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Table Of Contents

Journal of Digital Forensics, Security and Law

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Extraction Of Electronic Evidence From Voip: Identification & Analysis Of Digital Speech, David Irwin, Arek Dadej, Jill Slay

Journal of Digital Forensics, Security and Law

The Voice over Internet Protocol (VoIP) is increasing in popularity as a cost effective and efficient means of making telephone calls via the Internet. However, VoIP may also be an attractive method of communication to criminals as their true identity may be hidden and voice and video communications are encrypted as they are deployed across the Internet. This produces a new set of challenges for forensic analysts compared with traditional wire-tapping of the Public Switched Telephone Network (PSTN) infrastructure, which is not applicable to VoIP. Therefore, other methods of recovering electronic evidence from VoIP are required. This research investigates the …

Book Review: Dispute Resolution And E-Discovery, Milton Luoma

Journal of Digital Forensics, Security and Law

As is apparent from its title, this book tackles two very current and difficult legal issues – electronic discovery and dispute resolution. The authors tie the two legal concepts together in an effort to provide litigants and practitioners a less expensive and less time consuming alternative than is typically the case with traditional litigation and court proceedings. By including electronic discovery in the discussions, the authors recognize the importance and significance of electronic discovery in mediation and arbitration as it is in traditional litigation.

On The Development Of A Digital Forensics Curriculum, Manghui Tu, Dianxiang Xu, Samsuddin Wira, Cristian Balan, Kyle Cronin

Journal of Digital Forensics, Security and Law

Computer Crime and computer related incidents continue their prevalence and frequency, resulting in losses approaching billions of dollars. To fight against these crimes and frauds, it is urgent to develop digital forensics education programs to train a suitable workforce that can effectively investigate computer crimes and incidents. There is presently no standard to guide the design of digital forensics curriculum for an academic program. In this research, previous work on digital forensics curriculum design and existing education programs are thoroughly investigated. Both digital forensics educators and practitioners were surveyed and results were analyzed to determine the industry and law enforcement …

The Science Of Digital Forensics: Recovery Of Data From Overwritten Areas Of Magnetic Media, Fred Cohen

Journal of Digital Forensics, Security and Law

The first time I encountered data loss and recovery effects of magnetic memory was as a night and weekend computer operator for the computer science department of Carnegie-Mellon University in the 1973-1974 time frame. Part of my job involved dealing directly with outages and failures associated with magnetic memory components used in what, at the time, were large computer systems. On occasions, portions of magnetic core memory or disk drives would encounter various failure modes and the systems using these devices would have to be reconfigured to operate without the failed components until repair personnel could come in to repair …

Automatic Crash Recovery: Internet Explorer's Black Box, John Moran, Douglas Orr

Journal of Digital Forensics, Security and Law

A good portion of today's investigations include, at least in part, an examination of the user's web history. Although it has lost ground over the past several years, Microsoft's Internet Explorer still accounts for a large portion of the web browser market share. Most users are now aware that Internet Explorer will save browsing history, user names, passwords and form history. Consequently some users seek to eliminate these artifacts, leaving behind less evidence for examiners to discover during investigations. However, most users, and probably a good portion of examiners are unaware Automatic Crash Recovery can leave a gold mine of …

Book Review: The Software Ip Detective's Handbook: Measurement, Comparison, And Infringement Detections, Diane Barrett

Journal of Digital Forensics, Security and Law

Do not the book title fool you into thinking that the book is only for those looking to detect software infringement detection. It is a comprehensive look at software intellectual property. The book covers a wide range of topics and has something to offer for just about everyone from lawyers to programmers.

“Preemptive Suppression” – Judges Claim The Right To Find Digital Evidence Inadmissible Before It Is Even Discovered, Bob Simpson

Journal of Digital Forensics, Security and Law

Vermont state prosecutors have asked the Vermont Supreme Court to end a state trial judge’s practice of attaching conditions to computer warrants. The Vermont judge’s conditions are drawn from five conditions established in the 2009 decision of the 9th Circuit Court of Appeals in the Comprehensive Drug Testing, Inc. case (CDT II). This is the first time the validity of the “CDT conditions” will be decided by a state court of final jurisdiction in the United States

Sparse Coding For Hyperspectral Images Using Random Dictionary And Soft Thresholding, Ender Oguslu, Khan Iftekharuddin, Jiang Li, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)

Electrical & Computer Engineering Faculty Publications

Many techniques have been recently developed for classification of hyperspectral images (HSI) including support vector machines (SVMs), neural networks and graph-based methods. To achieve good performances for the classification, a good feature representation of the HSI is essential. A great deal of feature extraction algorithms have been developed such as principal component analysis (PCA) and independent component analysis (ICA). Sparse coding has recently shown state-of-the-art performances in many applications including image classification. In this paper, we present a feature extraction method for HSI data motivated by a recently developed sparse coding based image representation technique. Sparse coding consists of a …

Content Contribution In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

Social media allows individuals and businesses to contribute contents for public viewing. However, little is known about the underlying incentives that why content providers derive utilities from such activities. In this study, we build a dynamic structural model to recover the utility function for content providers. Our model distinguishes short-term payoffs based on ad revenue sharing from long-term payoffs driven by content providers' reputation. The model was estimated using a panel data of 914 top 1000 video providers on You Tube from Jun 7th, 2010, to Aug 7th, 2011 since top providers are more likely to be encouraged by these …

Economic Culture And Trading Behaviors In Information Markets, Khalid Nasser Alhayyan

USF Tampa Graduate Theses and Dissertations

There are four main components for influencing traders' behaviors in an information market context: trader characteristics, organizational characteristics, market design, and external information. This dissertation focuses on investigating the impact of individual trader characteristics on trading behaviors. Two newly-developed constructs, highly relevant to information market contexts, were identified to increase our understanding about trading behaviors: trader's economic culture and trader independence. The theory of planned behavior is used as the theoretical basis to postulate hypotheses for empirical testing. Data collected from subjects through a series of web-based experiments shows that trader participation can be fostered through recruiting individuals who are …

Tagline: Information Extraction For Semi-Structured Text Elements In Medical Progress Notes, Dezon K. Finch

USF Tampa Graduate Theses and Dissertations

Text analysis has become an important research activity in the Department of Veterans Affairs (VA). Statistical text mining and natural language processing have been shown to be very effective for extracting useful information from medical documents. However, neither of these techniques is effective at extracting the information stored in semi-structure text elements. A prototype system (TagLine) was developed as a method for extracting information from the semi-structured portions of text using machine learning. Features for the learning machine were suggested by prior work, as well as by examining the text, and selecting those attributes that help distinguish the various classes …

Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang

Research Collection School Of Computing and Information Systems

This study focuses on the uses of Twitter during the elections, examining whether the messages posted online are reflective of the climate of public opinion. Using Twitter data obtained during the official campaign period of the 2011 Singapore General Election, we test the predictive power of tweets in forecasting the election results. In line with some previous studies, we find that during the elections the Twitter sphere represents a rich source of data for gauging public opinion and that the frequency of tweets mentioning names of political parties, political candidates and contested constituencies could be used to make predictions about …

Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang

Research Collection School Of Computing and Information Systems

The fast development of multimedia technology and increasing availability of network bandwidth has given rise to an abundance of network data as a result of all the ever-booming social media and social websites in recent years, e.g., Flickr, Youtube, MySpace, Facebook, etc. Social network analysis has therefore become a critical problem attracting enthusiasm from both academia and industry. However, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. …

Demographic Prediction Of Mobile User From Phone Usage, Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, Michele C. Weigle

Computer Science Faculty Publications

In this paper, we describe how we use the mobile phone usage of users to predict their demographic attributes. Using call log, visited GSM cells information, visited Bluetooth devices, visited Wireless LAN devices, accelerometer data, and so on, we predict the gender, age, marital status, job and number of people in household of users. The accuracy of developed classifiers for these classification problems ranges from 45-87% depending upon the particular classification problem.

Warcreate - Create Wayback-Consumable Warc Files From Any Webpage, Mat Kelly, Michele C. Weigle, Michael L. Nelson

Computer Science Faculty Publications

[First Slide]

What is WARCreate?

• Google Chrome extension
• Creates WARC files
• Enables preservation by users from their browser
• First steps in bringing Institutional Archiving facilities to the PC

Overview Of Contrast Data Mining As A Field And Preview Of An Upcoming Book, Guozhu Dong, James Bailey

Kno.e.sis Publications

This report provides an overview of the field of contrast data mining and its applications, and offers a preview of an upcoming book on the topic. The importance of contrasting is discussed and a brief survey is given covering the following topics: general definitions and terminology for contrast patterns, representative contrast pattern mining algorithms, applications of contrast mining for fundamental data mining tasks such as classification and clustering, applications of contrast mining in bioinformatics, medicine, blog analysis, image analysis and subgroup mining, results on contrast based dataset similarity measure, and on analyzing item interaction in contrast patterns, and open research …

Computing Inconsistency Measure Based On Paraconsistent Semantics, Pascal Hitzler, Yue Ma, Guilin Qi

Computer Science and Engineering Faculty Publications

Measuring inconsistency in knowledge bases has been recognized as an important problem in several research areas. Many methods have been proposed to solve this problem and a main class of them is based on some kind of paraconsistent semantics. However, existing methods suffer from two limitations: (i) they are mostly restricted to propositional knowledge bases; (ii) very few of them discuss computational aspects of computing inconsistency measures. In this article, we try to solve these two limitations by exploring algorithms for computing an inconsistency measure of first-order knowledge bases. After introducing a four-valued semantics for first-order logic, we define an …

Object Recognition Based On Shape And Function, Akihiro Eguchi

Computer Science and Computer Engineering Undergraduate Honors Theses

This thesis explores a new approach to computational object recognition by borrowing an idea from child language acquisition studies in developmental psychology. Whereas previous image recognition research used shape to recognize and label a target object, the model proposed in this thesis also uses the function of the object resulting in a more accurate recognition. This thesis makes use of new gaming technology, Microsoft’s Kinect, in implementing the proposed new object recognition model. A demonstration of the model developed in this project properly infers different names for similarly shaped objects and the same name for differently shaped objects.

Value Relevance Of Blog Visibility, Nan Hu, Ling Liu, Arindam Tripathy, Lee J. Yao

Research Collection School Of Computing and Information Systems

This study empirically examines the effect of a non-traditional information source, namely a firm's blog visibility on the capital market valuation of firms. After controlling for earnings, book value of equity and other value relevant variables, such as traditional media exposure, R&D spending, and advertising expense, we find a positive association between a firm's blog visibility and its capital market valuation. In addition, we find blog visibility Grange causes trading, not vice versa. Our findings indicate that non-traditional information sources such as blogs help disseminate information and influence consumers' investment decisions by capturing their attention.

Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi

CBN Journal of Applied Statistics (JAS)

This study analyzed the trends and pattern of institutional credit supply to agriculture during pre- and post-financial reforms along with their determinants. It then compared the effects of reform policies on access to institutional credits in Nigerian agricultural sector before and after the reforms (1978 - 1985; and 1986 -2009). Relying mainly on time series data from CBN and NBS, it used ordinary least squares method (linear, semi-log and double log) to model the determinants of banking sector lending to the agricultural sector during the review period. The models were subjected to several econometric tests before accepting one. Chow test …

Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba

CBN Journal of Applied Statistics (JAS)

On global scale, central banks’ holdings of foreign reserves have escalated sharply in recent years. World international reserves holdings have risen significantly from US$1.2 trillion in 1995 to nearly US$10.0 trillion in June 2011. Dominant among these reserves are concentrated in the hands of few countries. Ten major holders of foreign reserves are mostly from Asia. Oil exporting countries in Africa and the Middle East are not left out in this trend. Nigeria’s foreign reserves rose from US$5.5 billion in 1999 to US$62.40 billion in July 2008, making Nigeria the twenty-fourth largest reserves holder in the world. This pace of …

Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan

CBN Journal of Applied Statistics (JAS)

This study investigates the effect of exchange rate movements on real output growth in Nigeria. Based on quarterly series for the period 1986 to 2010, the paper examines the possible direct and indirect relationship between exchange rates and GDP growth. The relationship is derived in two ways using a simultaneous equations model within a fully specified (but small) macroeconomic model. A Generalised Method of Moments (GMM) technique was explored. The estimation results suggest that there is no evidence of a strong direct relationship between changes in exchange rate and output growth. Rather, Nigeria’s economic growth has been directly affected by …

Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda

CBN Journal of Applied Statistics (JAS)

The adoption of the International Monetary Fund (IMF) Structural Adjustment Programme (SAP) in 1986 resulted in the transition from fixed exchange rate regime to floating exchange rate regime in Nigeria. Ever since, the exchange rate of naira vis-à-vis the U.S dollar has attained varying rates all through different time horizons. On this basis, this study examines the consistency, persistency, and severity (degree) of volatility in exchange rate of Nigerian currency (naira) vis-a-vis the United State dollar using monthly time series data from 1986 to 2008. The standard Purchasing Power Parity (PPP) model was used to analyze the long-run consistency of …

Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari

CBN Journal of Applied Statistics (JAS)

This research uses a cointegration VAR model to study the contemporaneous long-run dynamics of the impact of Foreign Private Investment (FPI), Interest Rate (INR) and Inflation rate (IFR) on Growth Domestic Products (GDP) in Nigeria for the period January 1970 to December 2009. The Unit Root Test suggests that all the variables are integrated of order 1. The VAR model was appropriately identified using AIC information criteria and the VECM model has exactly one cointegration relation. The study further investigates the causal relationship using the Granger causality analysis of VECM which indicates a uni-directional causality relationship between GDP and FDI …

Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola

CBN Journal of Applied Statistics (JAS)

The paper examines the relationship between banking sector credit and economic growth in Nigeria over the period 1970-2008. The causal links between the pairs of variables of interest were established using Granger causality test while a Two-Stage Least Squares (TSLS) estimation technique was used for the regression models. The results of Granger causality test show evidence of unidirectional causal relationship from GDP to private sector credit (PSC) and from industrial production index (IND) to GDP. Estimated regression models indicate that private sector credit impacts positively on economic growth over the period of coverage in this study. However, lending (interest) rate …

Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li

Research Collection School Of Computing and Information Systems

Modeling continuous social strength rather than conventional binary social ties in the social network can lead to a more precise and informative description of social relationship among people. In this paper, we study the problem of social strength modeling (SSM) for the users in a social media community, who are typically associated with diverse form of data. In particular, we take Flickr---the most popular online photo sharing community---as an example, in which users are sharing their experiences through substantial amounts of multimodal contents (e.g., photos, tags, geo-locations, friend lists) and social behaviors (e.g., commenting and joining interest groups). Such heterogeneous …

Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

With the popularity of social media, web users tend to spend more time than before for sharing their experience and interest in online photo-sharing sites. The wide variety of sharing behaviors generate different metadata which pose new opportunities for the discovery of communities. We propose a new approach, named context-based friend suggestion, to leverage the diverse form of contextual cues for more effective friend suggestion in the social media community. Different from existing approaches, we consider both visual and geographical cues, and develop two user-based similarity measurements, i.e., visual similarity and geo similarity for characterizing user relationship. The problem of …

Content Contribution Under Revenue Sharing And Reputation Concern In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

A key feature of social media is that it allows individuals and businesses to contribute contents for public viewing. However, little is known about how content providers derive payoffs from such activities. In this study, we build a dynamic structural model to recover the utility function for content providers. Our model distinguishes short-term payoffs based on ad revenue sharing from long-term payoffs driven by content providers’ reputation. The model was estimated using a panel data of 914 top 1000 providers and 381 randomly selected providers on YouTube from Jun 7th, 2010, to Aug 7th, 2011. The two different sets of …

Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes

Research Collection School Of Computing and Information Systems

The Third Workshop on Social Media (WSM2011) continues the series of Workshops on Social Media in 2009 and 2010 and has been established as a platform for the presentation and discussion of the latest, key research issues in social media analysis, exploration, search, mining, and emerging new social media applications. It is held in conjunction with the ACM International Multimedia Conference (MM'11) at Scottsdale, Arizona, USA, 2011 and has attracted contributions on various aspects of social media including data mining from social media, content organization, geo-localization, personalization, recommendation systems, user experience, machine learning and social media approaches and architectures for …