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A Driving Risk Prediction Approach Based on Generative Adversarial networks and VANET for Autonomous Trams

A Driving Risk Prediction Approach Based on Generative Adver...

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2021 International Conference on networking and network Applications, NaNA 2021

作者： Ji, Wenjiang Yang, Jiangcheng Wang, Yichuan Zhu, Lei Qiu, Yuan Hei, Xinhong College of Computer Science and Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Shaanxi Key Laboratory for Net work Computing and Security T echnology Xi'an China

ISBN: (纸本)9781665441582

Driving safety is an essential prerequisite to the rapid development of autonomous trams. However, the relationship of driving risk factors is nonlinear, which makes modeling difficult. To improve the accuracy of driving risk prediction, a data driven approach based on Generative Adversarial networks was proposed. First of all, a communication and alarming scenario of Vehicular Ad-hoc networks was demonstrated, in which the original data sets can be collected and transmitted by the help of sensors and Road Side Units. Then the RFE feature selection algorithm was used to keep the key features. To deal the sample asymmetry problem, a DCGAN model was designed for sparse samples expansion. At last, the XGBoost algorithm was used to classification and output the risk prediction result. During the experiment implemented with the public and real data sets, the risk prediction accuracy of proposed approach can up to 97.24%, for which takes the advantages in generating of the sparse samples. © 2021 IEEE.

关键词： Generative adversarial networks

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Numerical Calculation of Partial Differential Equation Deduction in Adaptive Total Variation Image Denoising 12

Numerical Calculation of Partial Differential Equation Deduc...

引用

12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

作者： Zhao, Minghua Wang, Qin Muniru, Abdul Nasir Ning, Jiawei Li, Peng Li, Bing School of computer science and engineering Xi'an University of Technology Xi'an Shaanxi China Shaanxi Key Laboratory of Network Computing and Security Technology Xi'an Shaanxi China

ISBN: (纸本)9781728148526

Total variation model of image denoising is easy to influence the gradient and lose the details of image. Due to these weaknesses, many adaptive total variation (ATV) models of image denoising have been proposed to eliminate the Gaussian noisy additive in the image. This paper implements the model through a numerical solution, where the gradient descent method is used to derive the partial differential equation (PDE) corresponding to the ATV model. First, based on Euler-Lagrange equation, a detailed derivation process for Partial Differential Equation is used to calculate the ATV model. Then, based on gradient descent method, a numerical calculation of the model is derived from the PDE using the Direct Difference Method. Finally, several different λ parameters are compared to produce different image denoising effects and the appropriate parameter λ value is determined. Experimental results prove that our proposed numerical calculation can effectively realize the ATV denoising model. © 2019 IEEE.

关键词： Partial differential equations

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Petri net modeling and vulnerability analysis of the Heartbleed

Petri net modeling and vulnerability analysis of the Heartbl...

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2021 International Conference on networking and network Applications, NaNA 2021

作者： Wang, Yichuan Wang, He Hei, Xinhong Ji, Wenjiang Zhu, Lei Xi'an University of technology School of computer science and engineering Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology China

ISBN: (纸本)9781665441582

In recent years, a variety of network attacks emerge in an endless stream, and network attacks gradually show the characteristics of higher secrecy and greater harm. At present, the analysis of system vulnerabilities is generally focused on the characteristics analysis and impact hazard level, and lack of formal modeling and vulnerability analysis methods. In this paper, we model the OpenSSL service's Heartbleed vulnerability based on Petri net. We build a formal model combined with the source code and system state, analyze the vulnerability of the system running state, and propose an automatic vulnerability repair scheme. Experiments show that this model can carry out fine-grained formal analysis and simulation of the Heartbleed, which is of great significance to explore the system vulnerability modeling method. © 2021 IEEE.

关键词： Petri nets

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A Pseudonym Exchange-Based Traceable Location Privacy Protection Scheme for IoV

A Pseudonym Exchange-Based Traceable Location Privacy Protec...

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2023 International Conference on networking and network Applications, NaNA 2023

作者： Ma, Weigang Yu, Yaping Wang, Yichuan Liu, Xiaoxue Wang, Zhoukai School of Computer Science and Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology China

ISBN: (纸本)9798350327380

Internet of Vehicles (IoV) is a network built by communicating entities such as vehicles and roadside infrastructure, etc. The entities can communicate with each other, sharing data and providing services. However, the openness and interoperability (location services) of IoV makes the communication entity vulnerable to attacks. when the vehicle requests location services, it will expose its own location information, which will cause serious personal safety problems. To address the location privacy leakage problem in the IoV, this paper proposes a pseudonym exchange-based traceable location privacy protection scheme for IoV. Our scheme not only provides location privacy protection, but has the following properties: First, the whole pseudonym exchange process does not require trusted third-party participation;Second, each vehicle performs a series of hash operations on several dynamic anonyms and obtains a corresponding fixed-length hash value as the corresponding account in order to cut off the connection between the real identity, which is different in each run. If a vehicle is compromised and utilized to launch attack, the trusted center (CA) can also recover his/her real identity;Last, the experimental results show that the pseudonym exchange process and pseudonym update process cost less time compared to relevant literature. Hence, these features make our scheme very suitable for computation-limited mobile devices compared with other related existing schemes. © 2023 IEEE.

关键词： Vehicles

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DDoS Attack Detection Based on Information Entropy Feature Extraction in Software Defined networks

DDoS Attack Detection Based on Information Entropy Feature E...

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2023 International Conference on networking and network Applications, NaNA 2023

作者： Ji, Wenjiang Yang, Yixin Zhang, Yaling Wang, Yichuan Tian, Mengjie Qiu, Yuan Xi'an University of Technology School of Computer Science and Engineering Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology China

ISBN: (纸本)9798350327380

Distributed Denial of Service(DDoS) attacks target the forwarding-control separation feature of Software-Defined networking(SDN) to launch attacks, causing network disruptions. Therefore security against DDoS attack detection for SDN controllers is the focus of current research. This paper proposes an Extreme Gradient Boosting (XGBoost) DDoS attack detection algorithm based on a combination of information gain and recursive feature elimination algorithms. We evaluated the performance of the method using the CICDDoS2019 dataset. This method works well in multi-classification model for attack detection with an accuracy of 93.41%. © 2023 IEEE.

关键词： Software defined networking

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WebIDE cloud server resource allocation with task pre-scheduling in IOT application development 2

WebIDE cloud server resource allocation with task pre-schedu...

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2nd IEEE International Conference on Industrial Internet Cloud, ICII 2019

作者： Wang, Huaijun Li, Junhuai Tian, Jubo Wang, Kan Shaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and Engineering Xian University of Technology Xian710048 China

ISBN: (纸本)9781728129778

WebIDE is leveraged for IOT applications development, which could adapt to the rapid growth of IOT applications and meanwhile facilitate the rapid development. Resource allocation is of vital significance in the WebIDE cloud service system. Existing resource allocation approaches may encounter issues such as unbalanced resource assignments, which could lead to the reduced system resource utilization or extended system response time. The fundamental reason behind it lies in the fact that existing ones are typically on the basis of predetermined resource demands for each task, and not applicable to the case with dynamic and unknown resource demands. Thus, in this paper, we propose a novel approach based on task pre-scheduling, which schedules beforehand each task into a virtual machine local task queue by means of demand prediction. Firstly, all tasks are classified, based on the execution state, execution operations and cloud server resource requirements. Secondly, the grouped tasks are mapped to different system states, with the Markov state transition probability matrix leveraged to model the transition probability between tasks, followed by the prediction model constructed. Finally, integrating both task pre-scheduling and ant colony algorithm, cloud server resource allocation is carried out. Simulation results show that the task prediction model could significantly not only reduce the task response time, but also improve the cloud server resource utilization. © 2019 IEEE.

关键词： Resource allocation

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TCS security Analysis in Intel SGX Enclave MultiThreading

TCS Security Analysis in Intel SGX Enclave MultiThreading

引用

2022 International Conference on networking and network Applications, NaNA 2022

作者： Zhang, Tong Cui, Xiangjie Wang, Yichuan Du, Yanning Gao, Wen School of Computer Science and Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

With the rapid development of Internet technology in recent years, the demand for security support for complex applications is becoming stronger and stronger. Intel Software Guard Extensions (Intel SGX) is created as an extension of Intel Systems to enhance software security. Intel SGX allows application developers to create so-called enclave. Sensitive application code and data are encapsulated in Trusted Execution Environment (TEE) by enclave. TEE is completely isolated from other applications, operating systems, and administrative programs. Enclave is the core structure of Intel SGX technology. Enclave supports multi-threading. Thread Control Structure (TCS) stores special information for restoring enclave threads when entering or exiting enclave. Each execution thread in enclave is associated with a TCS. This paper analyzes and verifies the possible security risks of enclave under concurrent conditions. It is found that in the case of multithread concurrency, a single enclave cannot resist flooding attacks, and related threads also throw TCS exception codes. © 2022 IEEE.

关键词： Floods

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A Novel On-Demand Service Architecture for Efficient Cloud-Edge Collaboration

A Novel On-Demand Service Architecture for Efficient Cloud-E...

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2023 International Conference on networking and network Applications, NaNA 2023

作者： Zhang, Yaling Chen, Jingjing Wang, Yichuan Xiao, Yeqiu Liu, Xiaoxue School of Computer Science and Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology China

ISBN: (纸本)9798350327380

With the advent of 5G era, the model of cloud-edge collaboration is used to handle massive data computing tasks with significant superiority. However, this architecture still uses the traditional web service model, which has problems such as single service and low resource utilization during the interaction between users and remote web servers. In this paper, we propose a novel on-demand service architecture that changes the traditional inefficient network service approach and skews the entire network service to the user. By fine- grained division of users' demands and hosting them in the corresponding functional servers for processing, the resolution of users' demands is no longer restricted by the services provided by the server, thus realizing 'information to people and services on demand'. Experiments show that the new on- demand service architecture reduces the latency by 33.3%, improves the quality and efficiency of information services, and realizes a more proactive and flexible information service model, which is more suitable for users' needs. © 2023 IEEE.

关键词： Information services

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Deep Reinforcement-Learning-Based Adaptive Traffic Signal Control with Real-Time Queue Lengths

Deep Reinforcement-Learning-Based Adaptive Traffic Signal Co...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Sun, Qi-Wei Han, Shi-Yuan Zhou, Jin Chen, Yue-Hui Yao, Kang University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China Shandong Provincial Network Security and Infomationization Technology Center Jinan250002 China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

The reinforcement learning (RL) with deep neural network, as a data-driven approach, is promising for adaptive traffic signal control (ATSC) in traffic scenarios. The majority of the existing studies focus on designing efficient agents and policy optimization for ATSC, but neglect to observe more detailed states of the environment. In this paper, an adaptive traffic signal control strategy, named as A2C RTQL, is proposed for scheduling the traffic signal in an intersection, by combining the real-time lane-based queue lengths with deep RL agent. First, the Lighthill-Whitham-Richards (LWR) shockwave theory is employed for obtaining the real-time queue lengths in each lane. After that, by defining the obtained queue lengths as the inputs, A2C RTQL strategy is designed for traffic signal control based on the advanced actor-critic (A2C) agent, where the lanes are divided into multiple parallel environments based on the phases of traffic signal. Simulation results demonstrate the optimality and efficiency of the proposed strategy compared with other methods in SUMO under simulated peak-hour traffic dynamics. © 2022 IEEE.

关键词： Reinforcement learning

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A Technique for Ensured Cross Chain IBC Transactions Using TPM 2

A Technique for Ensured Cross Chain IBC Transactions Using T...

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2nd International Conference on Big Data and Privacy computing, BDPC 2024

作者： Wang, YiChuan Yan, YiLiang Liu, XiaoXue Gao, Wen Wang, ZiYan School of Computer Science and Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China

ISBN: (纸本)9798350307597

Cross chain contact across several blockchains becomes increasingly significant in importance with the increased use of blockchain technology. However, security cannot be assured when producing equivalent outputs through cross-chain transmission because it is simple to launch an assault, and without security measures;it is simple to cause the transmission material to be stolen. This article combines TPM, IBC, and associates encryption and decryption techniques for protection to overcome this issue. We have establishes the viability and efficacy of the suggested method through testing and performance analyses. The experimental findings show that our approach can successfully preserve privacy and guarantee the security of data transfer. © 2024 IEEE.

关键词： Blockchain

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