A rights management approach to securing data distribution in coalitions

As network capacity has increased over the past decade, individuals and organisations have found it increasingly appealing to make use of remote services in the form of service-oriented architectures and cloud computing services. Data processed by remote services, however, is no longer under the direct control of the individual or organisation that provided the data, leaving data owners at risk of data theft or misuse. This paper describes a model by which data owners can control the distribution and use of their data throughout a dynamic coalition of service providers using digital rights management technology. Our model allows a data owner to establish the trustworthiness of every member of a coalition employed to process data, and to communicate a machine-enforceable usage policy to every such member.

Legislative and security requirements of audit material for evidentiary purpose

This research used the Queensland Police Service, Australia, as a major case study. Information on principles, techniques and processes used, and the reason for the recording, storing and release of audit information for evidentiary purposes is reported. It is shown that Law Enforcement Agencies have a two-fold interest in, and legal obligation pertaining to, audit trails. The first interest relates to the situation where audit trails are actually used by criminals in the commission of crime and the second to where audit trails are generated by the information systems used by the police themselves in support of the recording and investigation of crime. Eleven court cases involving Queensland Police Service audit trails used in evidence in Queensland courts were selected for further analysis. It is shown that, of the cases studied, none of the evidence presented was rejected or seriously challenged from a technical perspective. These results were further analysed and related to normal requirements for trusted maintenance of audit trail information in sensitive environments with discussion on the ability and/or willingness of courts to fully challenge, assess or value audit evidence presented. Managerial and technical frameworks for firstly what is considered as an environment where a computer system may be considered to be operating “properly” and, secondly, what aspects of education, training, qualifications, expertise and the like may be considered as appropriate for persons responsible within that environment, are both proposed. Analysis was undertaken to determine if audit and control of information in a high security environment, such as law enforcement, could be judged as having improved, or not, in the transition from manual to electronic processes. Information collection, control of processing and audit in manual processes used by the Queensland Police Service, Australia, in the period 1940 to 1980 was assessed against current electronic systems essentially introduced to policing in the decades of the 1980s and 1990s. Results show that electronic systems do provide for faster communications with centrally controlled and updated information readily available for use by large numbers of users who are connected across significant geographical locations. However, it is clearly evident that the price paid for this is a lack of ability and/or reluctance to provide improved audit and control processes. To compare the information systems audit and control arrangements of the Queensland Police Service with other government departments or agencies, an Australia wide survey was conducted. Results of the survey were contrasted with the particular results of a survey, conducted by the Australian Commonwealth Privacy Commission four years previous, to this survey which showed that security in relation to the recording of activity against access to information held on Australian government computer systems has been poor and a cause for concern. However, within this four year period there is evidence to suggest that government organisations are increasingly more inclined to generate audit trails. An attack on the overall security of audit trails in computer operating systems was initiated to further investigate findings reported in relation to the government systems survey. The survey showed that information systems audit trails in Microsoft Corporation's “Windows” operating system environments are relied on quite heavily. An audit of the security for audit trails generated, stored and managed in the Microsoft “Windows 2000” operating system environment was undertaken and compared and contrasted with similar such audit trail schemes in the “UNIX” and “Linux” operating systems. Strength of passwords and exploitation of any security problems in access control were targeted using software tools that are freely available in the public domain. Results showed that such security for the “Windows 2000” system is seriously flawed and the integrity of audit trails stored within these environments cannot be relied upon. An attempt to produce a framework and set of guidelines for use by expert witnesses in the information technology (IT) profession is proposed. This is achieved by examining the current rules and guidelines related to the provision of expert evidence in a court environment, by analysing the rationale for the separation of distinct disciplines and corresponding bodies of knowledge used by the Medical Profession and Forensic Science and then by analysing the bodies of knowledge within the discipline of IT itself. It is demonstrated that the accepted processes and procedures relevant to expert witnessing in a court environment are transferable to the IT sector. However, unlike some discipline areas, this analysis has clearly identified two distinct aspects of the matter which appear particularly relevant to IT. These two areas are; expertise gained through the application of IT to information needs in a particular public or private enterprise; and expertise gained through accepted and verifiable education, training and experience in fundamental IT products and system.

The impact of users’ cognitive style on their navigational behaviors in web searching

User-Web interactions have emerged as an important area of research in the field of information science. In this study, we investigate the effects of users’ cognitive styles on their Web navigational styles and information processing strategies. We report results from the analyses of 594 minutes recorded Web search sessions of 18 participants engaged in 54 scenario-based search tasks. We use questionnaires, cognitive style test, Web session logs and think-aloud as the data collection instruments. We classify users’ cognitive styles as verbalisers and imagers based on Riding’s (1991) Cognitive Style Analysis test. Two classifications of navigational styles and three categories of information processing strategies are identified. Our study findings show that there exist relationships between users’ cognitive style, and their navigational styles and information processing strategies. Verbal users seem to display sporadic navigational styles, and adopt a scanning strategy to understand the content of the search result page, while imagery users follow a structured navigational style and reading approach. We develop a matrix and a model that depicts the relationships between users’ cognitive styles, and their navigational style and information processing strategies. We discuss how the findings from this study could help search engine designers to provide an adaptive navigation support to users.

Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Using data mining on road asset management data in analysing road crashes

Road safety is a major concern worldwide. Road safety will improve as road conditions and their effects on crashes are continually investigated. This paper proposes to use the capability of data mining to include the greater set of road variables for all available crashes with skid resistance values across the Queensland state main road network in order to understand the relationships among crash, traffic and road variables. This paper presents a data mining based methodology for the road asset management data to find out the various road properties that contribute unduly to crashes. The models demonstrate high levels of accuracy in predicting crashes in roads when various road properties are included. This paper presents the findings of these models to show the relationships among skid resistance, crashes, crash characteristics and other road characteristics such as seal type, seal age, road type, texture depth, lane count, pavement width, rutting, speed limit, traffic rates intersections, traffic signage and road design and so on.

Road crash proneness prediction using data mining

Developing safe and sustainable road systems is a common goal in all countries. Applications to assist with road asset management and crash minimization are sought universally. This paper presents a data mining methodology using decision trees for modeling the crash proneness of road segments using available road and crash attributes. The models quantify the concept of crash proneness and demonstrate that road segments with only a few crashes have more in common with non-crash roads than roads with higher crash counts. This paper also examines ways of dealing with highly unbalanced data sets encountered in the study.

Identifying differences in wet and dry road crashes using data mining

It is commonly accepted that wet roads have higher risk of crash than dry roads; however, providing evidence to support this assumption presents some difficulty. This paper presents a data mining case study in which predictive data mining is applied to model the skid resistance and crash relationship to search for discernable differences in the probability of wet and dry road segments having crashes based on skid resistance. The models identify an increased probability of wet road segments having crashes for mid-range skid resistance values.

Using data mining to predict road crash count with a focus on skid resistance values

Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.