Chongzhi Gao's research while affiliated with Guangzhou University and other places
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Publications (23)
To support multi-source data stream generated from Internet of Things devices, edge computing emerges as a promising computing pattern with low latency and high bandwidth compared to cloud computing. To enhance the performance of edge computing within limited communication and computation resources, we study a cloud-edge-end computing architecture,...
Due to its low latency and energy consumption, edge computing technology is essential in processing multi-source data streams from intelligent devices. This article investigates a mobile edge computing network aided by wireless power transfer (WPT) for multi-source data streams, where the wireless channel parameters and the characteristic of the da...
![Impact of the weight factor μ\documentclass[12pt]{minimal}...](publication/370152533/figure/fig5/AS:11431281152144504@1682044789296/Impact-of-the-weight-factor-mdocumentclass12ptminimal-usepackageamsmath_Q320.jpg)
This paper investigates a non-orthogonal multiple access (NOMA)-aided mobile edge computing (MEC) network with multiple sources and one computing access point (CAP), in which NOMA technology is applied to transmit multi-source data streams to CAP for computing. To measure the performance of the considered NOMA-aided MEC network, we first design the...
In this paper, we investigate an intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) network under physical-layer security, where users can partially offload confidential and compute-intensive tasks to a computing access point (CAP) with the help of the IRS. We consider an eavesdropping environment, where an eavesdropper steal...
This article examines a multi-user mobile edge computing (MEC) system for the Internet of Vehicle (IoV), where one edge point (EP) nearby the vehicles can help assist in processing the compute-intensive tasks. For the MEC networks, the majority of existing works concentrate on the minimization of system cost of task offloading under the perfect cha...
In this paper, we investigate a multiuser mobile edge computing (MEC)-aided smart Internet of vehicle (IoV) network, where one edge server can help accomplish the intensive calculating tasks from the vehicular users. For the MEC networks, most existing works mainly focus on minimizing the system latency to guarantee the user’s quality of service (Q...
In the big data background, data privacy becomes more and more important when data leakage and other security events occur more frequently. As one of the key means of privacy protection, anonymous communication attracts large attention. Aiming at the problems such as low efficiency of message forwarding, high communication delay and abusing of anon...
In this paper, we investigate a multiuser mobile edge computing (MEC)-aided smart internet of vehicle (IoV) network, where one edge server can help accomplish the intensive computational tasks from the vehicular users. For the MEC networks, most of existing works mainly focus on minimizing the system latency to guarantee the user's quality of servi...
In recent years, many adversarial malware examples with different feature strategies, especially GAN and its variants, are introduced to handle the security threats, e.g., evading the detection of machine learning detector. However, these solutions still suffer from problems of complicated deployment or long running time. In this paper, we propose...
In a proxy re-signature scheme, a semi-trusted proxy can convert Alice's (also called as delegatee's) signature into Bob's (also called as delegator's) signature on the same message. However, the proxy itself cannot produce any signatures on behalf of either Alice or Bob. There exists some unidirectional one-use and multi-use (a message can be re-s...
The energy consumption of cloud servers accounts for about 25% of the total energy of cloud data centers. Reducing and optimizing this energy consumption is thus extremely important in energy saving in cloud data centers. Power model is fundamental in energy efficiency optimization scheduling for cloud computing. However, systems and tools for powe...
![Comparison between our proposed MASE and FHE [13].](profile/Changyu-Dong-2/publication/343355903/figure/tbl1/AS:1120887432581124@1644251797673/Comparison-between-our-proposed-MASE-and-FHE-13_Q320.jpg)
Homomorphic encryption (HE) schemes, such as fully homomorphic encryption (FHE), support a number of useful computations on ciphertext in a broad range of applications, such as e-voting, private information retrieval, cloud security, and privacy protection. While FHE schemes do not require any interaction during computation, the key limitations are...
In this age of freedom of speech, the increasing popularity of various social networking services is accelerating the propagation of crisis information. Many people express their views in an arbitrary way and spread them continuously in the virtual world of social networking since the entrance threshold for these social networking services is low....
Anonymous authentication is one of the most critical tools for the privacy protection in Internet-of-Things (IoT). The primitive of group signature has been widely applied to achieving anonymous authentication. Any mobile device is able to prove its privilege of the access control to a remote server which is an authenticated device with valid attes...
Internet of Things (IoT) has drawn much attention in recent years. However, the image data captured by IoT terminal devices are closely related to users’ personal information, which are sensitive and should be protected. Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support pri...
With the development of smart devices, the Internet of Things (IoT) has found wide applications and extended various services of Internet. On intermediate nodes and edge nodes of the IoT network, the aggregation primitive is a basic function for forwarding data, which takes data sources of other nodes as input. To protect sensitive information of s...
Searchable Encryption (SE) allows mobile devices with limited computing and storage resources to outsource data to an untrusted cloud server. Users are able to search and retrieve the outsourced, however, it suffers from information and privacy leakage. The reason is that most of the previous works rely on the single cloud model, which allows that...
With the advent of cloud computing, data privacy has become one of critical security issues and attracted much attention as more and more mobile devices are relying on the services in cloud. To protect data privacy, users usually encrypt their sensitive data before uploading to cloud servers, which renders the data utilization to be difficult. The...
Leakage of unprotected biometric authentication data has become a high-risk threat for many applications. Lots of researchers are investigating and designing novel authentication schemes to prevent such attacks. However, the biggest challenge is how to protect biometric data while keeping the practical performance of identity verification systems....
Grammatical evolution (GE) is an important automatic programming technique developed on the basis of genetic algorithm and context-free grammar. Making changes with either its chromosome structure or decoding method, we will obtain a great many GE variants such as \(\pi \)GE, model-based GE, etc. In the present paper, we will examine the performanc...
Grammatical evolution (GE) is a combination of genetic algorithm and context-free grammar, evolving programs for given problems by breeding candidate programs in the context of a grammar using genetic operations. As far as the representation is concerned, classical GE as well as most of its existing variants lacks awareness of both syntax and seman...
Identifying network traffics at their early stages accurately is very important for network management and security. Recent years, more and more studies have devoted to find effective machine learning models to identify traffics with few packets at the early stage. In this paper, we try to build an effective early stage traffic identification model...
The critical system is an open control system using distributed computing method and possessing increasing levels of autonomy. Due to openness of the network, the system is vulnerable various attacks. To enhance its security, the mutual authentication among the server, the user and the registration is essential. In last several years, many biometri...
Citations
... The BBO starts from a random population with population size N and dimension D, and each individual H ij is generated according to formula (13). To calculate HSI, sort population individuals H k in order from good to bad, and calculate emigration index μ k and immigrant index λ k according to formula (14). ...
... Among them, maxiterate is the maximum number of iterations. According to formula (11), the initial value of σ is 1, and when k = 1 in the first iteration, the value of ρ obtained by formula (10) is negative. Move in random directions away from the optimal solution, thus enabling a wider search [94]. ...
... Step 4: Add 1 to the number of iterations, and update the step factor according to formula (12). ...
... Anomaly detection, image-based malware detection, cloud-native security, and security automation are the six general categories used in this article to group them. The endeavors in this context have concentrated on utilizing a range of neural network architectures, including CNNs, RNN, and Long Short-Term Memory (LSTM) (Kumar et al. 202a;Rjoub et al. 2021;Zhang et al. 2022;Abou El Houda et al. 2022). Furthermore, the focus has been on assessing the effectiveness of the network traffic analysis system through performance metrics such as F1-score, precision, and accuracy Thilagam and Aruna 2021;Makkar et al. 2021;Landman and Nissim 2021). ...
... However, the method is not applicable to networks with high node mobility, such as imperfect channel estimation due to vehicle movement. Wu et al. [43] used Lagrange multipliers to obtain bandwidth allocation and reinforcement learning to select optimization strategies, so as to solve this limitation. Experiments show that the method has better computational power and lower energy consumption. ...
... However, these studies overlook the pricing aspect of the server and neglect the budget constraints of the users. To address this issue, Zhang et al. [43] introduced a method for offloading tasks from one vehicle to another. They incorporated the budget restriction into the system architecture and then developed a combination technique using Deep Reinforcement Learning (DRL) and convex optimization to tackle the problem. ...
... In recent years, with the advancement of deep learning, it has not only been extensively applied in other fields like natural language processing [11] and recommendation systems [12] but has also achieved significant accomplishments in the computer vision domain. Particularly, in the realm of low-light enhancement methods, deep learning has made remarkable progress, offering powerful solutions to improve image quality and performance in low-light conditions. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/11431281218354899-1705579871076_Q64/Jijie-Yan-2.jpg)
... However, these data involve a large amount of private information, and the leakage of private data will cause serious security problems. Therefore, privacy computing [18][19][20][21] has been widely considered the optimal solution for maintaining data security [22][23][24][25] and protecting privacy [26][27][28][29]. Private intersection-sum (PIS) is one of the most commonly used privacy-preserving protocols in specific scenarios. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/278634221850678-1443442984047_Q64/Jin-Li-13.jpg)
... TDP, measured in Watts (W), indicates the maximum power consumption under theoretical full load. However, this method oversimplifies the relationship between power consumption and utilisation [22], as modern hardware can dynamically adjust the frequency and deactivate entire cores to save energy. A more nuanced approach is based on the hardware's capacitance , voltage , and frequency , as = 1 /2 2 , but obtaining these values for all components is rather challenging. ...
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![[object Object]](https://i1.rgstatic.net/ii/profile.image/1071572022468620-1632494087665_Q64/Fagui-Liu.jpg)
... MAS-Encryption (MASE), to guard the secrecy ofmultiply-add (M-A) classifiers type. They demonstrated the effectiveness of MASE through two case study [47] examples: constructing a privacy preserving Naive Bayes classifier with minimal Bayes risk (MBR-PPNBC) and a privacy-preserving support vector machine classifier (PPSVMC). ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/558498404880386-1510167804256_Q64/Changyu-Dong-2.jpg)
