A Proposed Framework for Understanding Information Security Culture and Practices in the Saudi Context

An examination of Information Security (IS) and Information Security Management (ISM) research in Saudi Arabia has shown the need for more rigorous studies focusing on the implementation and adoption processes involved with IS culture and practices. Overall, there is a lack of academic and professional literature about ISM and more specifically IS culture in Saudi Arabia. Therefore, the overall aim of this paper is to identify issues and factors that assist the implementation and the adoption of IS culture and practices within the Saudi environment. The goal of this paper is to identify the important conditions for creating an information security culture in Saudi Arabian organizations. We plan to use this framework to investigate whether security culture has emerged into practices in Saudi Arabian organizations.

Information security culture : a behaviour compliance conceptual framework

Understanding the complex dynamic and uncertain characteristics of organisational employees who perform authorised or unauthorised information security activities is deemed to be a very important and challenging task. This paper presents a conceptual framework for classifying and organising the characteristics of organisational subjects involved in these information security practices. Our framework expands the traditional Human Behaviour and the Social Environment perspectives used in social work by identifying how knowledge, skills and individual preferences work to influence individual and group practices with respect to information security management. The classification of concepts and characteristics in the framework arises from a review of recent literature and is underpinned by theoretical models that explain these concepts and characteristics. Further, based upon an exploratory study of three case organisations in Saudi Arabia involving extensive interviews with senior managers, department managers, IT managers, information security officers, and IT staff; this article describes observed information security practices and identifies several factors which appear to be particularly important in influencing information security behaviour. These factors include values associated with national and organisational culture and how they manifest in practice, and activities related to information security management.

Mining Negative Relevance Feedback for Information Filtering

It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.

An effective model of using negative relevance feedback for information filtering

Over the years, people have often held the hypothesis that negative feedback should be very useful for largely improving the performance of information filtering systems; however, we have not obtained very effective models to support this hypothesis. This paper, proposes an effective model that use negative relevance feedback based on a pattern mining approach to improve extracted features. This study focuses on two main issues of using negative relevance feedback: the selection of constructive negative examples to reduce the space of negative examples; and the revision of existing features based on the selected negative examples. The former selects some offender documents, where offender documents are negative documents that are most likely to be classified in the positive group. The later groups the extracted features into three groups: the positive specific category, general category and negative specific category to easily update the weight. An iterative algorithm is also proposed to implement this approach on RCV1 data collections, and substantial experiments show that the proposed approach achieves encouraging performance.

International students using online information resources to learn

This qualitative study views international students as information-using learners, through an information literacy lens. Focusing on the experiences of 25 international students at two Australian universities, the study investigates how international students use online information resources to learn, and identifies associated information literacy learning needs. An expanded critical incident approach provided the methodological framework for the study. Building on critical incident technique, this approach integrated a variety of concepts and research strategies. The investigation centred on real-life critical incidents experienced by the international students whilst using online resources for assignment purposes. Data collection involved semi-structured interviews and an observed online resource-using task. Inductive data analysis and interpretation enabled the creation of a multifaceted word picture of international students using online resources and a set of critical findings about their information literacy learning needs. The study’s key findings reveal: • the complexity of the international students’ experience of using online information resources to learn, which involves an interplay of their interactions with online resources, their affective and reflective responses to using them, and the cultural and linguistic dimensions of their information use. • the array of strengths as well as challenges that the international students experience in their information use and learning. • an apparent information literacy imbalance between the international students’ more developed information skills and less developed critical and strategic approaches to using information • the need for enhanced information literacy education that responds to international students’ identified information literacy needs. Responding to the findings, the study proposes an inclusive informed learning approach to support reflective information use and inclusive information literacy learning in culturally diverse higher education environments.

The self-Googling phenomenon : investigating the performance of personalized information resources

This paper investigates self–Googling through the monitoring of search engine activities of users and adds to the few quantitative studies on this topic already in existence. We explore this phenomenon by answering the following questions: To what extent is the self–Googling visible in the usage of search engines; is any significant difference measurable between queries related to self–Googling and generic search queries; to what extent do self–Googling search requests match the selected personalised Web pages? To address these questions we explore the theory of narcissism in order to help define self–Googling and present the results from a 14–month online experiment using Google search engine usage data.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Word Segmentation for Chinese Wikipedia Using N-Gram Mutual Information

In this paper, we propose an unsupervised segmentation approach, named "n-gram mutual information", or NGMI, which is used to segment Chinese documents into n-character words or phrases, using language statistics drawn from the Chinese Wikipedia corpus. The approach alleviates the tremendous effort that is required in preparing and maintaining the manually segmented Chinese text for training purposes, and manually maintaining ever expanding lexicons. Previously, mutual information was used to achieve automated segmentation into 2-character words. The NGMI approach extends the approach to handle longer n-character words. Experiments with heterogeneous documents from the Chinese Wikipedia collection show good results.

User behaviours and intentions in digital media in Australia

This paper reports findings from a study of user behaviours and intentions towards online news and information in Australia, undertaken by the Queensland University of Technology Creative Industries Faculty and the Smart Services Cooperative Research Centre. It has used a literature review, online survey, focus groups and interviews to explore attitudes and behaviours towards online news and information. The literature review on consumer user of online media highlighted emerging technical opportunities, and flagged existing barriers to access experienced by consumers in the Australian digital media sector. The literature review highlighted multiple disconnects between consumer interests in online news and their ability to fulfil them. This presents an opportunity for news entities to appraise and resolve. Doing so may enhance their service offering, attract consumers and improve loyalty. These themes were further explored by the survey. The survey results revealed three typologies of user, described as ‘convenience’, ‘loyal’ and ‘customising’. Convenience users tend to access news by default, for example when they log out of email. Loyal users seek out a trusted brand such as mainstream news mastheads. Customising users tend to tailor news to their preferences, and be the first to use leading edge media. Respondents to the survey were then invited to participate in focus groups, which aimed to test the survey results. Consumer perceptions and attitudes are important factors in progression towards an information economy, because ultimately consumers are customers. By segmenting the online news market according to customer typology, media providers may identify new opportunities to attract and retain customers.

Competitiveness factors : a study of the real estate market in China

The execution of 'macro-adjustment' policies by the central government to cool down the overheated real estate market in the past few years has created an unfavourable operating environment for real estate developers in Mainland China. Developers need to rethink their business model and create a new form of competitive advantage in order to survive. Despite this, research into the factors that influence the competitiveness of the real estate market in China has been limited. Therefore, a survey of 58 real estate actitioners, experts and academics in China was conducted to probe opinion on the factors that influence competitiveness in real estate firms in China. Survey results suggest that the developer's financial competency, market coverage and management competencies are vital to its competitiveness. Findings also highlight the importance of industry ecognition/award, share in different types of property sales/development projects, profit after tax, growth rate of their securities price, and diversification of R&D in reflecting the competitiveness of real estate developers in China. The findings provide an insight into the factors that influence competitiveness in China's real estate market and also assist practitioners to formulate competitiveness improvement strategies.

A 5 year review of information requests to QISU

The Queensland Injury Surveillance Unit (QISU) has been collecting and analysing injury data in Queensland since 1988. QISU data is collected from participating emergency departments (EDs) in urban, rural and remote areas of Queensland. Using this data, QISU produces several injury bulletins per year on selected topics, providing a picture of Queensland injury, and setting this in the context of relevant local, national and international research and policy. These bulletins are used by numerous government and non-government groups to inform injury prevention and practice throughout the state. QISU bulletins are also used by local and state media to inform the general public of injury risk and prevention strategies. In addition to producing the bulletins, QISU regularly responds to requests for information from a variety of sources. These requests often require additional analysis of QISU data to tailor the response to the needs of the end user. This edition of the bulletin reviews 5 years of information requests to QISU.

Planning for smart urban ecosystems : information technology applications for capacity building in environmental decision making

Since the industrial revolution, our world has experienced rapid and unplanned industrialization and urbanization. As a result, we have had to cope with serious environmental challenges. In this context, an explanation of how smart urban ecosystems can emerge, gains a crucial importance. Capacity building and community involvement have always been key issues in achieving sustainable development and enhancing urban ecosystems. By considering these, this paper looks at new approaches to increase public awareness of environmental decision making. This paper will discuss the role of Information and Communication Technologies (ICT), particularly Webbased Geographic Information Systems (Web-based GIS) as spatial decision support systems to aid public participatory environmental decision making. The paper also explores the potential and constraints of these webbased tools for collaborative decision making.

Using information criteria to select the correct variance–covariance structure for longitudinal data in ecology

1. Ecological data sets often use clustered measurements or use repeated sampling in a longitudinal design. Choosing the correct covariance structure is an important step in the analysis of such data, as the covariance describes the degree of similarity among the repeated observations. 2. Three methods for choosing the covariance are: the Akaike information criterion (AIC), the quasi-information criterion (QIC), and the deviance information criterion (DIC). We compared the methods using a simulation study and using a data set that explored effects of forest fragmentation on avian species richness over 15 years. 3. The overall success was 80.6% for the AIC, 29.4% for the QIC and 81.6% for the DIC. For the forest fragmentation study the AIC and DIC selected the unstructured covariance, whereas the QIC selected the simpler autoregressive covariance. Graphical diagnostics suggested that the unstructured covariance was probably correct. 4. We recommend using DIC for selecting the correct covariance structure.

Introduction : the global flow of creative ideas

In the era of late modernism, various pressures play a decisive role in shaping the texture and meaning of the world around us. Population, work, transportation, new technologies of information and communication, lifestyle cultures and other forces are increasingly mobile, and this in turn helps make for a new set of public and personal surroundings. Social life everywhere now appears to share more and more in an international (if not a global) order, even if inequality and stratification remain common inside territories and across territories. Still, the perception is that a particular cultural life is increasingly universal. More and more consumers come to share in its practices and products, with those products becoming more and more homogeneous. This standardization argument finds much support in the apparent internationalization of many elements of media, entertainment, leisure and lifestyle cultures, with cultural conglomerates determined to maximize their global market reach. Once upon a time, in order to understand the economic, political and cultural forces affecting citizens and society, it was mostly deemed sufficient to look within the boundaries of the nation-state. Over the past two decades, these same pressures of globalization have impacted on critical research, highlighting the methodological need to adopt an optic that is more cross-border and transcultural as a means of gaining greater understanding of cultural life.