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Field of Research : Information Systems Management
Australian State/Territory : NSW
Research Topic : Machine Tools
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  • Researchers (12)
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  • Funded Activity

    Discovery Projects - Grant ID: DP0452348

    Funder
    Australian Research Council
    Funding Amount
    $120,000.00
    Summary
    Enhancing computer user productivity of integrated enterprise wide systems: an intervention study. This project addresses a critical issue in IT investment and productivity. Current theoretical models of user training and acceptance have not contributed to the effectiveness of implementing new integrated enterprise wide systems. This study will identify key indiviudal differences that predict user motivation to learn and utilize such systems under mandatory conditions. A longitudinal study in .... Enhancing computer user productivity of integrated enterprise wide systems: an intervention study. This project addresses a critical issue in IT investment and productivity. Current theoretical models of user training and acceptance have not contributed to the effectiveness of implementing new integrated enterprise wide systems. This study will identify key indiviudal differences that predict user motivation to learn and utilize such systems under mandatory conditions. A longitudinal study in two field settings will test the impact of selected interventions on task performance following training. The outcomes will inform Australian industry on models of effective implementation and provide guidance to increase the productivity of personnel using software systems.
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    Funded Activity

    Discovery Projects - Grant ID: DP1094799

    Funder
    Australian Research Council
    Funding Amount
    $180,000.00
    Summary
    Trust-Oriented Social Relation Analysis and Social Relation Aware Rating Analysis in Trust Management. Trust management is an emerging field offering critical challenges on evaluating the quality and trustworthiness of objects, services and raters. Thus it requires the development of novel techniques and solutions to address these challenges both conceptually and practically. This project will develop innovative techniques to infer trust in complex social networks, detect bias in trust ratings a .... Trust-Oriented Social Relation Analysis and Social Relation Aware Rating Analysis in Trust Management. Trust management is an emerging field offering critical challenges on evaluating the quality and trustworthiness of objects, services and raters. Thus it requires the development of novel techniques and solutions to address these challenges both conceptually and practically. This project will develop innovative techniques to infer trust in complex social networks, detect bias in trust ratings and its dependencies with social relations. They can greatly contribute to breakthrough techniques enabling trust-oriented social network analysis and more objective trust management systems that can be transferred to the Australian IT industry to promote the trustworthiness of Web services and reduce monetary loss.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP170100924

    Funder
    Australian Research Council
    Funding Amount
    $450,000.00
    Summary
    Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysi .... Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysis a monumental task. This project will provide advanced tools to detect fake website reviews and a cybersecurity system prototype ready to be used by industry, making Australia a leader in this field and resulting in a safer internet environment for all.
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    Funded Activity

    Discovery Projects - Grant ID: DP0558522

    Funder
    Australian Research Council
    Funding Amount
    $178,000.00
    Summary
    Security for Peer-to-Peer Systems. The importance of adequate security for Internet and online services has been underscored by recent events. The protection of information infrastructures in this ever-increasing digital world has become essential for businesses, governments and individuals. Secure interactions over the Internet have become a strategic necessity and it is critically important for Australia to possess the technology to anticipate and respond to security threats to its industry an .... Security for Peer-to-Peer Systems. The importance of adequate security for Internet and online services has been underscored by recent events. The protection of information infrastructures in this ever-increasing digital world has become essential for businesses, governments and individuals. Secure interactions over the Internet have become a strategic necessity and it is critically important for Australia to possess the technology to anticipate and respond to security threats to its industry and society. The outcomes of this research project will result in secure and trustworthy computing technologies that will enable secure e-commerce applications and on-line services and trusted interactions between users over the Internet.
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    Funded Activity

    Discovery Projects - Grant ID: DP0772493

    Funder
    Australian Research Council
    Funding Amount
    $217,000.00
    Summary
    Techniques for the Design of Trust Enhanced Secure Distributed Applications. Security and trusted systems for on-line services and information infrastructures are now of paramount importance. Secure trustworthy computing applications have become a strategic necessity for businesses, governments and individuals in the ever-increasing digital world. It is critically important for Australia to develop technologies to anticipate and respond to security threats to its industry and society. The outcom .... Techniques for the Design of Trust Enhanced Secure Distributed Applications. Security and trusted systems for on-line services and information infrastructures are now of paramount importance. Secure trustworthy computing applications have become a strategic necessity for businesses, governments and individuals in the ever-increasing digital world. It is critically important for Australia to develop technologies to anticipate and respond to security threats to its industry and society. The outcomes of this research will result in secure and trustworthy computing technologies that will enable the design of trust enhanced secure applications and trusted platforms, which will help to achieve secure e-commerce applications and on-line services, and trusted interactions between users over the Internet.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210101347

    Funder
    Australian Research Council
    Funding Amount
    $368,810.00
    Summary
    Targeted Graph Embedding for Anomaly Detection in Large-scale Networks. This project aims to tackle the challenging problem of anomaly detection in large-scale networks by leveraging graph embedding techniques. It expects to deliver a series of innovative graph embedding algorithms targeting optimised anomaly detection. By addressing under-developed research challenges, such as the versatile types of anomalies and lack of anomaly labels, the established theories and devised methodologies will ad .... Targeted Graph Embedding for Anomaly Detection in Large-scale Networks. This project aims to tackle the challenging problem of anomaly detection in large-scale networks by leveraging graph embedding techniques. It expects to deliver a series of innovative graph embedding algorithms targeting optimised anomaly detection. By addressing under-developed research challenges, such as the versatile types of anomalies and lack of anomaly labels, the established theories and devised methodologies will advance frontier technologies in both graph anomaly detection and graph representation learning. By uncovering anomalies with high efficiency and accuracy, this project will contribute to multiple real applications from fake review detection to financial fraud identification, bringing both social and economic benefits.
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    Showing 1-6 of 6 Funded Activites

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