Hang Lei's research while affiliated with University of Electronic Science and Technology of China and other places

Publications (64)

Conference Paper
The Internet of Things (IoT) has become increasingly popular due to the enormous growth in the number of smart devices and the massive amount of data these devices generate. Data access and sharing has been one of the most valuable services of the IoT network. For this reason, the security and privacy of the data are of great essence to harnessing...
Article
Full-text available
A public blockchain network ensures security, performance, and integrity through its consensus algorithm. However, most public blockchain consensus algorithms require intensive resources such as; energy, CPU, stake, and memory. Further, the incentive mechanisms of most permissionless consensus algorithms are biased towards the miners having the mos...
Article
Full-text available
The rapid advancement of the Internet of Vehicles (IoV) has led to a massive growth in data received from IoV networks. The cloud storage has been a timely service that provides a vast range of data storage for IoV networks. However, existing data storage and access models used to manage and protect data in IoV networks have proven to be insufficie...
Article
Recently, chaotic systems have become a thrilling discipline for information security applications, particularly in designing entropy sources. This paper presents a novel technique to tame an optimized 4D hyperchaotic Lorenz system by building a reconfigurable high randomness and low-cost hardware true random number generator (HC-HTRNG). Moreover,...
Article
Secure transmission of data is achieved through the steganography images, where the secret data are embedded and transmitted so that the prohibited users couldn’t able to access the data. In this research, the data are embedded in the optimal location of the network using the proposed FIEO Optimal Location Enabled Stegochain. The algorithm effectiv...
Chapter
With the continuous development of electronic countermeasures technology, how to achieve accurate and rapid target location in complex electromagnetic environment has outstanding application prospects and research value. The traditional active location technology requires the emission of electromagnetic waves outward, and the frequency band is rela...
Article
Full-text available
The quest to create a vaccine for covid-19 has rekindled hope for most people worldwide, with the anticipation that a vaccine breakthrough would be one step closer to the end of the deadly Covid-19. The pandemic has had a bearing on the use of Twitter as a communication medium to reach a wider audience. This study examines Covid-19 vaccine-related...
Article
Full-text available
The advancement of digital technology has played an essential role in shaping the impact of social media. The increasing number of people who use Facebook, Twitter, Instagram, weblogs, and other social networking sites has led to a considerable amount of textual content online, including news articles and historical documents. Information published...
Article
With the rapid development of parallel programming techniques and the widespread use of multiprocessors, scheduling and analysis techniques supporting parallel real-time tasks become a critical topic for multiprocessor real-time systems. Global scheduling that allows the vertices of a parallel task to execute on any processor is a promising schedul...
Article
In the real-time scheduling theory, schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols, respectively, and the empirical synthesis experiment is one of the major methods to compare the performance of such analyses. However, since many sophisticated techniques have been adopted to im...
Chapter
Fine-tuning the pre-trained language model is the current mainstream method of text classification. Take the fine-tuning BERT model as an example, this kind of approach has three main problems: the first one is that the training of massive parameters will cause high training costs The second is that the model is very easy to over-fit in trainable s...
Article
Full-text available
The ultimate focus of this paper is to provide a hyperchaos-based reconfigurable platform for the real-time securing of communicating embedded systems interconnected in networks according to the Internet of Things (IoT) standards. The proposed platform’s Register Transfer Level (RTL) architecture is entirely developed and designed from scratch usin...
Article
Full-text available
The ability of pre-trained BERT model to achieve outstanding performances on many Natural Language Processing (NLP) tasks has attracted the attention of researchers in recent times. However, the huge computational and memory requirements have hampered its widespread deployment on devices with limited resources. The concept of knowledge distillation...
Article
Parallel tasks have been paid growing attention in recent years, and the scheduling with shared resources is of significant importance to real-time systems. As an efficient mechanism to provide mutual exclusion for parallel processing, spin-locks are ubiquitous in multi-processor real-time systems. However, the spin-locks suffer the scalability pro...
Article
Full-text available
Image representation plays a vital role in the realisation of Content-Based Image Retrieval (CBIR) system. The representation is performed because pixel-by-pixel matching for image retrieval is impracticable as a result of the rigid nature of such an approach. In CBIR therefore, colour, shape and texture and other visual features are used to repres...
Chapter
Colour feature indexing for images has seen several approaches such as Conventional Colour Histogram, Colour Coherent Vector, Colour Moment and Colour Correlogram. These approaches for indexing images have proven to be fast, simple, and retrieve images from database with satisfactory results. The strength of these approaches however is based on the...
Chapter
Full-text available
The advances in deep learning (DL) models have proven to achieve outstanding results in text classification tasks. This success is due to DL models’ potential to reach high accuracy with less need for engineered features. Despite their popularity, DL models have their strengths and weaknesses in their learning capacity, depending on the task. Resea...
Article
Generative adversarial network(GAN) has shown profound power in machine learning. It inspires many researchers from other fields to create powerful tools for various tasks, including quantum state preparation, quantum circuit translation, and so on. It is known as classical techniques cannot efficiently simulate the quantum system, and the existing...
Article
Quantum machine learning (QML) is a rapidly rising research eld that incorporates ideas from quantum computing and machine learning to develop emerging tools for scientic research and improving data processing. How to efciently control or manipulate the quantum system is a fundamental and vexing problem in quantum computing. It can be described as...
Chapter
With the rapid development of blockchain technology, the reliability and security of blockchain smart contracts is one of the most emerging issues of greatest interest for researchers. In this paper, the framework of formal symbolic process virtual machine, called FSPVM-EOS, is presented to certify the reliability and security of EOS-based smart co...
Article
With the wide use of multiprocessor architecture, parallel tasks have been receiving growing attention in both industry and academia. In real-time systems, the scheduling and synchronization that ensure predictable task execution and resource access are of utmost importance. Although the scheduling of (independent) parallel tasks is widely studied...
Preprint
Full-text available
In early 2020, the Corona Virus Disease 2019 (COVID-19) epidemic swept the world. In China, COVID-19 has caused severe consequences. Moreover, online rumors during COVID-19 epidemic increased people's panic about public health and social stability. Understanding and curbing the spread of online rumor is an urgent task at present. Therefore, we anal...
Article
Full-text available
The security of blockchain smart contracts is one of the most emerging issues of the greatest interest for researchers. This article presents an intermediate specification language for the formal verification of Ethereum-based smart contract in Coq, denoted as Lolisa. The formal syntax and semantics of Lolisa contain a large subset of the Solidity...
Chapter
Content-Based Image Retrieval (CBIR) systems work by searching huge databases for similar images that match a query image. The CBIR systems depend on computing similarity between two images to retrieve images of interest. The choice of suitable similarity measuring tool is key for effective and efficient retrieval of images. Predominantly similarit...
Article
Geometric analysis of three-dimensional (3D) surfaces with local deformations is a challenging task, required by mobile devices. In this paper, we propose a new local feature-based method derived from diffusion geometry, including a keypoint detector named persistence-based Heat Kernel Signature (pHKS), and a feature descriptor named Heat Propagati...
Preprint
Real-time scheduling and locking protocols are fundamental facilities to construct time-critical systems. For parallel real-time tasks, predictable locking protocols are required when concurrent sub-jobs mutually exclusive access to shared resources. This paper for the first time studies the distributed synchronization framework of parallel real-ti...
Article
Full-text available
Hardware support for isolated execution (e.g., ARM TrustZone) enables the development of a trusted execution environment (TEE) that ensures the security of the code and data while communicating with a compromised rich execution environment (REE). The ability to satisfy various security services is complicated and usually consists of trusted applica...
Article
Full-text available
This paper reports a formal symbolic process virtual machine (FSPVM) denoted as FSPVM-E for verifying the reliability and security of Ethereum-based services at the source code level of smart contracts. A Coq proof assistant is employed for programming the system and for proving its correctness. The current version of FSPVM-E adopts execution-verif...
Article
Coordinated partitioning and resource sharing have attracted considerable research interest in the field of real-time multiprocessor systems. However, finding an optimal partition is widely known as NP-hard, even for independent tasks. A recently proposed resource-oriented partitioned (ROP) fixed-priority scheduling that partitions tasks and shared...
Article
Recently, blockchain technology has been widely applied in the financial field. Therefore, the security of blockchain smart contracts is among the most popular contemporary research topics. To improve the theorem-proving technology in this field, we are developing an extensible hybrid verification proof en-gine, denoted as FEther, for Ethereum smar...
Preprint
This paper reports on the development of a formal symbolic process virtual machine (FSPVM) denoted as FSPVM-E for verifying the reliability and security of Ethereum-based services at the source code level of smart contracts, and a Coq proof assistant is employed for both programming the system and for proving its correctness. The current version of...
Article
In recent publications, we presented a novel formal symbolic process virtual machine (FSPVM) framework that combined higher-order logic theorem proving and symbolic execution for verifying the reliability and security of smart contracts developed in the Ethereum blockchain system without suffering from standard issues surrounding reusability, consi...
Conference Paper
Global Platform (GP)1 specifications accepted as de facto industry standards are widely used for the development of embedded operating system running on secure chip devices. A promising approach to demonstrating the implementation of an OS meets its specification is formal verification. However, most previous work on operating system verification t...
Preprint
In recent publications, we presented a novel formal symbolic process virtual machine (FSPVM) framework that combined higher-order theorem proving and symbolic execution for verifying the reliability and security of smart contracts developed in the Ethereum blockchain system without suffering the standard issues surrounding reusability, consistency,...
Preprint
In recent years, a number of lightweight programs have been deployed in critical domains, such as in smart contracts based on blockchain technology. Therefore, the security and reliability of such programs should be guaranteed by the most credible technology. Higher-order logic theorem proving is one of the most reliable technologies for verifying...
Article
Salient region detection without prior knowledge is a challenging task, especially for 3D deformable shapes. This paper presents a novel framework that relies on clustering of a data set derived from the scale space of the auto diffusion function. It consists of three major techniques: scalar field construction, shape segmentation initialization an...
Article
This paper presents a learned feature based framework for both outdoor and indoor scene labelling. This framework is combined with a discriminative feature learning process to produce the posteriors of every pixel and a novel strategy to improve the global label consistency of a scene. First, we use Convolutional Neural Networks (ConvNets) to learn...
Article
Full-text available
Job search through online matching engines nowadays are very prominent and beneficial to both job seekers and employers. But the solutions of traditional engines without understanding the semantic meanings of different resumes have not kept pace with the incredible changes in machine learning techniques and computing capability. These solutions are...
Conference Paper
We present a novel local shape descriptor by means of General Adaptive Neighborhoods (GANs) based on the properties of the heat diffusion process on a Riemannian manifold. The GAN is a spatial region, surrounding the feature point and fitting its local shape structure, which is isometric. Our signature, called the Heat Propagation Contours (HPCs),...
Conference Paper
Abstract This paper presents an efficient feature point descriptor for non-rigid shape analysis. The descriptor is developed based on the properties of the heat diffusion process on a shape. We use, for the first time, the Heat Kernel Signature of a particular time scale to define the scalar field on a manifold. Then, motivated by the successful u...
Article
In this article, how word embeddings can be used as features in Chinese sentiment classification is presented. Firstly, a Chinese opinion corpus is built with a million comments from hotel review websites. Then the word embeddings which represent each comment are used as input in different machine learning methods for sentiment classification, incl...
Conference Paper
This paper presents a learned feature based method for scene labelling. This method is combined with a novel strategy to improve global label consistency. We first follow a traditional way to investigate trained features from convolutional neural networks (ConvNets) for scene labelling. Then, motivated by the recent successful use of general featur...
Article
The purpose of this paper is to investigate heterogeneous multi-column ConvNets (MCCNN) and fusion methods for them. We first construct heterogeneous MCCNN by combining ConvNets with different structures. We then use different fusion methods to check their performances to find out the effect of fusion methods for MCCNN. We also propose a novel slid...
Article
The Multiprocessor Priority Ceiling Protocol (MPCP) is a classic suspension-based real-time locking protocol for partitioned fixed-priority (P-FP) scheduling. However, existing blocking time analysis is pessimistic under the P-FP + MPCP scheduling, which negatively impacts the schedulability for real-time tasks. In this paper, we model each task as...
Conference Paper
With rapid development of Graphics Processing Units (GPU) technologies, GPUs are strongly motivated to be adopted in many real-time applications. However, it is still a challenging work to efficiently integrate multiple GPUs into multicore/multiprocessor real-time systems, due to many real world constraints caused by the non-real-time closed-source...
Article
Multicore processors are increasingly used in real-time embedded systems. Better utilization of hard real-time systems requires accurate scheduling and synchronization analysis. In this paper, we characterize the major synchronization penalties arising from partitioned fixed priority scheduling for hard real-time tasks on multicore platform, includ...

Citations

... Ethereum [10] has witnessed a great impact of this technology. Other notable applications of blockchain technology include identity-based PKI [11], crowdsourcing [12], internet of vehicle network [13], trading platforms [14], and IoT software update [15]. Fig.1 shows a structure of the blockchain. ...
... According to reports, the Support Vector Machine (SVM) classifier is the best match for the dataset with an accuracy of 84.32 percent. This study illustrates how Twitter data and machine learning techniques may be used to analyze the developing public discourse and attitudes on the Covid-19 vaccine deployment campaign [24]. In more recent study, Hutama and Suhartono used the pre-trained transformer multilingual model (XLM-R and mBERT) in conjunction with a BERTopic model as a topic distribution model to categorize Indonesian fake news. ...
... For means of data security within an IoT network, a Lorenz IP core was implemented to create a chaotic solution for low-power data encryption [86]. A chaotic system is one that produces seemingly random results from an outside perspective, but are predictable if the starting conditions are known. ...
... In the second eld, Twitter and other social media platforms have taken the lead in expressing opinions and sentiments during con icts by allowing researchers to conduct real-time assessments that may aid authorities to develope early response strategies [9]. For example, one study examined one of the most di cult challenges in international politics, the rule of Taliban in Afghanistan after the withdrawal of US soldiers, using public opinion expressed in tweets [10]. ...
... Ethereum [10] has witnessed a great impact of this technology. Other notable applications of blockchain technology include identity-based PKI [11], crowdsourcing [12], internet of vehicle network [13], trading platforms [14], and IoT software update [15]. Fig.1 shows a structure of the blockchain. ...
... This is generally because when the orientation of an image changes, the texton feature extractions also turn to produce different feature maps or vectors for the same image. The SCH approach proposed in [23] employed recurrent blurring to extract inherent textural information, thus solving the rigid nature of the textons. ...
... We developed an address verification program using a deep learning technique ( Figure 3). In this research, we use the deep learning technique for the text (address components) classification task as the deep learning technique may outperform other traditional machine learning algorithms in terms of performance, accuracy, and adaptability [32][33][34][35][36]. First, a Long Short-Term Memory (LSTM)-based multi-class classification model was created after labeling and character embedding on country-specific administrative district data. ...
... While applying TJM in this fault diagnosis experiment, we can get an average accuracy of 95.37% which is 3.81% lower than the eDANN. However, TJM owns better performance than the eDANN for domain adaptation scenarios of A ! D and D ! A. Deep Model Based Domain Adaptation (DAFD) [17] mainly induces MMD [39] algorithm to the autoencoder based Deep Neural Network (DNN) to extract the transferrable features. DAFD performs well in domain adaptation scenarios of D ! ...
... 20% compression higher than JPEG compression technology. The basic difference in the working mechanism between JPEG and 2000 JPEG is the first adoption of the transform and the last adoption of the wave transform [12]. ...
... Related Work: The traditional software testing methodology [11] cannot guarantee smart contracts' correctness and high reliability. Formal verification [12] has been proposed in the blockchain field involving Solidity [13][14][15], ethereum virtual machine (EVM) bytecode [16][17][18][19][20], and EOS [21][22]. On one side, different verification frameworks commonly only support one particular language of smart contracts. ...