Computer Sciences Commons^™

Technology Corner Visualising Forensic Data: Evidence (Part 1), Damian Schofield, Ken Fowle

Journal of Digital Forensics, Security and Law

Visualisation is becoming increasingly important for understanding information, such as investigative data (for example: computing, medical and crime scene evidence) and analysis (for example: network capability assessment, data file reconstruction and planning scenarios). Investigative data visualisation is used to reconstruct a scene or item and is used to assist the viewer (who may well be a member of the general public with little or no understanding of the subject matter) to understand what is being presented. Analysis visualisations, on the other hand, are usually developed to review data, information and assess competing scenario hypotheses for those who usually have an …

How Often Is Employee Anger An Insider Risk I? Detecting And Measuring Negative Sentiment Versus Insider Risk In Digital Communications, Eric Shaw, Maria Payri, Michael Cohn, Ilene R. Shaw

Journal of Digital Forensics, Security and Law

This research introduced two new scales for the identification and measurement of negative sentiment and insider risk in communications in order to examine the unexplored relationship between these two constructs. The inter-rater reliability and criterion validity of the Scale of Negativity in Texts (SNIT) and the Scale of Insider Risk in Digital Communications (SIRDC) were established with a random sample of email from the Enron archive and criterion measures from established insiders, disgruntled employees, suicidal, depressed, angry, anxious, and other sampled groups. In addition, the sensitivity of the scales to changes over time as the risk of digital attack increased …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Technology Corner: Visualising Forensic Data: Evidence Guidelines (Part 2), Damian Schofield, Ken Fowle

Journal of Digital Forensics, Security and Law

Visualisation is becoming increasingly important for understanding information, such as investigative data (for example: computing, medical and crime scene evidence) and analysis (for example, network capability assessment, data file reconstruction and planning scenarios). Investigative data visualisation is used to reconstruct a scene or item and is used to assist the viewer (who may well be a member of the general public with little or no understanding of the subject matter) to understand what is being presented. Analysis visualisations, on the other hand, are usually developed to review data, information and assess competing scenario hypotheses for those who usually have an …

How Often Is Employee Anger An Insider Risk Ii? Detecting And Measuring Negative Sentiment Versus Insider Risk In Digital Communications–Comparison Between Human Raters And Psycholinguistic Software, Eric Shaw, Maria Payri, Michael Cohn, Ilene R. Shaw

Journal of Digital Forensics, Security and Law

This research uses two recently introduced observer rating scales, (Shaw et al., 2013) for the identification and measurement of negative sentiment (the Scale for Negativity in Text or SNIT) and insider risk (Scale of Indicators of Risk in Digital Communication or SIRDC) in communications to test the performance of psycholinguistic software designed to detect indicators of these risk factors. The psycholinguistic software program, WarmTouch (WT), previously used for investigations, appeared to be an effective means for locating communications scored High or Medium in negative sentiment by the SNIT or High in insider risk by the SIRDC within a randomly selected …

Trends In Android Malware Detection, Kaveh Shaerpour, Ali Dehghantanha, Ramlan Mahmod

Journal of Digital Forensics, Security and Law

This paper analyzes different Android malware detection techniques from several research papers, some of these techniques are novel while others bring a new perspective to the research work done in the past. The techniques are of various kinds ranging from detection using host based frameworks and static analysis of executable to feature extraction and behavioral patterns. Each paper is reviewed extensively and the core features of each technique are highlighted and contrasted with the others. The challenges faced during the development of such techniques are also discussed along with the future prospects for Android malware detection. The findings of the …

Risk Management Of Email And Internet Use In The Workplace, John Ruhnka, Windham E. Loopesko

Journal of Digital Forensics, Security and Law

The article surveys the changing risk environment for corporations from their employees’ electronic communications. It identifies the types of liabilities that corporations can incur from such employee communications. It discusses the objectives of corporate internet use policies and the types of provisions such policies should contain. It suggests an alternative risk-based approach to corporate acceptable use policies instead of a traditional “laundry list” of internet use prohibitions.

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Analysis Of A Second Hand Google Mini Search Appliance, Stephen Larson

Journal of Digital Forensics, Security and Law

Information and the technological advancements for which mankind develops with regards to its storage has increased tremendously over the past few decades. As the total amount of data stored rapidly increases in conjunction with the amount of widely available computer-driven devices being used, solutions are being developed to better harness this data (LaTulippe, 2011). One of these solutions is commonly known as a search appliance. Search appliances have been used in e-discovery for several years. The Google Mini Search Appliance (Mini) has not only been used for e-discovery, but for indexing and searching internal documents. To accomplish these tasks, search …

System-Generated Digital Forensic Evidence In Graphic Design Applications, Enos Mabuto, Hein Venter

Journal of Digital Forensics, Security and Law

Graphic design applications are often used for the editing and design of digital art. The same applications can be used for creating counterfeit documents such as identity documents (IDs), driver’s licences, passports, etc. However, the use of any graphic design application leaves behind traces of digital information that can be used during a digital forensic investigation. Current digital forensic tools examine a system to find digital evidence, but they do not examine a system specifically for the creating of counterfeit documents created through the use of graphic design applications. The paper in hand reviews the system-generated digital forensic evidence gathered …

Hyperspectral Image Classification Using A Spectral-Spatial Sparse Coding Model, Ender Oguslu, Guoqing Zhou, Jiang Li, Lorenzo Bruzzone (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based spectral-spatial classification model for hyperspectral image (HSI) datasets. The proposed method consists of an efficient sparse coding method in which the l₁/l_q regularized multi-class logistic regression technique was utilized to achieve a compact representation of hyperspectral image pixels for land cover classification. We applied the proposed algorithm to a HSI dataset collected at the Kennedy Space Center and compared our algorithm to a recently proposed method, Gaussian process maximum likelihood (GP-ML) classifier. Experimental results show that the proposed method can achieve significantly better performances than the GP-ML classifier when training data …

Unmanned Autonomous Object Retrieval: Old Dominion University 2013 International Aerial Robotics Competition Entry, Johnathan Bailey, Austin Boyd, Chung-Hao Chen, Stephen Dailey, Lisa Henderson, Jeremy Stuart, Christina Williams

Electrical & Computer Engineering Faculty Publications

This paper describes the design implementation of a Quadrotor Unmanned Aerial Vehicle (UAV) with the capability of exploring indoor locations without the assistance of external aids. For relative position, the use of a laser range sensor, an optical flow sensor, and sonar sensor combined allows for the vehicle to generate mapping information. With relative position in mind, the vehicle uses vision algorithms to recognize immediate obstacles, sign, and entry ways to allow for quick movement responses and object recognition. A proportional-integral-differentiator controller allows for flight stability and mitigation in the tight confines of the indoor spaces. A mapping algorithm allows …

Performance Evaluation And Comparison Of Distributed Messaging Using Message Oriented Middleware, Naveen Mupparaju

UNF Graduate Theses and Dissertations

Message Oriented Middleware (MOM) is an enabling technology for modern event- driven applications that are typically based on publish/subscribe communication [Eugster03]. Enterprises typically contain hundreds of applications operating in environments with diverse databases and operating systems. Integration of these applications is required to coordinate the business process. Unfortunately, this is no easy task. Enterprise Integration, according to Brosey et al. (2001), "aims to connect and combines people, processes, systems, and technologies to ensure that the right people and the right processes have the right information and the right resources at the right time"[Brosey01]. Communication between different applications can be achieved …

Orientation Invariant Ecg-Based Stethoscope Tracking For Heart Auscultation Training On Augmented Standardized Patients, Nahom Kidane, Salim Chemlal, Jiang Li, Frederic D. Mckenzie, Tom Hubbard

Computational Modeling & Simulation Engineering Faculty Publications

Auscultation, the act of listening to the heart and lung sounds, can reveal substantial information about patients’ health and other cardiac-related problems; therefore, competent training can be a key for accurate and reliable diagnosis. Standardized patients (SPs), who are healthy individuals trained to portray real patients, have been extensively used for such training and other medical teaching techniques; however, the range of symptoms and conditions they can simulate remains limited since they are only patient actors. In this work, we describe a novel tracking method for placing virtual symptoms in correct auscultation areas based on recorded ECG signals with various …

Integration Of Multispectral Face Recognition And Multi-Ptz Camera Automated Surveillance For Security Applications, Chung-Hao Chen, Yi Yao, Hong Chang, Andreas Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Due to increasing security concerns, a complete security system should consist of two major components, a computer-based face-recognition system and a real-time automated video surveillance system. A computer-based face-recognition system can be used in gate access control for identity authentication. In recent studies, multispectral imaging and fusion of multispectral narrow-band images in the visible spectrum have been employed and proven to enhance the recognition performance over conventional broad-band images, especially when the illumination changes. Thus, we present an automated method that specifies the optimal spectral ranges under the given illumination. Experimental results verify the consistent performance of our algorithm via …

A Large Scale Distributed Syntactic, Semantic And Lexical Language Model For Machine Translation, Ming Tan

Browse all Theses and Dissertations

The n-gram model is the most widely used language model (LM) in statistical machine translation system, due to its simplicity and scalability. However, it only encodes the local lexical relation between adjacent words and clearly ignores the rich syntactic and semantic structures of the natural languages. Attempting to increase the order of an n-gram to describe longer range dependencies in natural language immediately runs into the curse of dimensionality. Although previous researches tried to increase the order of n-gram on a large corpus, they did not see obvious improvement beyond 6-gram. Meanwhile, other LMs, such as syntactic language models and …

Visual Exploration And Information Analytics Of High-Dimensional Medical Images, Darshan Pai

Wayne State University Dissertations

Data visualization has transformed how we analyze increasingly large and complex data sets. Advanced visual tools logically represent data in a way that communicates the most important information inherent within it and culminate the analysis with an insightful conclusion. Automated analysis disciplines - such as data mining, machine learning, and statistics - have traditionally been the most dominant fields for data analysis. It has been complemented with a near-ubiquitous adoption of specialized hardware and software environments that handle the storage, retrieval, and pre- and postprocessing of digital data. The addition of interactive visualization tools allows an active human participant in …

Opacity Of Discrete Event Systems: Analysis And Control, Majed Mohamed Ben Kalefa

Wayne State University Dissertations

The exchange of sensitive information in many systems over a network can be manipulated

by unauthorized access. Opacity is a property to investigate security and

privacy problems in such systems. Opacity characterizes whether a secret information

of a system can be inferred by an unauthorized user. One approach to verify security

and privacy properties using opacity problem is to model the system that may leak confidential

information as a discrete event system. The problem that has not investigated

intensively is the enforcement of opacity properties by supervisory control. In other

words, constructing a minimally restrictive supervisor to limit the system's …

A Matlab Primer In Four Hours With Practical Examples, Jerome Casey

Instructional Guides

No abstract provided.

A Semantics-Based Approach To Machine Perception, Cory Andrew Henson

Browse all Theses and Dissertations

Machine perception can be formalized using semantic web technologies in order to derive abstractions from sensor data using background knowledge on the Web, and efficiently executed on resource-constrained devices. Advances in sensing technology hold the promise to revolutionize our ability to observe and understand the world around us. Yet the gap between observation and understanding is vast. As sensors are becoming more advanced and cost-effective, the result is an avalanche of data of high volume, velocity, and of varied type, leading to the problem of too much data and not enough knowledge (i.e., insights leading to actions). Current estimates predict …

A Methodology For Extracting Human Bodies From Still Images, Athanasios Tsitsoulis

Browse all Theses and Dissertations

Monitoring and surveillance of humans is one of the most prominent applications of today and it is expected to be part of many future aspects of our life, for safety reasons, assisted living and many others. Many efforts have been made towards automatic and robust solutions, but the general problem is very challenging and remains still open. In this PhD dissertation we examine the problem from many perspectives. First, we study the performance of a hardware architecture designed for large-scale surveillance systems. Then, we focus on the general problem of human activity recognition, present an extensive survey of methodologies that …

Anomalies In Sensor Network Deployments: Analysis, Modeling, And Detection, Giovani Rimon Abuaitah

Browse all Theses and Dissertations

A sensor network serves as a vital source for collecting raw sensory data. Sensor data are later processed, analyzed, visualized, and reasoned over with the help of several decision making tools. A decision making process can be disastrously misled by a small portion of anomalous sensor readings. Therefore, there has been a vast demand for mechanisms that identify and then eliminate such anomalies in order to ensure the quality, integrity, and/or trustworthiness of the raw sensory data before they can even be interpreted.

Prior to identifying anomalies, it is essential to understand the various anomalous behaviors prevalent in a sensor …

Cooperative Interactive Distributed Guidance On Mobile Devices, Gregory Burnett

Browse all Theses and Dissertations

Mobiles device are quickly becoming an indispensable part of our society. Equipped with numerous communication capabilities, they are increasingly being examined as potential tools for civilian and military usage to aide in distributed remote collaboration for dynamic decision making and physical task completion. With an ever growing mobile workforce, the need for remote assistance in aiding field workers who are confronted with situations outside their expertise certainly increases. Enhanced capabilities in using mobile devices could significantly improve numerous components of a task's completion (i.e. accuracy, timing, etc.). This dissertation considers the design of mobile implementation of technology and communication capabilities …

Natural Language Document And Event Association Using Stochastic Petri Net Modeling, Michael Thomas Mills

Browse all Theses and Dissertations

The purpose of this research is to design and implement a new methodology that captures the natural language understanding of events from English natural language text and model it using Stochastic Petri Nets. To establish a baseline of recent natural language processing (NLP) and understanding (NLU) research, two surveys are presented. One is a general survey in NLP and NLU methodologies for processing multi-documents. It summarizes and presents methodologies in terms of their features, capabilities, and maturity. The second survey focuses on graph-based methods for NL text processing and understanding and analyzes them in terms of their functional descriptions, capabilities …

Adaptive Semantic Annotation Of Entity And Concept Mentions In Text, Pablo N. Mendes

Browse all Theses and Dissertations

The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc or application-specific databases.

These knowledge repositories figure as a central provider of unambiguous identifiers and semantic relationships between entities. As such, these shared entity descriptions serve as a common vocabulary to exchange and organize information in different formats and for different purposes. Therefore, there has been remarkable interest in systems that are able to automatically tag textual documents with identifiers from shared knowledge repositories so that the content in those documents is described in a …

Mining Diversified Decision Trees Across Multiple Datasets To Capture Similarities And Alignable Differences, Qian Han

Browse all Theses and Dissertations

This dissertation studies the problem of mining shared and alignable difference knowledge structures across multiple datasets/applications. Shared and alignable difference knowledge structures are important for identifying analogies between application domains and for forming new hypothesis in challenging research applications, and for assessing the degree and types of knowledge-level similarities and differences between application domains for use in learning transfer. Generally speaking, shared knowledge structures characterize underlying datasets and highlight conceptual-level structural similarities among the datasets. This dissertation studies the mining of shared decision trees, which are a special type of shared knowledge structures. We first consider building one shared decision …

Human Performance Regression Testing, Amanda Swearngin, Myra B. Cohen, Bonnie E. John, Rachel K. E. Bellamy

School of Computing: Conference and Workshop Papers

As software systems evolve, new interface features such as keyboard shortcuts and toolbars are introduced. While it is common to regression test the new features for functional correctness, there has been less focus on systematic regression testing for usability, due to the effort and time involved in human studies. Cognitive modeling tools such as CogTool provide some help by computing predictions of user performance, but they still require manual effort to describe the user interface and tasks, limiting regression testing efforts. In recent work, we developed CogTool-Helper to reduce the effort required to generate human performance models of existing systems. …

Fea Estimation And Experimental Validation Of Solid Rotor And Magnet Eddy Current Loss In Single-Sided Axial Flux Permanent Magnet Machines, Xu Yang, Dean Patterson, Jerry Hudgins, Jessica Colton

Department of Electrical and Computer Engineering: Faculty Publications

The rotor and magnet loss in single-sided axial flux permanent magnet machines with non-overlapped windings is studied in this paper. FEA estimations of the loss are carried out using both 2-D and 3-D modeling. The rotor and magnet losses are determined separately for stator slot passing and MMF space harmonics from currents in the stator. The segregation of loss between the solid rotor plate and the magnet is addressed. The eddy current loss reduction by magnet segments is discussed as well. The prototype 24 slot/22 pole single-sided AFPMs, fabricated with both single layer and double layer windings are assembled. Methods …

Employing Learning To Improve The Performance Of Meta-Raps, Fatemah Al-Duoli, Ghaith Rabadi

Engineering Management & Systems Engineering Faculty Publications

In their search for satisfactory solutions to complex combinatorial problems, metaheuristics methods are expected to intelligently explore the solution space. Various forms of memory have been used to achieve this goal and improve the performance of metaheuristics, which warranted the development of the Adaptive Memory Programming (AMP) framework [1]. This paper follows this framework by integrating Machine Learning (ML) concepts into metaheuristics as a way to guide metaheuristics while searching for solutions. The target metaheuristic method is Meta-heuristic for Randomized Priority Search (Meta-RaPS). Similar to most metaheuristics, Meta-RaPS consists of construction and improvement phases. Randomness coupled with a greedy heuristic …

Decision Support For Assorted Populations In Uncertain And Congested Environments, Pradeep Reddy Varakantham, Asrar Ahmed, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents, they effect other agents. While there has been much research in handling such implicit effects, it has primarily assumed deterministic movements of agents. We address the issue of decision support for individual agents that are identical and have involuntary movements in dynamic environments. For instance, in a taxi fleet serving a city, …