Thesis (Ph.D.)--Drexel University, 2009. / Includes abstract and vita. Includes bibliographical references (leaves 140-146).

Thesis (Ph.D.)--Indiana University, Dept. of Computer Science, 2009. / Title from PDF t.p. (viewed on Jul 20, 2010). Source: Dissertation Abstracts International, Volume: 70-12, Section: B, page: 7684. Adviser: Filippo Menczer.

Thesis (Ph.D.)--Drexel University, 2010. / Includes abstract and vita. Includes bibliographical references (leaves 141-150).

Thesis (Ph.D.)--Indiana University, School of Library and Information Science, 2006. / "Title from dissertation home page (viewed July 10, 2007)." Source: Dissertation Abstracts International, Volume: 67-08, Section: A, page: 2796. Adviser: Javed Mostafa.

<p> The purpose of this qualitative, multi-case study was to explain Tuckman&rsquo;s attributes within software development when using a collocated software designed methodology in a non-collocated setting. Agile is a software development methodology that is intended for use in a collocated setting; however, organizations are using it in a non-collocated setting, which is increasing the software errors in the final software product. The New Agile Process for Distributed Projects (NAPDiP) was developed to fix these software errors that arise when using Agile in a non-collocated setting but have not been effective. This research utilized Tuckman's team theory to explore the disparity related to why these errors still occur. The research question asked is how software development programmers explain Tuckman's attributes (i.e., forming, storming, norming, performing) on software development projects. The study adopted a qualitative model using nomothetic major and minor themes in the exploration of shared expressions of sentiments from participants. The study&rsquo;s population came from seven participants located in the United States and India who met the requirement of using the Agile development methodology and work for organizations on teams with a size of at least thirty individuals from various organizations. A total of seven participants reached saturation in this multi-case study supporting the research question explored. The findings of the research demonstrated that development teams do not meet all stages and attributes of Tuckman&rsquo;s team development. Future research should explore additional ways that software development teams satisfy a more significant number of Tuckman&rsquo;s team development stages.</p><p>

<p> With privacy settings on social networking sites (SNS) perceived as complex and difficult to use and maintain, young adults can be left vulnerable to others accessing and using their personal information. Consequences of not regulating the boundaries their information on SNS include the ability for current and future employers to make career-impacting decisions based upon their online reputation that may include disqualifying them as job candidates. </p><p> On SNS, such as Facebook, LinkedIn, and Twitter, young adults must decide on how to manage their online reputation by regulating boundaries to their own personal and professional information and identities. One known practice for the regulation of boundaries is the use of multiple profile management (MPM), where users of SNS create and use multiple accounts on a SNS and separate the social and professional identities that they disclose publicly and privately. </p><p> The purpose of the study was to understand the lived experiences of young adults in how they regulate boundaries on SNS, through the use of MPM, as they manage their online reputation to different audiences. The practice was studied by applying interpretative phenomenological analysis (IPA) through interviewing young adults of 18-23 years of age, who use MPM on a SNS. Semi-structured interviews permitted participants to provide in-depth descriptions of their lived experiences.</p><p> Eight themes were identified and described based on the analysis of the interviews that include: SNS use with online audiences, motivations for using MPM, the processes for the presentation of self, online search results, privacy settings, untagging SNS posts, self-editing and censorship, and new features. The themes describe the complexity and challenges that young adults face with regulating boundaries with their professional and social identities online through the use of MPM.</p><p> Findings from this study have implications for a variety of audiences. Through the findings of this study, SNS developers can introduce new features, improve usability related to privacy management, and further encourage use of their networks. Users of SNS can use this study to understand risks of using SNS and for learning of practices for how to manage their online reputation on SNS.</p><p>

<p> This is a study of the behavioral biometric of smartphone motion to determine the potential accuracy of authenticating users on smartphone devices. The study used the application Sensor Kinetics Pro and the Weka machine-learning library to analyze accelerometer and gyroscope data. The study conducted three experiments for the research. They were conducted in spring 2015, fall 2015, and spring 2016. The final experiment in spring 2016 used six Android-based smartphones to capture data from 60 participants and each participant performed 20 trials of two motions: bringing the phone up to eye level for review, and then bringing the phone to the ear, resulting in 1200 runs. The resulting sensor datasets were used for machine learning training and testing. The study used filtering data to remove noise, and then aggregated the data and used them as inputs to the Weka Machine Learning tool. The study used several machine classification algorithms: the Multilayer Perception (MLP), k-Nearest Neighbor (k-NN), Na&iuml;ve Bayes (N-B), and Support Vector Machine (SVM) machine learning classification algorithms. The study reached authentication accuracies of up to 93% thus supporting the use of behavioral motion biometrics for user authentication. Preliminary studies with smaller numbers of participants in spring 2015 and in fall 2015 also produced 90%+ authentication accuracy.</p><p>

Millions of books from public libraries and private collections have been scanned by various organizations in the last decade. The motivation is to preserve the written human heritage in electronic format for durable storage and efficient access. The information buried in these large book collections has always been of major interest for scholars from various disciplines. Several interesting research problems can be defined over large collections of scanned books given their corresponding optical character recognition (OCR) outputs. At the highest level, one can view the entire collection as a whole and discover interesting contextual relationships or linkages between the books. A more traditional approach is to consider each scanned book separately and perform information search and mining at the book level. Here we also show that one can view each book as a whole composed of chapters, sections, paragraphs, sentences, words or even characters positioned in a particular sequential order sharing the same global context. The information inherent in the entire context of the book is referred to as "global information" and it is demonstrated by addressing a number of research questions defined for scanned book collections. The global sequence information is one of the different types of global information available in textual documents. It is useful for discovering content overlap and similarity across books. Each book has a specific flow of ideas and events which distinguishes it from other books. If this global order is changed, then the flow of events and consequently the story changes completely. This argument is true across document translations as well. Although the local order of words in a sentence might not be preserved after translation, sentences, paragraphs, sections and chapters are likely to follow the same global order. Otherwise the two texts are not considered to be translations of each other. A global sequence alignment approach is therefore proposed to discover the contextual similarity between the books. The problem is that conventional sequence alignment algorithms are slow and not robust for book length documents especially with OCR errors, additional or missing content. Here we propose a general framework which can be used to efficiently align and compare the textual content of the books at various coarseness levels and even across languages. In a nut-shell, the framework uses the sequence of words which appear only once in the entire book (referred to as "the sequence of unique words") to represent the text. This representation is compact and it is highly descriptive of the content along with the global word sequence information. It is shown to be more accurate compared to the state of the art for efficiently i) detecting which books are partial duplicates in large scanned book collections (DUPNIQ), and, ii) finding which books are translations of each other without explicitly translating the entire texts using statistical machine translation approaches (TRANSNIQ). Using the global order of unique words and their corresponding positions in the text, one can also generate the complete text alignment efficiently using a recursive approach. The Recursive Text Alignment Scheme (RETAS) is several orders of magnitude faster than the conventional sequence alignment approaches for long texts and it is later used for iii) the automatic evaluation of OCR accuracy of books given the OCR outputs and the corresponding electronic versions, iv) mapping the corresponding portions of the two books which are known to be partial duplicates, and finally it is generalized for v) aligning long noisy texts across languages (Recursive Translation Alignment - RTA). Another example of the global information is that books are mostly printed in a single global font type. Here we demonstrate that the global font feature along with the letter sequence information can be used for facilitating and/or improving text search in noisy page images. There are two contributions in this area: (vi) an efficient word spotting framework for searching text in noisy document images, and, (vii) a state of the art dependence model approach to resolve arbitrary text queries using visual features. The effectiveness of these approaches is demonstrated for books printed in different scripts for which there is no OCR engine available or the recognition accuracy is low.

<p> Online reviews have become a popular method for consumers to express personal evaluation about products. Ecommerce firms have invested heavily into review systems because of the impact of product reviews on product sales and shopping behavior. However, the usage of product reviews is undermined by the increasing appearance of shill or fake reviews. As initial steps to deter and detect shill reviews, this study attempts to understand characteristics of shill reviews and influences of shill reviews on product quality and shopping behavior. To reveal the linguistic characteristics of shill reviews, this study compares shill reviews and normal reviews on informativeness, readability and subjectivity level. The results show that these features can be used as reliable indicators to separate shill reviews from normal reviews. An experiment was conducted to measure the impact of shill reviews on perceived product quality. The results showed that positive shill reviews significantly increased quality perceptions of consumers for thinly reviewed products. This finding provides strong evidence about the risks of shill reviews and emphasizes the need to develop effective detection and prevention methods.</p>

<p> Malicious Insider threats consist of employees, contractors, or business partners who either have current authorized access, or have had authorized access to an organization's critical information and have intentionally misused that access in a manner that compromised the organization. Although incidents initiated by malicious insiders are fewer in number than those initiated by external threats, insider incidents are more costly on average because the threat is already trusted by the organization and often has privileged access to the organization's most sensitive information. In spite of the damage they cause there are indications that the seriousness of insider incidents are underappreciated as threats by management. The purpose of this research was to investigate who constitutes MI threats, why and how they initiate attacks, the extent to which MI activity can be modeled or predicted, and to suggest some risk mitigation strategies. The results reveal that addressing the Malicious Insider threat is much more than just a technical issue. Dealing effectively with the threat involves managing the dynamic interaction between employees, their work environment and work associates, the systems with which they interact, and organizational policies and procedures. Techniques for detecting and mitigating the threat are available and can be effectively applied. Some of the procedural and technical methods include definition of, follow through, and consistent application of corporate, and dealing with adverse events indigenous to the business environment. Other methods include conduct of a comprehensive Malicious Insider risk assessment, selective monitoring of employees in response to behavioral precursors, minimizing unknown access paths, control of the organization's production software baseline, and effective use of peer reporting.</p><p> Keywords: Cybersecurity, Professor Paul Pantani, CERT, insider, threat, IDS, SIEMS. FIM, RBAC, ABAC, behavioral, peer, precursors, access, authentication, predictive, analytics, system, dynamics, demographics.</p>