Madhav Mukherjee
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Madhav Mukherjee has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- John Le
Institute of Cybersecurity and Cryptology, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
4 shared publications - Yang-Wai Chow
University of Wollongong
3 shared publications - Dung Hoang Duong
University of Wollongong
1 shared publication - Minh Vu Nguyen
School of Computing and Information Technology, University of Wollongong, Australia
1 shared publication - Willy Susilo
Institute of Cybersecurity and Cryptology, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
1 shared publication - Yannan Li
University of Wollongong
1 shared publication
Latest Publications
- 3 June 2026
- Published by Springer Nature
- p. 70-84
A Governable GenAI Tutoring Framework for Cybersecurity Education
- 3 June 2026
- Published by Springer Nature
- p. 70-84
A Governable GenAI Tutoring Framework for Cybersecurity Education
- Open Access
- 31 March 2025
- Published by MDPI AG in Future Internet
- Vol. 17 (4) , 154
Generative AI-Enhanced Intelligent Tutoring System for Graduate Cybersecurity Programs
Due to the widespread applicability of generative artificial intelligence, we have seen it adopted across many areas of education, providing universities with new opportunities, particularly in cybersecurity education. With the industry facing a skills shortage, this paper explores the use of generative artificial intelligence in higher cybersecurity education as an intelligent tutoring system to enhance factors leading to positive student outcomes. Despite its success in content generation and assessment within cybersecurity, the field’s multidisciplinary nature presents additional challenges to scalability and generalisability. We propose a solution using agents to orchestrate specialised large language models and to demonstrate its applicability in graduate level cybersecurity topics offered at a leading Australian university. We aim to show a generalisable and scalable solution to diversified educational paradigms, highlighting its relevant features, and a method to evaluate the quality of content as well as the general effectiveness of the intelligent tutoring system on subjective factors aligned with positive student outcomes. We further explore areas for future research in model efficiency, privacy, security, and scalability.
- 31 March 2025
- Published by MDPI AG in Future Internet
- Vol. 17 (4) , 154
Open AccessGenerative AI-Enhanced Intelligent Tutoring System for Graduate Cybersecurity Programs
Due to the widespread applicability of generative artificial intelligence, we have seen it adopted across many areas of education, providing universities with new opportunities, particularly in cybersecurity education. With the industry facing a skills shortage, this paper explores the use of generative artificial intelligence in higher cybersecurity education as an intelligent tutoring system to enhance factors leading to positive student outcomes. Despite its success in content generation and assessment within cybersecurity, the field’s multidisciplinary nature presents additional challenges to scalability and generalisability. We propose a solution using agents to orchestrate specialised large language models and to demonstrate its applicability in graduate level cybersecurity topics offered at a leading Australian university. We aim to show a generalisable and scalable solution to diversified educational paradigms, highlighting its relevant features, and a method to evaluate the quality of content as well as the general effectiveness of the intelligent tutoring system on subjective factors aligned with positive student outcomes. We further explore areas for future research in model efficiency, privacy, security, and scalability.
- Top Cited PapersOpen Access
- 18 February 2024
- Published by MDPI AG in Information
- Vol. 15 (2) , 117
Strategic Approaches to Cybersecurity Learning: A Study of Educational Models and Outcomes
As the demand for cybersecurity experts in the industry grows, we face a widening shortage of skilled professionals. This pressing concern has spurred extensive research within academia and national bodies, who are striving to bridge this skills gap through refined educational frameworks, including the integration of innovative information applications like remote laboratories and virtual classrooms. Despite these initiatives, current higher education models for cybersecurity, while effective in some areas, fail to provide a holistic solution to the root causes of the skills gap. Our study conducts a thorough examination of established cybersecurity educational frameworks, with the goal of identifying crucial learning outcomes that can mitigate the factors contributing to this skills gap. Furthermore, by analyzing six different educational models, for each one that can uniquely leverage technology like virtual classrooms and online platforms and is suited to various learning contexts, we categorize these contexts into four distinct categories. This categorization introduces a holistic dimension of context awareness enriched by digital learning tools into the process, enhancing the alignment with desired learning outcomes, a consideration sparsely addressed in the existing literature. This thorough analysis further strengthens the framework for guiding education providers in selecting models that most effectively align with their targeted learning outcomes and implies practical uses for technologically enhanced environments. This review presents a roadmap for educators and institutions, offering insights into relevant teaching models, including the opportunities for the utilization of remote laboratories and virtual classrooms, and their contextual applications, thereby aiding curriculum designers in making strategic decisions.
- 18 February 2024
- Published by MDPI AG in Information
- Vol. 15 (2) , 117
Top Cited PapersOpen AccessStrategic Approaches to Cybersecurity Learning: A Study of Educational Models and Outcomes
As the demand for cybersecurity experts in the industry grows, we face a widening shortage of skilled professionals. This pressing concern has spurred extensive research within academia and national bodies, who are striving to bridge this skills gap through refined educational frameworks, including the integration of innovative information applications like remote laboratories and virtual classrooms. Despite these initiatives, current higher education models for cybersecurity, while effective in some areas, fail to provide a holistic solution to the root causes of the skills gap. Our study conducts a thorough examination of established cybersecurity educational frameworks, with the goal of identifying crucial learning outcomes that can mitigate the factors contributing to this skills gap. Furthermore, by analyzing six different educational models, for each one that can uniquely leverage technology like virtual classrooms and online platforms and is suited to various learning contexts, we categorize these contexts into four distinct categories. This categorization introduces a holistic dimension of context awareness enriched by digital learning tools into the process, enhancing the alignment with desired learning outcomes, a consideration sparsely addressed in the existing literature. This thorough analysis further strengthens the framework for guiding education providers in selecting models that most effectively align with their targeted learning outcomes and implies practical uses for technologically enhanced environments. This review presents a roadmap for educators and institutions, offering insights into relevant teaching models, including the opportunities for the utilization of remote laboratories and virtual classrooms, and their contextual applications, thereby aiding curriculum designers in making strategic decisions.
- Open Access
- 7 December 2023
- Published by Association for Computing Machinery (ACM)
- p. 296-303
Blockchain Oracles: Implications for Smart Contracts in Legal Reasoning and Addressing the Oracle Problem
This paper presents a comprehensive investigation into the role, functionalities, and complexities of blockchain oracles, focusing particularly on the implications for smart contracts in legal reasoning contexts. Oracles serve as a vital bridge to smart contracts’ inability to interact with external or “off-chain” data, enabling them to be used in a variety of real-world situations. Oracle’s integration, however, introduces a number of complexities, including security vulnerabilities, collectively referred to as the Oracle Problem. In addition to a review of existing literature, we also provide a mathematical analysis quantifying the computational complexity associated with automating legal reasoning and a novel design framework aimed at establishing oracles that are secure, efficient, and legally compliant. The paper aims to serve as a foundational text for researchers, legal practitioners, and blockchain developers, advancing the academic discourse surrounding blockchain oracles and their role in smart contracts.
- 7 December 2023
- Published by Association for Computing Machinery (ACM)
- p. 296-303
Open AccessBlockchain Oracles: Implications for Smart Contracts in Legal Reasoning and Addressing the Oracle Problem
This paper presents a comprehensive investigation into the role, functionalities, and complexities of blockchain oracles, focusing particularly on the implications for smart contracts in legal reasoning contexts. Oracles serve as a vital bridge to smart contracts’ inability to interact with external or “off-chain” data, enabling them to be used in a variety of real-world situations. Oracle’s integration, however, introduces a number of complexities, including security vulnerabilities, collectively referred to as the Oracle Problem. In addition to a review of existing literature, we also provide a mathematical analysis quantifying the computational complexity associated with automating legal reasoning and a novel design framework aimed at establishing oracles that are secure, efficient, and legally compliant. The paper aims to serve as a foundational text for researchers, legal practitioners, and blockchain developers, advancing the academic discourse surrounding blockchain oracles and their role in smart contracts.