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Full-Text Articles in Computer Engineering

Development Of A National Repository Of Digital Forensic Intelligence, Mark Weiser, David P. Biros, Greg Mosier Oct 2016

Development Of A National Repository Of Digital Forensic Intelligence, Mark Weiser, David P. Biros, Greg Mosier

Annual ADFSL Conference on Digital Forensics, Security and Law

Many people do all of their banking online, we and our children communicate with peers through computer systems, and there are many jobs that require near continuous interaction with computer systems. Criminals, however, are also “connected”, and our online interaction provides them a conduit into our information like never before. Our credit card numbers and other fiscal information are at risk, our children's personal information is exposed to the world, and our professional reputations are on the line.

The discipline of Digital Forensics in law enforcement agencies around the nation and world has grown to match the increased risk and …


Designing A Data Warehouse For Cyber Crimes, Il-Yeol Song, John D. Maguire, Ki Jung Lee, Namyoun Choi, Xiaohua Hu, Peter Chen Oct 2016

Designing A Data Warehouse For Cyber Crimes, Il-Yeol Song, John D. Maguire, Ki Jung Lee, Namyoun Choi, Xiaohua Hu, Peter Chen

Annual ADFSL Conference on Digital Forensics, Security and Law

One of the greatest challenges facing modern society is the rising tide of cyber crimes. These crimes, since they rarely fit the model of conventional crimes, are difficult to investigate, hard to analyze, and difficult to prosecute. Collecting data in a unified framework is a mandatory step that will assist the investigator in sorting through the mountains of data. In this paper, we explore designing a dimensional model for a data warehouse that can be used in analyzing cyber crime data. We also present some interesting queries and the types of cyber crime analyses that can be performed based on …


Towards A Development Of A Mobile Application Security Invasiveness Index, Sam Espana Oct 2016

Towards A Development Of A Mobile Application Security Invasiveness Index, Sam Espana

KSU Proceedings on Cybersecurity Education, Research and Practice

The economic impact of Mobile IP, the standard that allows IP sessions to be maintained even when switching between different cellular towers or networks, has been staggering in terms of both scale and acceleration (Doherty, 2016). As voice communications transition to all-digital, all-IP networks such as 4G, there will be an increase in risk due to vulnerabilities, malware, and hacks that exist for PC-based systems and applications (Harwood, 2011). According to Gostev (2006), in June, 2004, a well-known Spanish virus collector known as VirusBuster, emailed the first known mobile phone virus to Kaspersky Lab, Moscow. Targeting the Symbian OS, the …


Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu Oct 2016

Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu

Research Collection School Of Computing and Information Systems

A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures. RepMatch is based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches. By considering the set of all nearest-neighbor matches, RepMatch can …


Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington Sep 2016

Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington

Journal of Digital Forensics, Security and Law

Empirical and anecdotal evidence indicates that cyberharassment is more prevalent as the use of social media becomes increasingly widespread, making geography and physical proximity irrelevant. Cyberharassment can take different forms (e.g., cyberbullying, cyberstalking, cybertrolling), and be motivated by the objectives of inflicting distress, exercising control, impersonation, and defamation. Little is currently known about the modus operandi of offenders and their psychological characteristics. Investigation of these behaviours is particularly challenging because it involves digital evidence distributed across the devices of both alleged offenders and victims, as well as online service providers, sometimes over an extended period of time. This special issue …


The Impact Of Low Self-Control On Online Harassment: Interaction With Opportunity., Hyunin Baek, Michael M. Losavio, George E. Higgins Sep 2016

The Impact Of Low Self-Control On Online Harassment: Interaction With Opportunity., Hyunin Baek, Michael M. Losavio, George E. Higgins

Journal of Digital Forensics, Security and Law

Developing Internet technology has increased the rates of youth online harassment. This study examines online harassment from adolescents with low self-control and the moderating effect of opportunity. The data used in this study were collected by the Korea Institute of Criminology in 2009. The total sample size was 1,091. The results indicated that low self-control, opportunity, and gender have a significant influence on online harassment. However, these results differed according to gender; for males, low self-control significantly impacted online harassment; for females, however, only low self-control significantly impacted online harassment. Furthermore, the interaction between low self-control and opportunity did not …


Table Of Contents Sep 2016

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.


A Legal Examination Of Revenge Pornography And Cyber-Harassment, Thomas Lonardo, Tricia Martland, Doug White Sep 2016

A Legal Examination Of Revenge Pornography And Cyber-Harassment, Thomas Lonardo, Tricia Martland, Doug White

Journal of Digital Forensics, Security and Law

This paper examines the current state of the statutes in the United States as they relate to cyber-harassment in the context of "revenge porn". Revenge porn refers to websites which cater to those wishing to exploit, harass, or otherwise antagonize their ex partners using pornographic images and videos which were obtained during their relationships. The paper provide examples and illustrations as well as a summary of current statute in the United States. The paper additionally explores some of the various legal remedies available to victims of revenge pornography.


Differentiating Cyberbullies And Internet Trolls By Personality Characteristics And Self-Esteem, Lauren A. Zezulka, Kathryn C. Seigfried-Spellar Sep 2016

Differentiating Cyberbullies And Internet Trolls By Personality Characteristics And Self-Esteem, Lauren A. Zezulka, Kathryn C. Seigfried-Spellar

Journal of Digital Forensics, Security and Law

Cyberbullying and internet trolling are both forms of online aggression or cyberharassment; however, research has yet to assess the prevalence of these behaviors in relationship to one another. In addition, the current study was the first to investigate whether individual differences and self-esteem discerned between self-reported cyberbullies and/or internet trolls (i.e., Never engaged in either, Cyberbully-only, Troll-only, Both Cyberbully and Troll). Of 308 respondents solicited from Mechanical Turk, 70 engaged in cyberbullying behaviors, 20 engaged in only trolling behaviors, 129 self-reported both behaviors, and 89 self-reported neither behavior. Results yielded low self-esteem, low conscientiousness, and low internal moral values for …


Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron Sep 2016

Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron

Journal of Digital Forensics, Security and Law

Threats are communicative acts, but it is not always obvious what they communicate or when they communicate imminent credible and serious risk. This paper proposes a research- and theory-based set of over 20 potential linguistic risk indicators that may discriminate credible from non-credible threats within online threat message corpora. Two prongs are proposed: (1) Using expert and layperson ratings to validate subjective scales in relation to annotated known risk messages, and (2) Using the resulting annotated corpora for automated machine learning with computational linguistic analyses to classify non-threats, false threats, and credible threats. Rating scales are proposed, existing threat corpora …


Landmark Detection With Surprise Saliency Using Convolutional Neural Networks, Feng Tang, Damian Lyons, Daniel Leeds Sep 2016

Landmark Detection With Surprise Saliency Using Convolutional Neural Networks, Feng Tang, Damian Lyons, Daniel Leeds

Faculty Publications

Abstract—Landmarks can be used as reference to enable people or robots to localize themselves or to navigate in their environment. Automatic definition and extraction of appropriate landmarks from the environment has proven to be a challenging task when pre-defined landmarks are not present. We propose a novel computational model of automatic landmark detection from a single image without any pre-defined landmark database. The hypothesis is that if an object looks abnormal due to its atypical scene context (what we call surprise saliency), it then may be considered as a good landmark because it is unique and easy to spot by …


Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh Sep 2016

Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh

Dissertations

This thesis reviews the current state of photometric classification in Astronomy and identifies two main gaps: a dependence on handcrafted rules, and a lack of interpretability in the more successful classifiers. To address this, Deep Learning and Computer Vision were used to create a more interpretable model, using unsupervised training to reduce human bias.

The main contribution is the investigation into the impact of using unsupervised feature-extraction from multi-wavelength image data for the classification task. The feature-extraction is achieved by implementing an unsupervised Deep Belief Network to extract lower-dimensionality features from the multi-wavelength image data captured by the Sloan Digital …


Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Haiyong Xie Sep 2016

Metaflow: A Scalable Metadata Lookup Service For Distributed File Systems In Data Centers, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Haiyong Xie

Research Collection School Of Computing and Information Systems

In large-scale distributed file systems, efficient metadata operations are critical since most file operations have to interact with metadata servers first. In existing distributed hash table (DHT) based metadata management systems, the lookup service could be a performance bottleneck due to its significant CPU overhead. Our investigations showed that the lookup service could reduce system throughput by up to 70%, and increase system latency by a factor of up to 8 compared to ideal scenarios. In this paper, we present MetaFlow, a scalable metadata lookup service utilizing software-defined networking (SDN) techniques to distribute lookup workload over network components. MetaFlow tackles …


Indoor Localization Via Multi-Modal Sensing On Smartphones, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, Yunhao Liu Sep 2016

Indoor Localization Via Multi-Modal Sensing On Smartphones, Han Xu, Zheng Yang, Zimu Zhou, Longfei Shangguan, Ke Yi, Yunhao Liu

Research Collection School Of Computing and Information Systems

Indoor localization is of great importance to a wide range ofapplications in shopping malls, office buildings and publicplaces. The maturity of computer vision (CV) techniques andthe ubiquity of smartphone cameras hold promise for offering sub-meter accuracy localization services. However, pureCV-based solutions usually involve hundreds of photos andpre-calibration to construct image database, a labor-intensiveoverhead for practical deployment. We present ClickLoc, anaccurate, easy-to-deploy, sensor-enriched, image-based indoor localization system. With core techniques rooted insemantic information extraction and optimization-based sensor data fusion, ClickLoc is able to bootstrap with few images. Leveraging sensor-enriched photos, ClickLoc also enables user localization with a single photo of the …


Developers’ Perceptions On Object-Oriented Design And Architectural Roles, Maurício Aniche, Marco Aurélio Gerosa, Christoph Treude Sep 2016

Developers’ Perceptions On Object-Oriented Design And Architectural Roles, Maurício Aniche, Marco Aurélio Gerosa, Christoph Treude

Research Collection School Of Computing and Information Systems

Software developers commonly rely on well-known software architecture patterns, such as MVC, to build their applications. In many of these patterns, classes play specific roles in the system, such as Controllers or Entities, which means that each of these classes has specific characteristics in terms of object-oriented class design and implementation. Indeed, as we have shown in a previous study, architectural roles are different from each other in terms of code metrics. In this paper, we present a study in a software development company in which we captured developers’ perceptions on object-oriented design aspects of the architectural roles in their …


Haptic Foot Feedback For Kicking Training In Virtual Reality, Hank Huang, Hong Tan Aug 2016

Haptic Foot Feedback For Kicking Training In Virtual Reality, Hank Huang, Hong Tan

The Summer Undergraduate Research Fellowship (SURF) Symposium

As means to further supplement athletic performances increases, virtual reality is becoming helpful to sports in terms of cognitive training such as reaction, mentality, and game strategies. With the aid of haptic feedback, interaction with virtual objects increases by another dimension, in addition to the presence of visual and auditory feedback. This research presents an integrated system of a virtual reality environment, motion tracking system, and a haptic unit designed for the dorsal foot. The prototype simulates a scenario of virtual kicking and returns haptic response upon collision between the user’s foot and virtual object. The overall system was evaluated …


Anti-Forensics: Furthering Digital Forensic Science Through A New Extended, Granular Taxonomy, Kevin Conlan, Ibrahim Baggili, Frank Breitinger Aug 2016

Anti-Forensics: Furthering Digital Forensic Science Through A New Extended, Granular Taxonomy, Kevin Conlan, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Anti-forensic tools, techniques and methods are becoming a formidable obstacle for the digital forensic community. Thus, new research initiatives and strategies must be formulated to address this growing problem. In this work we first collect and categorize 308 antidigital forensic tools to survey the field. We then devise an extended anti-forensic taxonomy to the one proposed by Rogers (2006) in order to create a more comprehensive taxonomy and facilitate linguistic standardization. Our work also takes into consideration anti-forensic activity which utilizes tools that were not originally designed for antiforensic purposes, but can still be used with malicious intent. This category …


Improving The Efficiency Of Ci With Uber-Commits, Matias Waterloo Aug 2016

Improving The Efficiency Of Ci With Uber-Commits, Matias Waterloo

School of Computing: Dissertations, Theses, and Student Research

Continuous Integration (CI) is a software engineering practice where developers break their coding tasks into small changes that can be integrated with the shared code repository on a frequent basis. The primary objectives of CI are to avoid integration problems caused by large change sets and to provide prompt developer feedback so that if a problem is detected, it can be easily and quickly resolved. In this thesis, we argue that while keeping changes small and integrating often is a wise approach for developers, the CI server may be more efficient operating on a different scale. In our approach, the …


Using Ubiquitous Data To Improve Smartwatches' Context Awareness, Yuankun Song Aug 2016

Using Ubiquitous Data To Improve Smartwatches' Context Awareness, Yuankun Song

Open Access Theses

Nowadays, more and more data is being generated by various software applications, services and smart devices every second. The data contains abundant information about people’s daily lives. This research explored the possibility of improving smartwatches’ context awareness by using common ubiquitous data. The researcher developed a prototype system consisting of an Android application and a web application, and conducted an experiment where 10 participants performed several tasks with the help of a smartwatch. The result showed a significant improvement of the smartwatch’s context awareness running the prototype application, which used ubiquitous data to automatically execute proper actions according to contexts. …


Monitoring Dbms Activity To Detect Insider Threat Using Query Selectivity, Prajwal B. Hegde Aug 2016

Monitoring Dbms Activity To Detect Insider Threat Using Query Selectivity, Prajwal B. Hegde

Open Access Theses

The objective of the research presented in this thesis is to evaluate the importance of query selectivity for monitoring DBMS activity and detect insider threat. We propose query selectivity as an additional component to an existing anomaly detection system (ADS). We first look at the advantages of working with this particular ADS. This is followed by a discussion about some existing limitations in the anomaly detection system (ADS) and how it affects its overall performance. We look at what query selectivity is and how it can help improve upon the existing limitations of the ADS. The system is then implemented …


Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam Aug 2016

Interactive Logical Analysis Of Planning Domains, Rajesh Kalyanam

Open Access Dissertations

Humans exhibit a significant ability to answer a wide range of questions about previously unencountered planning domains, and leverage this ability to construct “general-purpose'' solution plans for the domain.

The long term vision of this research is to automate this ability, constructing a system that utilizes reasoning to automatically verify claims about a planning domain. The system would use this ability to automatically construct and verify a generalized plan to solve any planning problem in the domain. The goal of this thesis is to start with baseline results from the interactive verification of claims about planning domains and develop the …


Exploring Spin-Transfer-Torque Devices And Memristors For Logic And Memory Applications, Zoha Pajouhi Aug 2016

Exploring Spin-Transfer-Torque Devices And Memristors For Logic And Memory Applications, Zoha Pajouhi

Open Access Dissertations

As scaling CMOS devices is approaching its physical limits, researchers have begun exploring newer devices and architectures to replace CMOS.

Due to their non-volatility and high density, Spin Transfer Torque (STT) devices are among the most prominent candidates for logic and memory applications. In this research, we first considered a new logic style called All Spin Logic (ASL). Despite its advantages, ASL consumes a large amount of static power; thus, several optimizations can be performed to address this issue. We developed a systematic methodology to perform the optimizations to ensure stable operation of ASL.

Second, we investigated reliable design of …


Cufa: A More Formal Definition For Digital Forensic Artifacts, Vikram S. Harichandran, Daniel Walnycky, Ibrahim Baggili, Frank Breitinger Aug 2016

Cufa: A More Formal Definition For Digital Forensic Artifacts, Vikram S. Harichandran, Daniel Walnycky, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

The term “artifact” currently does not have a formal definition within the domain of cyber/ digital forensics, resulting in a lack of standardized reporting, linguistic understanding between professionals, and efficiency. In this paper we propose a new definition based on a survey we conducted, literature usage, prior definitions of the word itself, and similarities with archival science. This definition includes required fields that all artifacts must have and encompasses the notion of curation. Thus, we propose using a new term e curated forensic artifact (CuFA) e to address items which have been cleared for entry into a CuFA database (one …


Deleting Collected Digital Evidence By Exploiting A Widely Adopted Hardware Write Blocker, Christopher S. Meffert, Ibrahim Baggili, Frank Breitinger Aug 2016

Deleting Collected Digital Evidence By Exploiting A Widely Adopted Hardware Write Blocker, Christopher S. Meffert, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

In this primary work we call for the importance of integrating security testing into the process of testing digital forensic tools. We postulate that digital forensic tools are increasing in features (such as network imaging), becoming networkable, and are being proposed as forensic cloud services. This raises the need for testing the security of these tools, especially since digital evidence integrity is of paramount importance. At the time of conducting this work, little to no published anti-forensic research had focused on attacks against the forensic tools/process.We used the TD3, a popular, validated, touch screen disk duplicator and hardware write blocker …


Use Of Clustering Techniques For Protein Domain Analysis, Eric Rodene Jul 2016

Use Of Clustering Techniques For Protein Domain Analysis, Eric Rodene

School of Computing: Dissertations, Theses, and Student Research

Next-generation sequencing has allowed many new protein sequences to be identified. However, this expansion of sequence data limits the ability to determine the structure and function of most of these newly-identified proteins. Inferring the function and relationships between proteins is possible with traditional alignment-based phylogeny. However, this requires at least one shared subsequence. Without such a subsequence, no meaningful alignments between the protein sequences are possible. The entire protein set (or proteome) of an organism contains many unrelated proteins. At this level, the necessary similarity does not occur. Therefore, an alternative method of understanding relationships within diverse sets of proteins …


Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi Jul 2016

Vision-Based Motion For A Humanoid Robot, Khalid Abdullah Alkhulayfi

Dissertations and Theses

The overall objective of this thesis is to build an integrated, inexpensive, human-sized humanoid robot from scratch that looks and behaves like a human. More specifically, my goal is to build an android robot called Marie Curie robot that can act like a human actor in the Portland Cyber Theater in the play Quantum Debate with a known script of every robot behavior. In order to achieve this goal, the humanoid robot need to has degrees of freedom (DOF) similar to human DOFs. Each part of the Curie robot was built to achieve the goal of building a complete humanoid …


Recursive Non-Local Means Filter For Video Denoising With Poisson-Gaussian Noise, Redha A. Almahdi, Russell C. Hardie Jul 2016

Recursive Non-Local Means Filter For Video Denoising With Poisson-Gaussian Noise, Redha A. Almahdi, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

In this paper, we describe a new recursive Non-Local means (RNLM) algorithm for video denoising that has been developed by the current authors. Furthermore, we extend this work by incorporating a Poisson-Gaussian noise model. Our new RNLM method provides a computationally efficient means for video denoising, and yields improved performance compared with the single frame NLM and BM3D benchmarks methods. Non-Local means (NLM) based methods of denoising have been applied successfully in various image and video sequence denoising applications. However, direct extension of this method from 2D to 3D for video processing can be computationally demanding. The RNLM approach takes …


Vertical Implementation Of Cloud For Education (V.I.C.E.), Travis S. Brummett Jul 2016

Vertical Implementation Of Cloud For Education (V.I.C.E.), Travis S. Brummett

Masters Theses & Specialist Projects

There are several different implementations of open source cloud software that organizations can utilize when deploying their own private cloud. Some possible solutions are OpenNebula, Nimbus, and Eucalyptus. These are Infrastructure-as-a-Service (IaaS) cloud implementations that ultimately gives users virtual machines to undefined job types. A typical IaaS cloud is composed of a front-end cloud controller node, a cluster controller node for controlling compute nodes, a virtual machine image repository node, and many persistent storage nodes and compute nodes. These architectures are built for ease of scalability and availability.

Interestingly, the potential of such architectures could have in the educational field …


Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay Jul 2016

Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay

Electrical and Computer Engineering Faculty Publications

Lung cancer is the leading cause of cancer death in the United States. It usually exhibits its presence with the formation of pulmonary nodules. Nodules are round or oval-shaped growth present in the lung. Computed Tomography (CT) scans are used by radiologists to detect such nodules. Computer Aided Detection (CAD) of such nodules would aid in providing a second opinion to the radiologists and would be of valuable help in lung cancer screening. In this research, we study various feature selection methods for the CAD system framework proposed in FlyerScan. Algorithmic steps of FlyerScan include (i) local contrast enhancement (ii) …


Significant Permission Identification For Android Malware Detection, Lichao Sun Jul 2016

Significant Permission Identification For Android Malware Detection, Lichao Sun

School of Computing: Dissertations, Theses, and Student Research

A recent report indicates that a newly developed malicious app for Android is introduced every 11 seconds. To combat this alarming rate of malware creation, we need a scalable malware detection approach that is effective and efficient. In this thesis, we introduce SigPID, a malware detection system based on permission analysis to cope with the rapid increase in the number of Android malware. Instead of analyzing all 135 Android permissions, our approach applies 3-level pruning by mining the permission data to identify only significant permissions that can be effective in distinguishing benign and malicious apps. Based on the identified significant …