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10th IEEE Smart World Congress, SWC 2024

作者： Gu, Qiliang Lu, Qin Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan China

ISBN: (纸本)9798331520861

The legal judgement prediction (LJP) of judicial texts represents a multi-label text classification (MLTC) problem, which in turn involves three distinct tasks: the prediction of charges, legal articles, and terms of penalty. Nevertheless, extant multi-label text classification models tend to eschew the consideration of multiple correlations and semantic information between labels when predicting judicial texts, which may result in the loss of pertinent information. Furthermore, these models do not take full advantage of the local and overall information of the labels in the process of selecting appropriate labels for the text using the multi-head attention mechanism. To address these issues, we propose a new model, BGFLFF, which explores label correlation and semantics among the three tasks by employing Graph Convolutional network (GCN) and multi-head attention mechanisms. In particular, we propose a Bi-Graph Fusion GCN (BGF-GCN), which fuses the co-occurrence matrix of labels with the cosine similarity matrix, thereby fully exploiting the multiple correlations between labels. Furthermore, prior to embedding the tags, the interpretations of the labels are obtained via Google in order to enhance the semantic information between the labels. To further reinforce the interconnections between labels and text and more effectively comprehend the interrelationships between the three tasks, we propose a Multi-Head Label Feature Fusion Attentional Mechanism (MH-LFFAtt), which assigns distinct weights to the pertinent label information in the text by fusing the local and overall features of the labels. The experimental results demonstrate that the F1 score exhibits an improvement of up to 2. 2 8 % and a minimum of 1. 2 9 % across the various tasks of the two datasets. This evidence substantiates the assertion that BGFLFF outperforms the existing baseline model. © 2024 IEEE.

关键词： Semantics

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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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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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C-privacy:A social relationship-driven image customization sharing method in cyber-physical networks

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Digital Communications and networks 2025年第2期11卷 563-573页

作者： Dapeng Wu Jian Liu Yangliang Wan Zhigang Yang Ruyan Wang Xinqi Lin School of Communications and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China Aerospace Tianmu Satellite Technology Company Limited Chongqing401332China School of Cyber Security and Information Law Chongqing University of Posts and TelecommunicationsChongqing400065China College of Computer and Cyber Security Fujian Normal UniversityFujian350117China The Advanced Network and Intelligent Connection Technology Key Laboratory Chongqing400065China Key Laboratory of Ubiquitous Sensing and Networking Chongqing400065China

Cyber-Physical networks(CPN)are comprehensive systems that integrate information and physical domains,and are widely used in various fields such as online social networking,smart grids,and the Internet of Vehicles(IoV).With the increasing popularity of digital photography and Internet technology,more and more users are sharing images on ***,many images are shared without any privacy processing,exposing hidden privacy risks and making sensitive content easily accessible to Artificial Intelligence(AI)*** image sharing methods lack fine-grained image sharing policies and cannot protect user *** address this issue,we propose a social relationship-driven privacy customization protection model for publishers and *** construct a heterogeneous social information network centered on social relationships,introduce a user intimacy evaluation method with time decay,and evaluate privacy levels considering user interest *** protect user privacy while maintaining image appreciation,we design a lightweight face-swapping algorithm based on Generative Adversarial network(GAN)to swap faces that need to be *** proposed method minimizes the loss of image utility while satisfying privacy requirements,as shown by extensive theoretical and simulation analyses.

关键词： Cyber-physical networks Customized privacy Face-swapping Heterogeneous information network Deep fakes

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Intermittent Fault Diagnosis of Split-Star networks and its Applications

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IEEE Transactions on Parallel and Distributed Systems 2023年第4期34卷 1253-1264页

作者： Song, Jiankang Lin, Limei Huang, Yanze Hsieh, Sun-Yuan Fujian Normal University College of Computer and Cyber Security Key Laboratory of Network Security and Cryptology Fuzhou Fujian350117 China Fujian University of Technology School of Computer Science and Mathematics Fuzhou Fujian350118 China National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan

With the rapid increase of the number of processors in multiprocessor systems and the fast expansion of interconnection networks, the reliability of interconnection network is facing severe challenges, where the fast recognition of fault processors is crucial. In practice, most of the processor failures are intermittent faults. In this article, we first determine the intermittent fault diagnosability t I PMC(S n 2) tIPMC(Sn2) of n-dimensional split-star network Sn2 under the PMC model. In addition, we propose a fast intermittent fault probabilistic diagnosis algorithm FIFPDPMC to identify the nodes with intermittent fault in the n-dimensional split-star network Sn2 under the PMC model, and we calculated the time complexity of the algorithm FIFPDPMC. Then we implement the algorithm FIFPDPMC in the IoT-based wireless sensor network (IoTWSN) and a randomly generated network (RGN) under different number of nodes with intermittent fault, and we evaluate the performance and efficiency of the algorithm FIFPDPMC in terms of accuracy, precision, recall (TPR), F1, G-mean, FPR, TNR and FNR. Experimental results show that, as the number of stages of executing the algorithm FIFPDPMC increases, the number of nodes with intermittent fault being diagnosed by the algorithm FIFPDPMC increases, which implies that the algorithm FIFPDPMC has good performance and efficiency in both IoTWSN and RGN. © 1990-2012 IEEE.

关键词： Fault detection

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Competitive Swarm Optimizer Based on Individual Learning Mechanism 5

Competitive Swarm Optimizer Based on Individual Learning Mec...

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5th International Conference on High Performance Big Data and Intelligent Systems, HDIS 2023

作者： Tang, JingQi Li, Wei Wang, Lei 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)9798350394160

In view of the disadvantages of the traditional competitive swarm optimizer (CSO), such as falling into local minimization or poor convergence accuracy, this paper proposed an enhanced CSO algorithm called competitive swarm optimizer based on individual learning mechanism (ILCSO). Firstly, the individual selection rate and the learning rate are designed to dynamically select the winner and loser. The losers are updated by the precise competitive learning strategy to improve the algorithm exploitation ability. Secondly, the mutation strategy based on performance improvement is introduced, which improves the search ability of algorithm. The proposed algorithm effectively balances the local search and global exploration with the individual learning mechanism, and improves the probability of finding the global optimal solution. Finally, ILCSO is compared with six classical meta-heuristic algorithms on CEC2014 benchmark functions. The Wilcoxon rank-sum test is used to demonstrate that the ILCSO is effective. Experimental results and statistical analysis show that ILCSO has higher convergence speed and convergence accuracy. ©2023 IEEE.

关键词： Swarm intelligence

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A Trusted Privacy-Preserving Model for Cross-Chain Transactions Based on zk_SNARKs

A Trusted Privacy-Preserving Model for Cross-Chain Transacti...

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2023 International Conference on networking and network Applications, NaNA 2023

作者： Wang, Yichuan Tie, Jianhuan Hei, Xinhong Zhao, Li Zhang, Xiaohui School of Computer Science and Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technolog Xi'an China

ISBN: (纸本)9798350327380

Currently, the privacy protection technology of blockchain is not mature enough, such as user data leakage and lack of anonymity exist, and these problems are especially serious when conducting cross-chain transactions. In this paper, we propose a method of cross-chain transactions based on zk_SNARKs in a trusted environment for cross-chain transactions for privacy protection. Cross-chain transactions are performed through the features of zk_SNARKs such as efficiency, privacy, and verifiability. zk_SNARKs needs to generate trusted settings with the help of a third party during the transaction, and the process has serious privacy issues, and the private parameters generated during the transaction may be maliciously attacked and thus obtained by attackers. To address this problem, we use a hardware technology SGX for trusted computing to encrypt and store some private parameters generated by zk_SNARKs, thus ensuring the security of cross-chain transactions. The experimental results show that the privacy protection scheme using SGX for cross-chain transactions takes less time than the traditional transaction privacy protection, with a verification time of 1.2s for a number of 10 sidechains, and is more efficient than the traditional cross-chain transaction privacy protection. © 2023 IEEE.

关键词： Blockchain

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Petri Net-Based Attack Modeling for Industrial Control System networks 3rd

Petri Net-Based Attack Modeling for Industrial Control Syste...

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3rd China Intelligent Robotics Annual Conference, CCF CIRAC 2022

作者： Wang, Yichuan Lv, Zhaoqi Zhang, Yaling Xiao, Yeqiu Hei, Xinhong 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)9789819903009

Industrial control systems have been deeply involved in industrial facilities and infrastructure. With the integrated development of industry and information technology, industrial control systems are tied to the Internet and may be threatened by cyber attacks. Modeling analysis and security evaluation are significant to guarantee industrial control system security. For in-depth research of security in the industrial control network, we first provide a cyber attack strategy for programmable logic controllers with respect to critical nodes in industrial control systems. Then, we explore and validate the viability of attacks based on the proposed strategy through simulations and visualization. Finally, Petri net modeling is utilized to depict both cyber attacks and defensive techniques. The results in this paper demonstrate that the proposed attack strategy gives new ideas for us to investigate industrial control cyber assaults, while the modeling and analytic methodologies in this paper are also useful for system weaknesses analysis. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： network security

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A Positive Influence Maximization Algorithm in Signed Social networks

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computers, Materials & Continua 2023年第8期76卷 1977-1994页

作者： Wenlong Zhu Yang Huang Shuangshuang Yang Yu Miao Chongyuan Peng College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar161006China College of Teacher Education Qiqihar UniversityQiqihar161006China

The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social *** positive influence maximization(PIM)problem is an extension of the IM problem,which consider the polar relation of nodes in signed social networks so that the positive influence of seeds can be the most widely *** solve the PIM problem,this paper proposes the polar and decay related independent cascade(IC-PD)model to simulate the influence propagation of nodes and the decay of information during the influence propagation in signed social *** overcome the low efficiency of the greedy based algorithm,this paper defines the polar reverse reachable(PRR)set and devises a signed reverse influence sampling(SRIS)*** algorithm utilizes the ICPD model as well as the PRR set to select *** are two phases in *** is the sampling phase,which utilizes the IC-PD model to generate the PRR set and a binary search algorithm to calculate the number of needed PRR *** other is the node selection phase,which uses a greedy coverage algorithm to select optimal ***,Experiments on three real-world polar social network datasets demonstrate that SRIS outperforms the baseline algorithms in *** on the Slashdot dataset,SRIS achieves 24.7% higher performance than the best-performing compared algorithm under the weighted cascade model when the seed set size is 25.

关键词： Positive influencemaximization polar relation information decay reverse influence sampling

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