gear

All Graduate Theses, Dissertations, and Other Capstone Projects

Given the large number of information technology jobs open and lack of qualified individuals to fill them, coding boot camps have sprung up in response to this skill gap by offering a specialized training program in an accelerated format. This fast growth has created a need to measure these training programs and understand their effectiveness. In the present study, a series of analyses examined whether specific or combinations of predictors were valid for training performance in this coding academy. Self-rated, daily efficacy scores were used as outcome variables of training success and correlation results showed a positive relationship with efficacy …

G-Code Generation For Multi-Process 3d Printing, Callum Peter Bailey

Open Access Theses & Dissertations

Since the inception of stereolithography in the 1980s, interest in 3D printing has exploded, with desktop 3D printers now commercially accessible to the general public. In recent years, next-generation multifunctional technologies have been developed, which combine 3D printing with other technologies such as wire embedding, foil embedding, CNC machining, and robotic component placement, enabling complex parts to be made on a single multifunctional machine.

However, the complexity of these integrated processes exceeds the capabilities of established design tools. To this end, this Thesis aims to develop a multi-functional design solution that can automatically generate final control code for next-generation multifunctional …

A Unit Design : Learning To Code With Finches, William V. Gruman

Graduate Research Papers

The purpose of this project was to develop a coding unit for students in grades 5-8 as an introductory programming course using the programming language SNAP! with a Finch robotics platform. The robotics platform provides a means of student engagement that allows them to complete computer programming challenges that drive interest and motivation. A series of five major learning activities were created as part of a middle school technology exploratory course. The beta testers included the four course instructors and around 30 of middle school student volunteers.

The designed unit was implemented once as a pilot, and was being implemented …

Home Networking With Enterprise Equipment, Alex Lowers

Williams Honors College, Honors Research Projects

This project tested various wired and wireless topologies and benchmarked download speeds and quality for various types of media. For music, topology had a negligible impact. High quality video streams were impacted by latency introduced in the wireless topologies. Likewise, video game streaming, especially games of high graphical fidelity, were negatively impacted when streamed over a wireless network. For all types of media, a fully wired topology is recommended.

De-Anonymization Attack Anatomy And Analysis Of Ohio Nursing Workforce Data Anonymization, Jacob M. Miracle

Browse all Theses and Dissertations

Data generalization (anonymization) is a widely misunderstood technique for preserving individual privacy in non-interactive data publishing. Easily avoidable anonymization failures are still occurring 14 years after the discovery of basic techniques to protect against them. Identities of individuals in anonymized datasets are at risk of being disclosed by cyber attackers who exploit these failures. To demonstrate the importance of proper data anonymization we present three perspectives on data anonymization. First, we examine several de-anonymization attacks to formalize the anatomy used to conduct attacks on anonymous data. Second, we examine the vulnerabilities of an anonymous nursing workforce survey to convey how …

Identifying Offensive Videos On Youtube, Rajeshwari Kandakatla

Browse all Theses and Dissertations

Harassment on social media has become a critical problem and social media content depicting harassment is becoming common place. Video-sharing websites such as YouTube contain content that may be offensive to certain community, insulting to certain religion, race etc., or make fun of disabilities. These videos can also provoke and promote altercations leading to online harassment of individuals and groups. In this thesis, we present a system that identifies offensive videos on YouTube. Our goal is to determine features that can be used to detect offensive videos efficiently and reliably. We conducted experiments using content and metadata available for each …

Computer Graphics And Visualization Based Analysis And Record System For Hand Surgery And Therapy Practice, Venkatamanikanta Subrahmanyakartheek Gokavarapu

Browse all Theses and Dissertations

In this thesis, we have designed and developed a computer graphics and visualization based analysis and record system for hand surgery and therapy practice. In particular, we have designed and developed three novel technologies: (i) model-based data compression for hand motion records (ii) model-based surface area estimation of a human hand and (iii) an emulated study of hand wound area estimation. First, we have presented a new data compression technique to better address the needs of electronic health record systems, such as file storage and privacy. In our proposed approach, we will extract the patient's hand motion information and store …

Private Record Linkage: A Comparison Of Selected Techniques For Name Matching, Pawel B. Grzebala

Browse all Theses and Dissertations

The rise of Big Data Analytics has shown the utility of analyzing all aspects of a problem by bringing together disparate data sets. Efficient and accurate private record linkage algorithms are necessary to achieve this. However, records are often linked based on personally identifiable information, and protecting the privacy of individuals is critical. This work contributes to this field by studying an important component of the private record linkage problem: linking based on names while keeping those names encrypted, both on disk and in memory. We explore the applicability, accuracy, speed and security of three different primary approaches to this …

Dynamic Level-2 Cache Memory Locking By Utilizing Multiple Miss Tables, Andrew Louis Mocniak

Browse all Theses and Dissertations

Cache memory plays a vital role in a system's performance by acting as a buffer to quickly supply requested instruction/data blocks from the main memory to the central processing unit (CPU). Cache management techniques may increase or decrease a system's performance. The results vary from process to process, depending on how well optimized the cache management technique is for a particular process. The inclusion of level-2 (L2) cache locking has been shown in previous studies to be beneficial in increasing a system's performance. This is further improved upon through the inclusion of a miss table (MT), which keeps track of …

A Stochastic Petri Net Based Nlu Scheme For Technical Documents Understanding, Adamantia Psarologou

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Natural Language Understanding (NLU) is a very old research field, which deals with machine reading comprehension. Despite the many years of work and the numerous accomplishments by several researchers in the field, there is still place for significant improvements. Here, our goal is to develop a novel NLU methodology for detecting and extracting event/action associations in technical documents. In order to achieve this goal we present a synergy of methods (Kernel extraction, Formal Language Modeling, Stochastic Petri-nets (SPN) mapping and Event Representation via SPN graph synthesis). In particular, the basic meaning of a natural language sentence is given by its …

Pothole Reporting System, Alissa L. Mcgill, Brian G. Simmons, Sean D. Querry, Elizabeth J. Hammell

Williams Honors College, Honors Research Projects

The purpose of this project is to create a pothole detection device that can be attached to the underside of a commercial vehicle. Potholes cost motorists around 6.4 billion dollars annually, thus demonstrating the need for a system to aid with the detection and reporting of potholes. The four systems we needed to consider for the implementation of this project were the power system, the sensing system, the data processing system, and the reporting and logging system. Power pulled from the vehicle will enable the sensors and data processing module. The data processing module will analyze the readings from the …