ORCID Profile
0000-0002-4691-8330
Current Organisation
Deakin University
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Elsevier BV
Date: 07-2020
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Springer Singapore
Date: 2018
Publisher: ACM
Date: 16-10-2023
Publisher: IEEE
Date: 11-2007
Publisher: Inderscience Publishers
Date: 2018
Publisher: Springer International Publishing
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 18-05-2018
Publisher: Springer Science and Business Media LLC
Date: 06-2014
Publisher: ACM
Date: 30-10-2017
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: IEEE
Date: 12-2022
Publisher: Association for Computing Machinery (ACM)
Date: 06-12-2020
DOI: 10.1145/3417978
Abstract: Deep Learning (DL) is a disruptive technology that has changed the landscape of cyber security research. Deep learning models have many advantages over traditional Machine Learning (ML) models, particularly when there is a large amount of data available. Android malware detection or classification qualifies as a big data problem because of the fast booming number of Android malware, the obfuscation of Android malware, and the potential protection of huge values of data assets stored on the Android devices. It seems a natural choice to apply DL on Android malware detection. However, there exist challenges for researchers and practitioners, such as choice of DL architecture, feature extraction and processing, performance evaluation, and even gathering adequate data of high quality. In this survey, we aim to address the challenges by systematically reviewing the latest progress in DL-based Android malware detection and classification. We organize the literature according to the DL architecture, including FCN, CNN, RNN, DBN, AE, and hybrid models. The goal is to reveal the research frontier, with the focus on representing code semantics for Android malware detection. We also discuss the challenges in this emerging field and provide our view of future research opportunities and directions.
Publisher: MDPI AG
Date: 22-06-2023
Abstract: In recent years, edge-based intelligent UAV delivery systems have attracted significant interest from both the academic and industrial sectors. One key obstacle faced by these smart UAV delivery systems is data privacy, as they rely on vast amounts of data from users and UAVs for training machine learning models for person re-identification (ReID) purposes. To tackle this issue, federated learning (FL) has been extensively adopted as a promising solution since it only involves sharing and updating model parameters with a central server, without transferring raw data. However, traditional FL still suffers from the problem of having a single point of failure. In this study, we present a performance optimization method for federated person re-identification using benchmark analysis in blockchain-powered edge-based smart UAV delivery systems. Our method integrates a decentralized FL mechanism enabled by blockchain, which eliminates the necessity for a central server and stores private data on a decentralized permissioned blockchain, thus preventing a single point of failure. We employ the person ReID application in intelligent UAV delivery systems as a representative ex le to drive our research and examine privacy concerns. Additionally, we introduce the Federated Re-identification Consensus (FRC) protocol to address the scalability issue of the blockchain in supporting UAV delivery systems. The efficiency of our proposed method is illustrated through experiments on energy efficiency, confirmation time, and throughput. We also explore the effects of the incentive mechanism and analyze the system’s resilience under various security attacks. This study offers valuable insights and potential solutions for addressing data privacy and security challenges in the fast-growing domain of smart UAV delivery systems.
Publisher: IOP Publishing
Date: 10-2018
Publisher: Springer Science and Business Media LLC
Date: 19-06-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Publisher: IEEE
Date: 08-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Wiley
Date: 07-07-2017
DOI: 10.1002/CPE.4181
Publisher: Wiley
Date: 25-03-2019
DOI: 10.1002/CPE.5270
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Informa UK Limited
Date: 05-12-2017
Publisher: IEEE
Date: 2006
DOI: 10.1109/ISCC.2006.93
Publisher: Springer International Publishing
Date: 2019
Publisher: Elsevier BV
Date: 11-2021
Publisher: IEEE
Date: 10-2018
Publisher: ACM
Date: 10-07-2023
Publisher: IEEE
Date: 06-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer International Publishing
Date: 2018
Publisher: Elsevier BV
Date: 10-2017
Publisher: Springer Science and Business Media LLC
Date: 31-03-2020
Publisher: Wiley
Date: 06-04-2020
DOI: 10.1002/CPE.5726
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2023
Publisher: Springer Science and Business Media LLC
Date: 07-05-2018
Publisher: American Physical Society (APS)
Date: 02-11-2022
Publisher: ACM
Date: 10-07-2023
Publisher: Elsevier BV
Date: 12-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 12-2019
Publisher: IEEE
Date: 11-2018
Publisher: IEEE
Date: 08-2012
Publisher: Springer Science and Business Media LLC
Date: 19-04-2018
Publisher: IEEE
Date: 07-2019
Publisher: Springer Singapore
Date: 2016
Publisher: Springer Science and Business Media LLC
Date: 26-02-2021
Publisher: Springer Science and Business Media LLC
Date: 13-04-2017
DOI: 10.1038/SREP46302
Abstract: Quantum cryptography is commonly used to generate fresh secure keys with quantum signal transmission for instant use between two parties. However, research shows that the relatively low key generation rate hinders its practical use where a symmetric cryptography component consumes the shared key. That is, the security of the symmetric cryptography demands frequent rate of key updates, which leads to a higher consumption of the internal one-time-pad communication bandwidth, since it requires the length of the key to be as long as that of the secret. In order to alleviate these issues, we develop a matrix algorithm for fast and simple high-capacity quantum cryptography. Our scheme can achieve secure private communication with fresh keys generated from Fibonacci- and Lucas- valued orbital angular momentum (OAM) states for the seed to construct recursive Fibonacci and Lucas matrices. Moreover, the proposed matrix algorithm for quantum cryptography can ultimately be simplified to matrix multiplication, which is implemented and optimized in modern computers. Most importantly, considerably information capacity can be improved effectively and efficiently by the recursive property of Fibonacci and Lucas matrices, thereby avoiding the restriction of physical conditions, such as the communication bandwidth.
Publisher: Elsevier BV
Date: 09-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Publisher: Elsevier BV
Date: 03-2018
Publisher: IEEE
Date: 12-2018
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: IEEE
Date: 03-2013
DOI: 10.1109/IMF.2013.11
Publisher: IEEE
Date: 07-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Wiley
Date: 04-08-2022
DOI: 10.1002/CPE.5816
Abstract: Realistic modeling of mechanical behavior of soft tissue has been recognized as an essential part for medical Internet of thing for minimal invasive surgery (MIS) training simulator. Therefore, the blockchain‐based constitutive model is crucial for mechanical response of soft tissue modeling. In this article, based on the Ogden second order model, a novel hyperplastic model was presented to describe the stress‐stretch relationship in the MIS training system. To validate this theoretical model, two experimental techniques (uniaxial compression and uniaxial tensile) were conducted to obtain data related to stress‐strain in the blockchain system, which plays an important role in investigating the mechanical behavior of soft tissue. Our results show that the new model has a satisfied coincidence of the experimental data than other existing models. Furthermore, the viscoelastic properties of soft tissue were investigated and a viscoelastic model based on three‐parameter was utilized to interpret the viscoelastic behavior of the soft tissue. The contributions of this article include several biomechanical tests that were performed to investigate the soft tissue hyperelastic and viscoelastic properties in the MIS system, and theoretical guidance for simulating soft tissue mechanical behavior in the blockchain‐based simulation system.
Publisher: IEEE
Date: 07-2017
Publisher: ACM
Date: 31-01-2017
Publisher: IEEE
Date: 08-2008
Publisher: Elsevier BV
Date: 11-2017
Publisher: Springer Berlin Heidelberg
Date: 2014
Publisher: ACM
Date: 10-07-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2008
DOI: 10.1109/MSP.2008.74
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2021
Publisher: Informa UK Limited
Date: 13-11-2017
Publisher: Springer International Publishing
Date: 2020
Publisher: IEEE
Date: 04-2007
DOI: 10.1109/SADFE.2007.2
Publisher: IEEE
Date: 12-2016
DOI: 10.1109/CIT.2016.22
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Springer International Publishing
Date: 2020
Publisher: IEEE
Date: 10-2014
Publisher: IGI Global
Date: 10-2012
Abstract: The need for an automated approach to forensic digital investigation has been recognized for some years, and several authors have developed frameworks in this direction. The aim of this paper is to assist the forensic investigator with the generation and testing of hypotheses in the analysis phase. In doing so, the authors present a new architecture which facilitates the move to automation of the investigative process this new architecture draws together several important components of the literature on question and answer methodologies including the concept of ‘pivot’ word and sentence ranking. Their architecture is supported by a detailed case study demonstrating its practicality.
Publisher: ACM
Date: 31-01-2017
Publisher: Elsevier BV
Date: 11-2023
Publisher: IOP Publishing
Date: 26-03-2019
Publisher: IOP Publishing
Date: 04-09-2018
Publisher: IGI Global
Date: 2013
DOI: 10.4018/978-1-4666-4006-1.CH013
Abstract: The need for an automated approach to forensic digital investigation has been recognized for some years, and several authors have developed frameworks in this direction. The aim of this paper is to assist the forensic investigator with the generation and testing of hypotheses in the analysis phase. In doing so, the authors present a new architecture which facilitates the move to automation of the investigative process this new architecture draws together several important components of the literature on question and answer methodologies including the concept of ‘pivot’ word and sentence ranking. Their architecture is supported by a detailed case study demonstrating its practicality.
Publisher: Springer International Publishing
Date: 2022
Publisher: Springer Singapore
Date: 2019
Publisher: Springer International Publishing
Date: 2022
Publisher: IEEE
Date: 11-2015
Publisher: Springer Science and Business Media LLC
Date: 12-08-2016
DOI: 10.1038/SREP31350
Abstract: With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m -bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m -bonacci sequences to detect eavesdropping. Meanwhile, we encode m -bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.
Publisher: IEEE
Date: 11-2019
Publisher: Springer International Publishing
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-0006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2021
Publisher: Informa UK Limited
Date: 10-12-2017
Publisher: Informa UK Limited
Date: 23-05-2021
Publisher: IEEE
Date: 03-2017
No related grants have been discovered for Lei Pan.