Reinforcing the security of corporate information resources:a critical review of the role of the acceptable use policy

Increasingly users are seen as the weak link in the chain, when it comes to the security of corporate information. Should the users of computer systems act in any inappropriate or insecure manner, then they may put their employers in danger of financial losses, information degradation or litigation, and themselves in danger of dismissal or prosecution. This is a particularly important concern for knowledge-intensive organisations, such as universities, as the effective conduct of their core teaching and research activities is becoming ever more reliant on the availability, integrity and accuracy of computer-based information resources. One increasingly important mechanism for reducing the occurrence of inappropriate behaviours, and in so doing, protecting corporate information, is through the formulation and application of a formal ‘acceptable use policy (AUP). Whilst the AUP has attracted some academic interest, it has tended to be prescriptive and overly focussed on the role of the Internet, and there is relatively little empirical material that explicitly addresses the purpose, positioning or content of real acceptable use policies. The broad aim of the study, reported in this paper, is to fill this gap in the literature by critically examining the structure and composition of a sample of authentic policies – taken from the higher education sector – rather than simply making general prescriptions about what they ought to contain. There are two important conclusions to be drawn from this study: (1) the primary role of the AUP appears to be as a mechanism for dealing with unacceptable behaviour, rather than proactively promoting desirable and effective security behaviours, and (2) the wide variation found in the coverage and positioning of the reviewed policies is unlikely to be fostering a coherent approach to security management, across the higher education sector.

Polymer degradation and stability

This edition of Polymer Degradation and Stability is dedicated to papers which were presented in the session on ‘Chemical Modification’ at the Third International Conference on Modification Degradation and Stabilisation of Polymers (MoDeSt) held in Lyon in August 2004. This was the third meeting of the MoDeSt Society which was set up in the year 2000 under the chairmanship of Professor Franco LaMantia; the earlier meetings were held in Palermo (2000) and Budapest (2002). The overall goal of the MoDeSt Society is to promote the latest research carried out in University laboratories, in public organisations and in industry through publications, and organisation of biannual scientific conferences and workshops that act as forums for scientific developments and for promoting networking between academics and industrialists from across the field of polymer modification, degradation and stabilisation. In September 2004, Professor Norman Billingham was elected as Chairman of the Society. The conference was organised by Dr Alain Michel and Veronique Bounor-Legare of the University Claude Bernard, Lyon 1, attracting over 250 delegates with the ‘Chemical Modification’ Session alone enjoying 54 oral presentations and many more poster presentations. We are all very grateful to the organisers for running such a successful and enjoyable meeting. I wish to thank my co-editors, Professors Philippe Dubois and Domenico Acierno and Dr Alain Michel, for their cooperation in the editorial task of the papers published in this special issue. On behalf of the editors of this issue, I wish to express our appreciation to the Editor-in-Chief of Polymer Degradation and Stability, Professor Norman Billingham, for the support and help received during the preparation of this special issue.

A framework for automated construction of resource space based on background knowledge

Resource Space Model is a kind of data model which can effectively and flexibly manage the digital resources in cyber-physical system from multidimensional and hierarchical perspectives. This paper focuses on constructing resource space automatically. We propose a framework that organizes a set of digital resources according to different semantic dimensions combining human background knowledge in WordNet and Wikipedia. The construction process includes four steps: extracting candidate keywords, building semantic graphs, detecting semantic communities and generating resource space. An unsupervised statistical language topic model (i.e., Latent Dirichlet Allocation) is applied to extract candidate keywords of the facets. To better interpret meanings of the facets found by LDA, we map the keywords to Wikipedia concepts, calculate word relatedness using WordNet's noun synsets and construct corresponding semantic graphs. Moreover, semantic communities are identified by GN algorithm. After extracting candidate axes based on Wikipedia concept hierarchy, the final axes of resource space are sorted and picked out through three different ranking strategies. The experimental results demonstrate that the proposed framework can organize resources automatically and effectively.©2013 Published by Elsevier Ltd. All rights reserved.

Summarization of scientific documents by detecting common facts in citations

Reading scientific articles is more time-consuming than reading news because readers need to search and read many citations. This paper proposes a citation guided method for summarizing multiple scientific papers. A phenomenon we can observe is that citation sentences in one paragraph or section usually talk about a common fact, which is usually represented as a set of noun phrases co-occurring in citation texts and it is usually discussed from different aspects. We design a multi-document summarization system based on common fact detection. One challenge is that citations may not use the same terms to refer to a common fact. We thus use term association discovering algorithm to expand terms based on a large set of scientific article abstracts. Then, citations can be clustered based on common facts. The common fact is used as a salient term set to get relevant sentences from the corresponding cited articles to form a summary. Experiments show that our method outperforms three baseline methods by ROUGE metric.©2013 Elsevier B.V. All rights reserved.

Incorporating Water Sensitive Urban Design (WSUD) practices into the planning context:the conceptual case for lot-scale developments

In recent decades, a number of sustainable strategies and polices have been created to protect and preserve our water environments from the impacts of growing communities. The Australian approach, Water Sensitive Urban Design (WSUD), defined as the integration of urban planning and design with the urban water cycle management, has made considerable advances on design guidelines since 2000. WSUD stormwater management systems (e.g. wetlands, bioretentions, porous pavement etc), also known as Best Management Practices (BMPs) or Low Impact Development (LID), are slowly gaining popularity across Australia, the USA and Europe. There have also been significant improvements in how to model the performance of the WSUD technologies (e.g. MUSIC software). However, the implementation issues of these WSUD practices are mainly related to ongoing institutional capacity. Some of the key problems are associated with a limited awareness of urban planners and designers; in general, they have very little knowledge of these systems and their benefits to the urban environments. At the same time, hydrological engineers should have a better understanding of building codes and master plans. The land use regulations are equally as important as the physical site conditions for determining opportunities and constraints for implementing WSUD techniques. There is a need for procedures that can make a better linkage between urban planners and WSUD engineering practices. Thus, this paper aims to present the development of a general framework for incorporating WSUD technologies into the site planning process. The study was applied to lot-scale in the Melbourne region, Australia. Results show the potential space available for fitting WSUD elements, according to building requirements and different types of housing densities. © 2011 WIT Press.

Formal methods @ runtime

Heuristics, simulation, artificial intelligence techniques and combinations thereof have all been employed in the attempt to make computer systems adaptive, context-aware, reconfigurable and self-managing. This paper complements such efforts by exploring the possibility to achieve runtime adaptiveness using mathematically-based techniques from the area of formal methods. It is argued that formal methods @ runtime represents a feasible approach, and promising preliminary results are summarised to support this viewpoint. The survey of existing approaches to employing formal methods at runtime is accompanied by a discussion of their challenges and of the future research required to overcome them. © 2011 Springer-Verlag.

An angle-based interest model for text recommendation

Building an interest model is the key to realize personalized text recommendation. Previous interest models neglect the fact that a user may have multiple angles of interests. Different angles of interest provide different requests and criteria for text recommendation. This paper proposes an interest model that consists of two kinds of angles: persistence and pattern, which can be combined to form complex angles. The model uses a new method to represent the long-term interest and the short-term interest, and distinguishes the interest on object and the interest on the link structure of objects. Experiments with news-scale text data show that the interest on object and the interest on link structure have real requirements, and it is effective to recommend texts according to the angles.

Automatic maintenance of category hierarchy

Category hierarchy is an abstraction mechanism for efficiently managing large-scale resources. In an open environment, a category hierarchy will inevitably become inappropriate for managing resources that constantly change with unpredictable pattern. An inappropriate category hierarchy will mislead the management of resources. The increasing dynamicity and scale of online resources increase the requirement of automatically maintaining category hierarchy. Previous studies about category hierarchy mainly focus on either the generation of category hierarchy or the classification of resources under a pre-defined category hierarchy. The automatic maintenance of category hierarchy has been neglected. Making abstraction among categories and measuring the similarity between categories are two basic behaviours to generate a category hierarchy. Humans are good at making abstraction but limited in ability to calculate the similarities between large-scale resources. Computing models are good at calculating the similarities between large-scale resources but limited in ability to make abstraction. To take both advantages of human view and computing ability, this paper proposes a two-phase approach to automatically maintaining category hierarchy within two scales by detecting the internal pattern change of categories. The global phase clusters resources to generate a reference category hierarchy and gets similarity between categories to detect inappropriate categories in the initial category hierarchy. The accuracy of the clustering approaches in generating category hierarchy determines the rationality of the global maintenance. The local phase detects topical changes and then adjusts inappropriate categories with three local operations. The global phase can quickly target inappropriate categories top-down and carry out cross-branch adjustment, which can also accelerate the local-phase adjustments. The local phase detects and adjusts the local-range inappropriate categories that are not adjusted in the global phase. By incorporating the two complementary phase adjustments, the approach can significantly improve the topical cohesion and accuracy of category hierarchy. A new measure is proposed for evaluating category hierarchy considering not only the balance of the hierarchical structure but also the accuracy of classification. Experiments show that the proposed approach is feasible and effective to adjust inappropriate category hierarchy. The proposed approach can be used to maintain the category hierarchy for managing various resources in dynamic application environment. It also provides an approach to specialize the current online category hierarchy to organize resources with more specific categories.

Semantics, knowledge and grids on big data

Semantics, knowledge and Grids represent three spaces where people interact, understand, learn and create. Grids represent the advanced cyber-infrastructures and evolution. Big data influence the evolution of semantics, knowledge and Grids. Exploring semantics, knowledge and Grids on big data helps accelerate the shift of scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies.