ORCID Profile
0000-0002-1807-7220
Current Organisation
University of Sydney
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Communications Technologies | Broadband Network Technology | Computer Communications Networks | Communications Technologies Not Elsewhere Classified | Radio Communications And Broadcasting Not Elsewhere Classified | Satellite Communications | Antenna Technology | Optical And Photonic Systems | Signal Processing | Interorganisational Information Systems | Information Systems Management | Interdisciplinary Engineering Not Elsewhere Classified | Research, Science And Technology Policy | Interdisciplinary Engineering | Data Security | Speech Recognition | Database Management
Telecommunications | Network transmission equipment | Information processing services | Technological and organisational innovation | Network switching equipment | Air transport | Other | Communication services not elsewhere classified | Computer software and services not elsewhere classified | Health and support services not elsewhere classified |
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Society for Industrial & Applied Mathematics (SIAM)
Date: 2018
DOI: 10.1137/17M1157635
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-07-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-07-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-06-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2021
Publisher: MDPI AG
Date: 29-05-2022
DOI: 10.3390/S22114123
Abstract: Cyber-attacks are getting increasingly complex, and as a result, the functional concerns of intrusion-detection systems (IDSs) are becoming increasingly difficult to resolve. The credibility of security services, such as privacy preservation, authenticity, and accessibility, may be jeopardized if breaches are not detected. Different organizations currently utilize a variety of tactics, strategies, and technology to protect the systems’ credibility in order to combat these dangers. Safeguarding approaches include establishing rules and procedures, developing user awareness, deploying firewall and verification systems, regulating system access, and forming computer-issue management groups. The effectiveness of intrusion-detection systems is not sufficiently recognized. IDS is used in businesses to examine possibly harmful tendencies occurring in technological environments. Determining an effective IDS is a complex task for organizations that require consideration of many key criteria and their sub-aspects. To deal with these multiple and interrelated criteria and their sub-aspects, a multi-criteria decision-making (MCMD) approach was applied. These criteria and their sub-aspects can also include some ambiguity and uncertainty, and thus they were treated using q-rung orthopair fuzzy sets (q-ROFS) and q-rung orthopair fuzzy numbers (q-ROFNs). Additionally, the problem of combining expert and specialist opinions was dealt with using the q-rung orthopair fuzzy weighted geometric (q-ROFWG). Initially, the entropy method was applied to assess the priorities of the key criteria and their sub-aspects. Then, the combined compromised solution (CoCoSo) method was applied to evaluate six IDSs according to their effectiveness and reliability. Afterward, comparative and sensitivity analyses were performed to confirm the stability, reliability, and performance of the proposed approach. The findings indicate that most of the IDSs appear to be systems with high potential. According to the results, Suricata is the best IDS that relies on multi-threading performance.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-06-2022
DOI: 10.36227/TECHRXIV.20063285.V1
Abstract: We focus on the secure performance metrics at the legitimate users, i.e. secure outage probability (SOP) and secrecy capacity, to quantify the secrecy performance of NOMA-RIS-aided IoT systems. We assume the RIS is placed between the access point and the legitimate devices, and is expected to enhance the link security through the smart phase shift mechanism of metasurface elements in RIS. We first present analytical results for the SOP and secrecy capacity. Next, an iterative search algorithm is adopted to exhibit optimal SOP for further insights and analysis. In order to help the base station allocate power coefficients to NOMA users properly, an efficient deep-neural network (DNN)-based secure metric prediction scheme is adopted to achieve the secure performance. Our derivations and simulations indicate that the number of meta-surface elements of the RIS and the average signal-to-noise ratio at the base station contribute the most to the system performance enhancement.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-06-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-06-2022
DOI: 10.36227/TECHRXIV.20063285
Abstract: We focus on the secure performance metrics at the legitimate users, i.e. secure outage probability (SOP) and secrecy capacity, to quantify the secrecy performance of NOMA-RIS-aided IoT systems. We assume the RIS is placed between the access point and the legitimate devices, and is expected to enhance the link security through the smart phase shift mechanism of metasurface elements in RIS. We first present analytical results for the SOP and secrecy capacity. Next, an iterative search algorithm is adopted to exhibit optimal SOP for further insights and analysis. In order to help the base station allocate power coefficients to NOMA users properly, an efficient deep-neural network (DNN)-based secure metric prediction scheme is adopted to achieve the secure performance. Our derivations and simulations indicate that the number of meta-surface elements of the RIS and the average signal-to-noise ratio at the base station contribute the most to the system performance enhancement.
Publisher: Springer Science and Business Media LLC
Date: 26-01-2023
Publisher: Springer Science and Business Media LLC
Date: 06-09-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-11-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-06-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-04-2022
Publisher: Elsevier BV
Date: 12-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-05-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-04-2023
DOI: 10.36227/TECHRXIV.22348456
Abstract: A paper with 8 pages and 5 figures
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer Science and Business Media LLC
Date: 05-12-2022
DOI: 10.1038/S41467-022-33407-5
Abstract: Although machine learning (ML) has shown promise across disciplines, out-of-s le generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature ( n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large erse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Start Date: 04-2004
End Date: 12-2007
Amount: $300,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 05-2009
End Date: 12-2012
Amount: $270,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 07-2007
End Date: 12-2010
Amount: $303,810.00
Funder: Australian Research Council
View Funded ActivityStart Date: 12-2004
End Date: 10-2010
Amount: $216,326.00
Funder: Australian Research Council
View Funded ActivityStart Date: 01-2010
End Date: 12-2014
Amount: $285,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 12-2004
End Date: 12-2010
Amount: $1,950,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2007
End Date: 12-2007
Amount: $200,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2003
End Date: 12-2003
Amount: $20,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 12-2004
End Date: 01-2011
Amount: $1,500,000.00
Funder: Australian Research Council
View Funded Activity