Raphael C.-W. Phan

• PhD
• Professor at Monash University Malaysia

Energy-based models (EBMs) are a powerful class of probabilistic generative models due to their flexibility and interpretability. However, relationships between potential flows and explicit EBMs remain underexplored, while contrastive divergence training via implicit Markov chain Monte Carlo (MCMC) sampling is often unstable and expensive in high-d...

Detecting concealed emotions within apparently normal expressions is crucial for identifying potential mental health issues and facilitating timely support and intervention. The task of spotting macro and micro-expressions involves predicting the emotional timeline within a video, accomplished by identifying the onset, apex, and offset frames of th...

Medical image denoising is essential for improving the reliability of clinical diagnosis and guiding subsequent image-based tasks. In this paper, we propose a multi-scale approach that integrates anisotropic Gaussian filtering with progressive Bezier-path redrawing. Our method constructs a scale-space pyramid to mitigate noise while preserving crit...

Action recognition in dark, low-light (under-exposed) or noisy videos is a challenging task due to visibility degradation, which can hinder critical spatiotemporal details. This paper proposes MD-BERT, a novel multi-stream approach that integrates complementary pre-processing techniques such as gamma correction and histogram equalization alongside...

Modern brain imaging technologies have enabled the detailed reconstruction of human brain connectomes, capturing structural connectivity (SC) from diffusion MRI and functional connectivity (FC) from functional MRI. Understanding the intricate relationships between SC and FC is vital for gaining deeper insights into the brain's functional and organi...

Diffusion tractography, a cornerstone of white matter mapping, relies on point-to-point stream-line propagation—a process often compromised by errors stemming from inadequate signal-to-noise ratio and limited spatial-angular resolution in diffusion MRI (dMRI) data. Here, we present Anatomy-to-Tract Mapping (ATM), a novel deep learning framework tha...

Brain tumor detection in multiplane Magnetic Resonance Imaging (MRI) slices is a challenging task due to the various appearances and relationships in the structure of the multiplane images. In this paper, we propose a new You Only Look Once (YOLO)-based detection model that incorporates Pretrained Knowledge (PK), called PK-YOLO, to improve the perf...

Analyzing the community structure of brain networks provides new insights into human brain function. Existing studies broadly use conventional network clustering approaches. While graph neural networks have recently shown promise in modeling brain functional connectivity (FC) networks, their applications to brain community detection still need impr...

Recent applications of pattern recognition techniques on brain connectome classification using functional connectivity (FC) are shifting towards acknowledging the non-Euclidean topology and dynamic aspects of brain connectivity across time. In this paper, a deep spatiotemporal variational Bayes (DSVB) framework is proposed to learn time-varying top...

Brain functional connectivity (FC) networks inferred from functional magnetic resonance imaging (fMRI) have shown altered or aberrant brain functional connectome in various neuropsychiatric disorders. Recent application of deep neural networks to connectome-based classification mostly relies on traditional convolutional neural networks (CNNs) using...

Extreme learning machines (ELMs) are shown to be efficient and effective learning algorithms for regression and classification tasks. ELMs, however, are typically utilized to solve supervised learning problems. Only a handful of research on ELMs focuses on exploring unlabeled data. One representative work is the unsupervised extreme learning machin...

With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection. However, the performance of using YOLO networks is scarcely investigated in brain tumor detection. We propose a novel YOLO architecture with Reparameterized Convolution based on channel Shuffle (R...

The Facial Action Coding System (FACS) comprehensively describes facial expressions with facial action units (AUs). It is a well-used technique by researchers in emotions research to understand human emotions better. Most micro-expression datasets provide FACS-coded AU ground truths corresponding to micro-expressions classes. It is commonly accepte...

With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection. However, the performance of using YOLO networks is scarcely investigated in brain tumor detection. We propose a novel YOLO architecture with Reparameterized Convolution based on channel Shuffle (R...

Behavioral biometrics is an emerging trend due to their cost-effectiveness and non-intrusive implementations that support remote access for user identification. This is the case especially in recent times of social distancing and working from home arrangements, where online attendance is the preferred option in contrast to physical presence. In thi...

Common measures of brain functional connectivity (FC) including covariance and correlation matrices are semi-positive definite (SPD) matrices residing on a cone-shape Riemannian manifold. Despite its remarkable success for Euclidean-valued data generation, use of standard generative adversarial networks (GANs) to generate manifold-valued FC data ne...

Recent applications of pattern recognition techniques to brain connectome-based classification focus on static functional connectivity (FC) neglecting the dynamics of FC over time, and use input connectivity matrices on a regular Euclidean grid. We exploit the graph convolutional networks (GCNs) to learn irregular structural patterns in brain FC ne...

Facial micro-expressions are crucial cues for expressing human emotions. Existing works have shown substantial progress in detecting micro-expressions for various applications in the computer vision field. However, it is still onerous for existing methods to handle and interpret micro-expressions efficiently. This paper proposes a deep learning-bas...

Emotions are essential for human communication as they reflect our inner states and influence our actions. Today, emotions provide crucial information to many applications, from virtual assistants to security systems, mood-tracking wearable devices, and autism robots. The speech emotion recognition (SER) model must be lightweight to run on varying...

Photocatalysis has emerged as a powerful technology with beneficial impacts on the fields of science and engineering. To date, most photocatalysis research are experimentally-based that strongly rely on various experimental conditions. As the coronavirus pandemic hit the world in 2020, research and experiments were disrupted in various scientific d...

It is vital to authenticate the content of speech signals to prevent the framing of innocent individuals. Furthermore, lack of speech content authentication may lead to repudiation. The research problem of authenticity vs falsehood is timely considering the recent worldwide interest in fake news and viral manipulated media. Liu & Wang proposed an a...

This paper first presents a novel approach for modelling facial features, Local Directional Texture (LDT), which exploits the unique directional information in image textures for the problem of face recognition. A variant of LDT with privacy-preserving temporal strips (TS) is then considered to achieve faceless recognition with a higher degree of p...

Several studies on micro-expression recognition have contributed mainly to accuracy improvement. However, the computational complexity receives lesser attention comparatively and therefore increases the cost of micro-expression recognition for real-time application. In addition, majority of the existing approaches required at least two frames (i.e....

Genetic algorithm, a technique inspired by evolutionary biology to mimic the process of natural selection, has been applied in the image encryption due to the confusion and diffusion properties of mutation and crossover processes involved in the genetic algorithm. In this paper, we analyze the security of the image encryption designed based on gene...

Fingerprint is the most well-known and successfully deployed biometric modalities in view of its ease of acquisition, established use, acceptance and high recognition rate (i.e., robustness). This is also due in part to its use in crime scene investigations to link crimes to suspected individuals. One form of fingerprint is called the latent finger...

This paper proposes a novel approach for privacy-preserving facial recognition based on the new feature computation technique: Local Binary Pattern from Temporal Planes (LBP-TP) that extracts information from only the XT or YT planes of a video sequence; in contrast to previous work that depend significantly on spatial information within the video...

The key encapsulation mechanism is an important cryptographic tool to protect communication in Internet of Things. In the near future, classical algorithms used to construct key encapsulation mechanisms, such as RSA and Elliptic Curve Cryptography, will be vulnerable to attacks from quantum computers. Recently, Yamada et al. proposed the QC-MDPC KE...

With the proliferation of the internet of things (IoT) and device-to-device (D2D) communications enabled by the boom of mobile computing technology, secure high-speed communication has now become indispensable in our daily life. This is especially true when potentially private data are being continually sensed by and communicated among mobile devic...

The latest techniques in video motion magnification and relevant small motion analysis are surveyed. The main motion magnification techniques are discussed in chronological fashion, highlighting the inherent limitations of predecessor techniques in comparison with subsequent variants. The focus is then shifted to the specific stages within the moti...

The emergence of Internet of Things (IoT) brings us the possibility to form a well connected network for ubiquitous sensing, intelligent analysis and timely actuation, which opens up many innovative applications in our daily life. To secure the communication between sensor nodes, gateway devices and cloud servers, cryptographic algorithms (e.g. dig...

With the emergence of IoT and cloud computing technologies, massive data are generated from various applications everyday and communicated through the Internet. Secure communication is essential to protect these data from malicious attacks. Block ciphers are one mechanism to offer such protection but unfortunately involve intensive computations tha...

A joint encryption and authentication scheme for HEVC compressed video is proposed in this work. It produces a HEVC format compliant video stream that permits the authentication process to be carried out irregardless of the video being in the encrypted or plaintext (i.e., decrypted) form. To achieve this separable property, one set of syntax elemen...

Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical diagnosis, forensic investigation and security systems. Advances in computer algorithms and video acquisition technology have rendere...

With the advent of telemedicine technology, many medical services can be provided remotely, which greatly enhances the welfare of our mankind. However, security and privacy of medical data transmitted through telecommunication systems remain a serious issue to be resolved when deploying such services. In particular, the medical images and data stor...

RSA is an algorithm widely used in protecting the key exchange between two parties for secure mobile and wireless communication. Modular exponentiation is the main operation involved in RSA, which is very time consuming when the bit-size is large, usually in the range of 1024-bit to 4096-bit. The speed performance of RSA comes to concerns when thou...

The emergence of Cloud Computing is revolutionizing the way we store, query, analyze and consume data, which also bring forward other development that fundamentally changed our life style. For example, Industry 4.0 and Internet of Things (IoT) can improve the quality of manufacturing and many aspects in our daily life; both of them rely heavily on...

Facial micro-expression (ME) recognition has posed a huge challenge to researchers for its subtlety in motion and limited databases. Recently, handcrafted techniques have achieved superior performance in micro-expression recognition but at the cost of domain specificity and cumbersome parametric tunings. In this paper, we propose an Enriched Long-t...

Micro-expressions can occur when a person attempts to conceal and suppress his true feelings and emotions, both deliberately or unconsciously.In recent years, facial micro-expression analysis has received tremendous attention in the field of psychology, media and computer vision. However, due to its subtlety and brief duration, development of autom...

Due to the increasing demand on secure image transmission, image encryption has emerged as an active research field in recent years. Many of the proposed image encryption schemes are designed based on chaotic maps with permutation–diffusion architecture. While most of these schemes reported good statistical properties, they are slow in execution sp...

In this paper, we revisit the notions of Square, saturation, integrals, multisets, bit patterns and tuples, and propose a new Slice & Fuse paradigm to better exploit multiset type properties of block ciphers, as well as relations between multisets and constituent bitslice tuples. With this refined analysis, we are able to improve the best bounds pr...

The fingerprint is arguably the most successfully deployed biometric data in a broad spectrum of applications for identification and verification purposes. While fingerprint matching algorithms are fairly matured, most studies have so far focused on improving the matching precision, and some effort has been channelled to combat spoofing attacks on...

Facial expression recognition has been intensively studied for decades, notably by the psychology community and more recently the pattern recognition community. What is more challenging, and the subject of more recent research , is the problem of recognizing subtle emotions exhibited by so-called micro-expressions. Recognizing a micro-expression is...

The utility providers are estimated to lose billions of dollars annually due to energy theft. Although the implementation of smart grids offers technical and social advantages, the smart meters deployed in smart grids are susceptible to more attacks and network intrusions by energy thieves as compared to conventional mechanical meters. To mitigate...

Higher order differentiation was introduced in a cryptographic context by Lai. Several attacks can be viewed in the context of higher order differentiations, amongst them the cube attack and the AIDA attack. All of the above have been developed for the binary case. We examine differentiation in larger fields, starting with the field $GF(p)$ of inte...

Recently, micro-expression recognition has seen an increase of interest from psychological and computer vision communities. As micro-expressions are generated involuntarily on a person’s face, and are usually a manifestation of repressed feelings of the person. Most existing works pay attention to either the detection or spotting of micro-expressio...

This book constitutes the refereed post-conference proceedings of the Second International Conference on Cryptology and Malicious Security, held in Kuala Lumpur, Malaysia, December 1-2, 2016. The 26 revised full papers, two short papers and two keynotes presented were carefully reviewed and selected from 51 submissions. The papers are organized in...

An HEVC format-compliant joint selective encryption and data embedding technique is proposed. The proposed technique is separable, where the decryption and data extraction processes are independent, with minimal parsing overhead. Specifically, elements in the HEVC coding structure are divided into two groups, where one group is manipulated to perce...

In 2004, Bellare et al. formalized the notion for identity-based identification (IBI) schemes and proposed many schemes based on their transformation from standard identification schemes. However the authors left the security under active/concurrent attacks of one of the pairing-free schemes, the Beth-IBI scheme, as an open problem. In 2008, Cresce...

Ye and Zhou [Appl. Soft. Comput. 22 (2014) 351-357] proposed an efficient chaotic based image encryption scheme which only employs diffusion, while usually both confusion and diffusion are used for encryption structures. We present both chosen-plaintext and chosen-ciphertext attacks against the scheme for any number of its rounds r by exploiting r-...

In this work, we propose a novel sketch attack for H.264/AVC format-compliant encrypted video. We briefly describe the notion of sketch attack, review the conventional sketch attacks designed for DCT based compressed image, and identify their shortcomings when applied to attack compressed video. Specifically, the conventional DCT based sketch attac...

A multi-layer authentication scheme for HEVC compressed video is proposed. The combination of CU sizes, which is unique to HEVC and sensitive to video manipulation, is considered along with other elements in the HEVC coding standard to generate the authentication tag. Temporal dependency was enforced, where the authentication tag generated in one s...

Optical strain is an extension of optical flow that is capable of quantifying subtle changes on faces and representing the minute facial motion intensities at the pixel level. This is computationally essential for the relatively new field of spontaneous micro-expression, where subtle expressions can be technically challenging to pinpoint. In this p...

Despite recent interest and advances in facial micro-expression research, there is still plenty room for improvement in terms of micro-expression recognition. Conventional feature extraction approaches for micro-expression video consider either the whole video sequence or a part of it, for representation. However, with the high-speed video capture...

Despite recent interest and advances in facial micro-expression research, there is still plenty room for improvement in terms of micro-expression recognition. Conventional feature extraction approaches for micro-expression video consider either the whole video sequence or a part of it, for representation. However, with the high-speed video capture...

Smart devices capture users' activity information such as unlock failures, application usage, location and proximity of devices in and around its surrounding environment. This activity information varies between users and can be considered as digital fingerprints of the users' behaviour. Traditionally, users are authenticated to access restricted d...

Wadi and Zainal recently proposed a high definition image encryption algorithm based on a modified AES-128 block cipher in (Wirel Pers Commun 79(2):811–829, 2014). In this paper, we show that the core component of their image encryption algorithm, a modified AES-128 cipher, is insecure against impossible differential attack. The proposed impossible...

One of the general ways in designing a secure image encryption algorithm based on chaos theory is to derive a number of round subkeys from the Key Schedule algorithm under the control of an external secret key. A compulsory condition for the security of an image encryption algorithm is that the length of the external secret key should be sufficient...

Smart devices capture users' activity such as unlock failures, application usage, location and proximity of devices in and around its surrounding environment. This activity information varies between users and can be used as digital fingerprints of the users' behaviour. Traditionally, users are authenticated to access restricted data using long ter...

GPU is widely used in various applications that require huge computational power. In this paper, we contribute to the cryptography and high performance computing research community by presenting techniques to accelerate symmetric block ciphers (AES-128, CAST-128, Camellia, SEED, IDEA, Blowfish and Threefish) in NVIDIA GTX 980 with Maxwell architect...