Experimenting with an intrusion detection system for encrypted networks

Network-based Intrusion Detection Systems (NIDSs) analyse network traffic to detect instances of malicious activity. Typically, this is only possible when the network traffic is accessible for analysis. With the growing use of Virtual Private Networks (VPNs) that encrypt network traffic, the NIDS can no longer access this crucial audit data. In this paper, we present an implementation and evaluation of our approach proposed in Goh et al. (2009). It is based on Shamir's secret-sharing scheme and allows a NIDS to function normally in a VPN without any modifications and without compromising the confidentiality afforded by the VPN.

Service aggregators in business networks

This position paper examines the development of a dedicated service aggregator role in business networks. We predict that these intermediaries will soon emerge in service ecosystems and add value through the application of dedicated domain knowledge in the process of creating new, innovative services or service bundles based on the aggregation, composition, integration or orchestration of existing services procured from different service providers in the service ecosystem. We discuss general foundations of service aggregators and present Fourth-Party Logistics Providers as a real-world example of emerging business service aggregators. We also point out a demand for future research, e.g. into governance models, risk management tools, service portfolio management approaches and service bundling techniques, to be able to better understand core determinants of competitiveness and success of service aggregators.

The importance of a new kind of learning in collaborative networks

There is wide agreement that in order to manage the increasingly complex and uncertain tasks of business, government and community, organizations can no longer operate in supreme isolation, but must develop a more networked approach. Networks are not ‘business as usual’. Of particular note is what has been referred to as collaborative networks. Collaborative networks now constitute a significant part of our institutional infrastructure. A key driver for the proliferation of these multiorganizational arrangements is their ability to facilitate the learning and knowledge necessary to survive or to respond to increasingly complex social issues In this regard the emphasis is on the importance of learning in networks. Learning applies to networks in two different ways. These refer to the kinds of learning that occur as part of the interactive processes of networks. This paper looks at the importance of these two kinds of learning in collaborative networks. The first kind of learning relates to networks as learning networks or communities of practice. In learning networks people exchange ideas with each other and bring back this new knowledge for use in their own organizations. The second type of learning is referred to as network learning. Network learning refers to how people in collaborative networks learn new ways of communicating and behaving with each other. Network learning has been described as transformational in terms of leading to major systems changes and innovation. In order to be effective, all networks need to be involved as learning networks; however, collaborative networks must also be involved in network learning to be effective. In addition to these two kinds of learning in collaborative networks this paper also focuses on the importance of how we learn about collaborative networks. Maximizing the benefits of working through collaborative networks is dependent on understanding their unique characteristics and how this impacts on their operation. This requires a new look at how we specifically teach about collaborative networks and how this is similar to and/or different from how we currently teach about interorgnizational relations.

Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in western Africa

Objective We aimed to predict sub-national spatial variation in numbers of people infected with Schistosoma haematobium, and associated uncertainties, in Burkina Faso, Mali and Niger, prior to implementation of national control programmes. Methods We used national field survey datasets covering a contiguous area 2,750 × 850 km, from 26,790 school-aged children (5–14 years) in 418 schools. Bayesian geostatistical models were used to predict prevalence of high and low intensity infections and associated 95% credible intervals (CrI). Numbers infected were determined by multiplying predicted prevalence by numbers of school-aged children in 1 km2 pixels covering the study area. Findings Numbers of school-aged children with low-intensity infections were: 433,268 in Burkina Faso, 872,328 in Mali and 580,286 in Niger. Numbers with high-intensity infections were: 416,009 in Burkina Faso, 511,845 in Mali and 254,150 in Niger. 95% CrIs (indicative of uncertainty) were wide; e.g. the mean number of boys aged 10–14 years infected in Mali was 140,200 (95% CrI 6200, 512,100). Conclusion National aggregate estimates for numbers infected mask important local variation, e.g. most S. haematobium infections in Niger occur in the Niger River valley. Prevalence of high-intensity infections was strongly clustered in foci in western and central Mali, north-eastern and northwestern Burkina Faso and the Niger River valley in Niger. Populations in these foci are likely to carry the bulk of the urinary schistosomiasis burden and should receive priority for schistosomiasis control. Uncertainties in predicted prevalence and numbers infected should be acknowledged and taken into consideration by control programme planners.

Introduction to the Proceedings of the 1st EDOC 2009 Workshop on Service-Oriented Business Networks and Ecosystems (SOBNE '09)

The first Workshop on Service-Oriented Business Networks and Ecosystems (SOBNE ’09) is held in conjunction with the 13th IEEE International EDOC Conference on 2 September 2009 in Auckland, New Zealand. The SOBNE ’09 program includes 9 peer-reviewed papers (7 full and 2 short papers) and an open discussion session. This introduction to the Proceedings of SOBNE ’09 starts with a brief background of the motivation for the workshop. Next, it contains a short description of the peer-reviewed papers, and finally, after some concluding statements and the announcement of the winners of the Best Reviewer Award and the Most Promising Research Award, it lists the members of the SOBNE ’09 Program Committee and external reviewers of the workshop submissions.

Generating rules with predicates, terms and variables from the pruned neural networks

Artificial neural networks (ANN) have demonstrated good predictive performance in a wide range of applications. They are, however, not considered sufficient for knowledge representation because of their inability to represent the reasoning process succinctly. This paper proposes a novel methodology Gyan that represents the knowledge of a trained network in the form of restricted first-order predicate rules. The empirical results demonstrate that an equivalent symbolic interpretation in the form of rules with predicates, terms and variables can be derived describing the overall behaviour of the trained ANN with improved comprehensibility while maintaining the accuracy and fidelity of the propositional rules.

Bayesian latent trait modeling of migraine symptom data

Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population sample using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.

'Try hard' : Attitudes to advertising in online social networks

Advertising has recently entered many new spaces it does not fully understand. The rules that apply in traditional media do not always translate in new media environments. However, their low cost of entry and the availability of hard-to-reach target markets, such as Generation Y, make environments such as online social networking sites attractive to marketers. This paper accumulates teenage perspectives from two qualitative studies to identify attitudes towards advertising in online social network sites and develop implications for marketers seeking to advertising on social network sites.

Rivalry within and between strategic networks : an investigation of the United States Automotive Industry

As a consequence of the increased incidence of collaborative arrangements between firms, the competitive environment characterising many industries has undergone profound change. It is suggested that rivalry is not necessarily enacted by individual firms according to the traditional mechanisms of direct confrontation in factor and product markets, but rather as collaborative orchestration between a number of participants or network members. Strategic networks are recognised as sets of firms within an industry that exhibit denser strategic linkages among themselves than other firms within the same industry. Based on this, strategic networks are determined according to evidence of strategic alliances between firms comprising the industry. As a result, a single strategic network represents a group of firms closely linked according to collaborative ties. Arguably, the collective outcome of these strategic relationships engineered between firms suggest that the collaborative benefits attributed to interorganisational relationships require closer examination in respect to their propensity to influence rivalry in intraindustry environments. Derived in large from the social sciences, network theory allows for the micro and macro examination of the opportunities and constraints inherent in the structure of relationships in strategic networks, establishing a relational approach upon which the conduct and performance of firms can be more fully understood. Research to date has yet to empirically investigate the relationship between strategic networks and rivalry. The limited research that has been completed utilising a network rationale to investigate competitive patterns in contemporary industry environments has been characterised by a failure to directly measure rivalry. Further, this prior research has typically embedded investigation in industry settings dominated by technological or regulatory imperatives, such as the microprocessor and airline industries. These industries, due to the presence of such imperatives, are arguably more inclined to support the realisation of network rivalry, through subscription to prescribed technological standards (eg., microprocessor industry) or by being bound by regulatory constraints dictating operation within particular market segments (airline industry). In order to counter these weaknesses, the proposition guiding research - Are patterns of rivalry predicted by strategic network membership? – is embedded in the United States Light Vehicles Industry, an industry not dominated by technological or regulatory imperatives. Further, rivalry is directly measured and utilised in research, thus distinguishing this investigation from prior research efforts. The timeframe of investigation is 1993 – 1999, with all research data derived from secondary sources. Strategic networks were defined within the United States Light Vehicles Industry based on evidence of horizontal strategic relationships between firms comprising the industry. The measure of rivalry used to directly ascertain the competitive patterns of industry participants was derived from the traditional Herfindahl Index, modified to account for patterns of rivalry observed at the market segment level. Statistical analyses of the strategic network and rivalry constructs found little evidence to support the contention of network rivalry; indeed, greater levels of rivalry were observed between firms comprising the same strategic network than between firms participating in opposing network structures. Based on these results, patterns of rivalry evidenced in the United States Light Vehicle Industry over the period 1993 – 1999 were not found to be predicted by strategic network membership. The findings generated by this research are in contrast to current theorising in the strategic network – rivalry realm. In this respect, these findings are surprising. The relevance of industry type, in conjunction with prevailing network methodology, provides the basis upon which these findings are contemplated. Overall, this study raises some important questions in relation to the relevancy of the network rivalry rationale, establishing a fruitful avenue for further research.

Making connections : creative industries networks in outer suburban locations

The role of networks and their contribution to sustaining and developing creative industries is well documented (Wittel 2001; Kong 2005; Pratt 2007). This article argues that although networks operate across geographical boundaries, particularly through the use of communication technologies, the majority of studies have focussed on the ways in which networks operate in a) specific inner-urban metropolitan regions or b) specific industries. Such studies are informed by the geographical mindset of creative city proponents such as Florida (2002) and Landry (2000) in which inner-urban precincts are seen as the prime location for creative industries activity, business development and opportunity. But what of those creative industries situated beyond the inner city? Evidence in Australia suggests there is increasing creative industries activity beyond the inner city, in outer-suburban and ex-urban areas (Gibson & Brennan-Horley 2006). This article identifies characteristics of creative industries networks in outer-suburban locations in Melbourne and Brisbane. It argues that supporting and sustaining creative industries networks in these locations may require different strategies than those applied to inner-city networks. The article thus contributes to the growing understanding of the cultural economic geography of creative industries.

Design and evaluation of an image analysis platform for low-power, low-bandwidth camera networks

We describe the design and evaluation of a platform for networks of cameras in low-bandwidth, low-power sensor networks. In our work to date we have investigated two different DSP hardware/software platforms for undertaking the tasks of compression and object detection and tracking. We compare the relative merits of each of the hardware and software platforms in terms of both performance and energy consumption. Finally we discuss what we believe are the ongoing research questions for image processing in WSNs.

Closed-form design equations for decoupling networks of small arrays

Small element spacing in compact arrays results in strong mutual coupling between the array elements. A decoupling network consisting of reactive cross-coupling elements can alleviate problems associated with the coupling. Closed-form design equations for the decoupling networks of symmetrical arrays with two or three elements are presented.