- Epping, New South Wales, Australia
Xiangjian He
University of Technology Sydney, Computing and communication, Faculty Member
Research Interests:
Web servers and web-based applications are commonly used as attack targets. The main issues are how to prevent unauthorised access and to protect web servers from the attack. Intrusion Detection Systems (IDSs) are widely used security... more
Web servers and web-based applications are commonly used as attack targets. The main issues are how to prevent unauthorised access and to protect web servers from the attack. Intrusion Detection Systems (IDSs) are widely used security tools to detect cyber-attacks and malicious activities in computer systems and networks. In this paper, we focus on the detection of various web-based attacks using Geometrical Structure Anomaly Detection (GSAD) model and we also propose a novel algorithm for the selection of most discriminating features to improve the computational complexity of payload-based GSAD model. Linear Discriminant method (LDA) is used for the feature reduction and classification of the incoming network traffic. GSAD model is based on a pattern recognition technique used in image processing. It analyses the correlations between various payload features and uses Mahalanobis Distance Map (MDM) to calculate the difference between normal and abnormal network traffic. We focus on ...
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these... more
Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the ...
Research Interests: Computer Science, Algorithms, Artificial Intelligence, Biomedical Engineering, Medical Physics, and 9 moreParticle Swarm Optimization, Medicine, Endoscopy, Computer assisted orthopaedic surgery, Electromagnetic phenomena, X ray Computed Tomography, Monte Carlo Method, Video Recording, and Endoscopes
This paper proposes an observation-driven adaptive differential evolution algorithm that fuses bronchoscopic video sequences, electromagnetic sensor measurements, and computed tomography images for accurate and smooth bronchoscope... more
This paper proposes an observation-driven adaptive differential evolution algorithm that fuses bronchoscopic video sequences, electromagnetic sensor measurements, and computed tomography images for accurate and smooth bronchoscope three-dimensional motion tracking. Currently an electromagnetic tracker with a position sensor fixed at the bronchoscope tip is commonly used to estimate bronchoscope movements. The large tracking error from directly using sensor measurements, which may be deteriorated heavily by patient respiratory motion and the magnetic field distortion of the tracker, limits clinical applications. How to effectively use sensor measurements for precise and stable bronchoscope electromagnetic tracking remains challenging. We here exploit an observation-driven adaptive differential evolution framework to address such a challenge and boost the tracking accuracy and smoothness. In our framework, two advantageous points are distinguished from other adaptive differential evol...
Research Interests: Engineering, Computer Science, Algorithms, Artificial Intelligence, Computer Vision, and 11 moreMedical Image Analysis, Medicine, Computer assisted orthopaedic surgery, Humans, Three Dimensional Imaging, Image Enhancement, Bronchoscopy, Reproducibility of Results, Sensitivity and Specificity, Smoothness, and Medical and Health Sciences
Research Interests:
Research Interests:
Research Interests: Mathematics, Computer Science, Multivariate Statistics, Data Mining, Network Security, and 14 moreDoS Attack, Correlation, Feature Extraction, Computer System Security, Characterization, First-Order Logic, First Order Logic, Denial of Service, Network Traffic, Euclidean Distance, Feature Space, Denial of Service Attack, Multivariate Correlations, and Springer Ebooks
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests: Engineering, Computer Science, Distributed Computing, Data Mining, Network Security, and 14 moreDoS Attack, Cloud Computing, Anomaly Detection, Distibuted systems, Geometry, Computer Software, Cyber Security, Computer System Security, Intrusion Detection System, Computer Network Security, Parllel computing, Denial of Service, Server, and Denial of Service Attack
Research Interests: Engineering, Computer Science, Technology, Network Security, Real Time Computing, and 9 moreComputer Networks, Principal Component Analysis, Pattern Recognition, Intrusion Detection, Cyber Security, Intrusion Detection System, Principal Components, Telecommunications and Networking, and Data pre-processing
Research Interests: Computer Science, Artificial Intelligence, Data Mining, A Priori Knowledge, Intrusion Detection Systems, and 12 moreAnomaly Detection, Feature Selection, Network Intrusion Detection & Prevention, Linear Discriminant Analysis, Computer System Security, Real Time, Intrusion Detection System, High Dimensionality, Euclidean Distance, Anomaly Intrusion Detection, Linear discriminate analysis, and Feature vector
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests: Computer Science, Artificial Intelligence, Surgery, Computer Vision, Data Mining, and 15 moreImage Analysis, Support Vector Machines, Image segmentation, Image Classification, Medical Engineering, Segmentation, Support vector machine, Surgical Planning, Texture Analysis, Liver Disease, Pixel, Nova, Morphological Operation, Image Texture, and Automatic segmentation
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests: Mathematics, Computer Science, Artificial Intelligence, Computer Vision, Categorization, and 15 moreProcessing Speed, Gaussian processes, Image Classification, Quantization, Object Recognition, Colour, Indexing, Histogram, Robustness, Image matching, Intersection, Boolean Satisfiability, Histograms, Application Software, and Histogram matching
Research Interests:
Research Interests:
Research Interests:
Real images are often corrupted by noise from various sources. Bilateral filtering is a nonlinear filter that considers intensity variations as well as spatial closeness in the noise smoothing process. It has been demonstrated to have a... more
Real images are often corrupted by noise from various sources. Bilateral filtering is a nonlinear filter that considers intensity variations as well as spatial closeness in the noise smoothing process. It has been demonstrated to have a better edge-preserving quality ...