ORCID Profile
0000-0002-5665-0980
Current Organisation
University of South Australia
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Publisher: IEEE
Date: 06-0066
Publisher: MDPI AG
Date: 28-11-2019
Abstract: Aerial human action recognition is an emerging topic in drone applications. Commercial drone platforms capable of detecting basic human actions such as hand gestures have been developed. However, a limited number of aerial video datasets are available to support increased research into aerial human action analysis. Most of the datasets are confined to indoor scenes or object tracking and many outdoor datasets do not have sufficient human body details to apply state-of-the-art machine learning techniques. To fill this gap and enable research in wider application areas, we present an action recognition dataset recorded in an outdoor setting. A free flying drone was used to record 13 dynamic human actions. The dataset contains 240 high-definition video clips consisting of 66,919 frames. All of the videos were recorded from low-altitude and at low speed to capture the maximum human pose details with relatively high resolution. This dataset should be useful to many research areas, including action recognition, surveillance, situational awareness, and gait analysis. To test the dataset, we evaluated the dataset with a pose-based convolutional neural network (P-CNN) and high-level pose feature (HLPF) descriptors. The overall baseline action recognition accuracy calculated using P-CNN was 75.92%.
Publisher: Springer International Publishing
Date: 2019
Publisher: IEEE
Date: 08-2017
Publisher: ACM
Date: 06-11-2017
Publisher: IEEE
Date: 09-2009
Publisher: IEEE
Date: 11-2012
Publisher: Academic Conferences International Ltd
Date: 28-02-2023
Abstract: There has been a dramatic increase in the number of Internet of Things (IoT) devices and their applications. Furthermore, there is a growing impetus to integrate IoT networks on a global scale, using satellites to expand the range of IoT connectivity into geographically remote areas. Ensuring the security of satellite backhaul for IoT networks is thus of paramount importance. The steady advance of quantum computing in recent years threatens to nullify classical cryptographic approaches based on assumptions of computational hardness, motivating the need for post-quantum cryptography. Quantum computing algorithms have been developed that, once a quantum computer of sufficient scale is realised, will be able to break classical cryptosystems efficiently (at polynomial-time complexity). A promising method of securing information against this threat at the physical layer has emerged in the form of quantum key distribution (QKD). QKD exploits the fundamental physical properties of light to guarantee information-theoretic security. Research into the application and standardisation of QKD to secure satellite backhaul, however, is still in its infancy. This paper presents a brief overview of the theoretical basis for QKD, whilst also providing a survey of contemporary QKD protocols. It evaluates the ability of these protocols to secure satellite backhaul in the context of a typical satellite-IoT network architecture. Furthermore, it highlights the vulnerabilities, as well as the technical challenges associated with this endeavour. Finally, it proposes directions for future research and development into protocols and standardisation for the satellite-integrated IoT domain. Several challenges must be overcome before QKD can evolve into a global-scale solution for securing satellite-IoT. Secret key generation rate remains very low in practical demonstrations of trusted-relay QKD satellite architectures. Further research is needed to overcome or mitigate the fundamental rate-distance trade-off before satellite QKD can be considered practicable in an IoT application. Alternatives that do not rely on trusted nodes are contingent on nascent technologies such as quantum repeaters and quantum memory. Whilst in theory QKD provides perfect information-theoretic security, it remains vulnerable to attacks that exploit imperfections in real-world equipment. Further effort is needed to develop QKD protocols that can safeguard against the aforementioned challenges.
Publisher: Association for Computing Machinery (ACM)
Date: 02-2009
Abstract: A typical wireless sensor node has little protection against radio jamming. The situation becomes worse if energy-efficient jamming can be achieved by exploiting knowledge of the data link layer. Encrypting the packets may help to prevent the jammer from taking actions based on the content of the packets, but the temporal arrangement of the packets induced by the nature of the protocol might unravel patterns that the jammer can take advantage of, even when the packets are encrypted. By looking at the packet interarrival times in three representative MAC protocols, S-MAC, LMAC, and B-MAC, we derive several jamming attacks that allow the jammer to jam S-MAC, LMAC, and B-MAC energy efficiently. The jamming attacks are based on realistic assumptions. The algorithms are described in detail and simulated. The effectiveness and efficiency of the attacks are examined. In addition, we validate our simulation model by comparing its results with measurements obtained from actual implementation on our sensor node prototypes. We show that it takes little effort to implement such effective jammers, making them a realistic threat. Careful analysis of other protocols belonging to the respective categories of S-MAC, LMAC, and B-MAC reveals that those protocols are, to some extent, also susceptible to our attacks. The result of this investigation provides new insights into the security considerations of MAC protocols.
Publisher: IEEE
Date: 10-2013
Publisher: IEEE
Date: 11-10-2020
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: IEEE Comput. Soc
Date: 2003
Publisher: IEEE
Date: 05-2010
Publisher: IEEE
Date: 03-2016
Publisher: IEEE
Date: 10-2012
Publisher: IEEE
Date: 09-2019
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 2022
Publisher: Elsevier BV
Date: 07-2018
Publisher: IEEE
Date: 05-2020
Publisher: MDPI AG
Date: 22-08-2022
DOI: 10.3390/E24081169
Abstract: We consider the problem of optimal maneuvering, where an autonomous vehicle, an unmanned aerial vehicle (UAV) for ex le, must maneuver to maximize or minimize an objective function. We consider a vehicle navigating in a Global Navigation Satellite System (GNSS)-denied environment that self-localizes in two dimensions using angle-of-arrival (AOA) measurements from stationary beacons at known locations. The objective of the vehicle is to travel along the path that minimizes its position and heading estimation error. This article presents an informative path planning (IPP) algorithm that (i) uses the determinant of the self-localization estimation error covariance matrix of an unscented Kalman filter as the objective function (ii) applies an l-step look-ahead (LSLA) algorithm to determine the optimal heading for a constant-speed vehicle. The novel algorithm takes into account the kinematic constraints of the vehicle and the AOA means of measurement. We evaluate the performance of the algorithm in five scenarios involving stationary and mobile beacons and we find the estimation error approaches the lower bound for the estimator. The simulations show the vehicle maneuvers to locations that allow for minimum estimation uncertainty, even when beacon placement is not conducive to accurate estimation.
Publisher: Association for Computing Machinery (ACM)
Date: 02-2006
Abstract: Cryptographic algorithms play an important role in the security architecture of wireless sensor networks (WSNs). Choosing the most storage- and energy-efficient block cipher is essential, due to the facts that these networks are meant to operate without human intervention for a long period of time with little energy supply, and that available storage is scarce on these sensor nodes. However, to our knowledge, no systematic work has been done in this area so far. We construct an evaluation framework in which we first identify the candidates of block ciphers suitable for WSNs, based on existing literature and authoritative recommendations. For evaluating and assessing these candidates, we not only consider the security properties but also the storage- and energy-efficiency of the candidates. Finally, based on the evaluation results, we select the most suitable ciphers for WSNs, namely Skipjack, MISTY1, and Rijndael, depending on the combination of available memory and required security (energy efficiency being implicit). In terms of operation mode, we recommend Output Feedback Mode for pairwise links but Cipher Block Chaining for group communications.
Publisher: IEEE
Date: 06-2013
Publisher: ICST
Date: 2008
Publisher: ACM
Date: 08-05-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2017
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: IEEE
Date: 12-2014
Publisher: ACM
Date: 16-06-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 04-2006
DOI: 10.1007/BF03219910
Publisher: IEEE
Date: 2009
DOI: 10.1109/IAS.2009.215
Publisher: MECS Publisher
Date: 17-03-2011
Publisher: Elsevier BV
Date: 2014
Publisher: Springer US
Date: 2003
Publisher: Springer International Publishing
Date: 2019
Publisher: IEEE Comput. Soc
Date: 2003
Publisher: IEEE
Date: 12-2008
Publisher: IEEE
Date: 08-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2012
DOI: 10.1109/TMC.2011.88
Publisher: IEEE
Date: 30-11-2022
Publisher: IOP Publishing
Date: 26-09-2018
Publisher: Elsevier BV
Date: 07-2020
Publisher: Emerald
Date: 16-04-2018
DOI: 10.1108/IJIUS-10-2017-0012
Abstract: The purpose of this paper is to present a preliminary solution to address the problem of estimating human pose and trajectory by an aerial robot with a monocular camera in near real time. The distinguishing feature of the solution is a dynamic classifier selection architecture. Each video frame is corrected for perspective using projective transformation. Then, a silhouette is extracted as a Histogram of Oriented Gradients (HOG). The HOG is then classified using a dynamic classifier. A class is defined as a pose-viewpoint pair, and a total of 64 classes are defined to represent a forward walking and turning gait sequence. The dynamic classifier consists of a Support Vector Machine (SVM) classifier C64 that recognizes all 64 classes, and 64 SVM classifiers that recognize four classes each – these four classes are chosen based on the temporal relationship between them, dictated by the gait sequence. The solution provides three main advantages: first, classification is efficient due to dynamic selection (4-class vs 64-class classification). Second, classification errors are confined to neighbors of the true viewpoints. This means a wrongly estimated viewpoint is at most an adjacent viewpoint of the true viewpoint, enabling fast recovery from incorrect estimations. Third, the robust temporal relationship between poses is used to resolve the left-right ambiguities of human silhouettes. Experiments conducted on both fronto-parallel videos and aerial videos confirm that the solution can achieve accurate pose and trajectory estimation for these different kinds of videos. For ex le, the “walking on an 8-shaped path” data set (1,652 frames) can achieve the following estimation accuracies: 85 percent for viewpoints and 98.14 percent for poses.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2020
Publisher: Academic Conferences International Ltd
Date: 08-06-2022
Abstract: As the space sector continues to grow, so do the cybersecurity risks. As large as the attack surface of a space system is, the ground segment remains an attractive source of intrusion points, not only because of its relative accessibility but also because the ground system is often viewed as little more than a conventional IT system. Thus, a representative security assessment of a space system cannot avoid addressing the vulnerabilities of the associated ground system and the relevant threats. This motivates the construction of a virtual ground station testbed, as part of larger reference platform, to support our ongoing research on the cybersecurity of space systems. Presented here is a discussion of the preliminary work being undertaken at the University of South Australia node of the SmartSat Cooperative Research Centre on such a testbed. A distinguishing feature of the testbed is the integration of a security information and event management (SIEM) system justifying the name of the testbed, “SIEM4GS”. Based on the latest literature on ground stations, a logical architecture and an implementation plan involving only open-source software building blocks for SIEM4GS are proposed. Features of the ground station and SIEM services are discussed. A plan is provided on how to extend the SIEM system from a primarily “detect” role in the NIST Cybersecurity Framework to a “detect and respond” role.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2015
Publisher: Wiley
Date: 03-12-2010
DOI: 10.1002/SEC.256
Publisher: Academic Conferences International Ltd
Date: 28-02-2023
Abstract: Hypersonic vehicles are vehicles travelling faster than Mach 5 (five times the speed of sound). Hypersonic technologies have existed since the end of the 1950s, but recent developments of defence applications have led to their resurgence. Hypersonic weapons can be hypersonic (powered) cruise missiles or hypersonic glide vehicles (HGVs). The near-space trajectories of HGV, combined with their superior manoeuvrability, enable HGVs to evade existing space and terrestrial sensors used to track ballistic missiles, posing an immediate threat to today’s radar networks and making HGVs well-suited for intercontinental ( 5500 km) targets. Securing HGV detection and tracking systems is of great interest to at-risk nations and cybersecurity researchers alike. However, like hypersonic flight technologies, HGV defence technologies are heavily guarded secrets. The shortage of public-domain information did not stop academia from proposing various detection and tracking schemes, but a reasonable question is: “How credible and useful is current public-domain information, including academic publications, on HGV detection and tracking for academic researchers to base their cybersecurity research on?” To answer this question, we scanned and critically reviewed public-domain literature on HGV detection and tracking. We then identified ambiguities and knowledge gaps in the literature. In this paper, we provide a concise version of our multivocal literature review and an analysis of the identified ambiguities and knowledge gaps in our attempt to answer our earlier question.
Publisher: Springer Science and Business Media LLC
Date: 04-08-2010
DOI: 10.1155/2011/685219
Publisher: Academic Conferences International Ltd
Date: 19-06-2023
Abstract: This paper briefly reviews the application of the Software-defined Networking (SDN) architecture to satellite networks. It highlights the prominent cyber threats that SDN-based satellite networks are vulnerable to and proposes relevant defence mechanisms. SDN transforms traditional networking architectures by separating the control plane from the forwarding (data) plane. This separation enhances scalability and centralises management. In comparison, in traditional networks, the control plane and the data plane are usually combined, resulting in complex network management and reduced scalability. Satellite networks can take advantage of these benefits offered by SDN and this supports them as key enablers of critical services, including weather prediction, global broadband Internet coverage, and Internet of Things (IoT) services. Ease of configuration and flexibility are essential for satellites providing critical services to instantly adapt to network changes. These desirable attributes can be realised by applying SDN to satellite networks. Although SDN offers significant benefits to satellite networks, it is vulnerable to cyber-attacks and particularly due to its centralised architecture. A common attack on SDN is the Distributed Denial of Service (DDoS) attack which could render the entire SDN unavailable. To mitigate such threats, an efficient Intrusion Detection System (IDS) is required to monitor the network and detect any suspicious traffic. However, traditional IDSs produce too many false positives and often fail to detect advanced attacks. For their ability to learn feature hierarchies in network traffic data automatically, whether, for network traffic classification or anomaly detection, deep learning (DL) plays an increasingly important role in IDSs. In this paper, we present a brief review of recent developments in cyber security for SDN-based space systems, and we identify vulnerabilities and threats to an SDN-based satellite network. We further discuss the potential of a DL-based IDS for the detection of cyber threats. Finally, we identify further research gaps in the recent literature and propose future research directions.
Publisher: Springer Science and Business Media LLC
Date: 29-06-2018
Publisher: Springer International Publishing
Date: 2014
Publisher: ACM
Date: 21-06-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2013
Publisher: ACM
Date: 07-11-2005
Publisher: MDPI AG
Date: 31-12-2020
DOI: 10.3390/SYM13010056
Abstract: Autonomous vehicles need to localize themselves within the environment in order to effectively perform most tasks. In situations where a Global Navigation Satellite System such as the Global Positioning System cannot be used for localization, other methods are required. One self-localization method is to use signals transmitted by beacons at known locations to determine the relative distance and bearing of the vehicle from the beacons. Estimation performance is influenced by the beacon–vehicle geometry and the investigation into the optimal placement of beacons is of interest to maximize the estimation performance. In this article, a new solution to the optimal beacon placement problem for self-localization of a vehicle on a two-dimensional plane using angle-of-arrival measurements is proposed. The inclusion of heading angle in the estimation problem differentiates this work from angle-of-arrival target localization, making the optimization problem more difficult to solve. First, an expression of the determinant of the Fisher information matrix for an arbitrary number of beacons is provided. Then, a procedure for analytically determining the optimal angular separations for the case of three beacons is presented. The use of three beacons is motivated by practical considerations. Numerical simulations are used to demonstrate the optimality of the proposed method.
No related grants have been discovered for Yee Wei Law.