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Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial network

Computer Systems Science & Engineering 2021年第12期39卷 373-390页

作者： Jiaming Mao Mingming Zhang Mu Chen Lu Chen Fei Xia Lei Fan ZiXuan Wang Wenbing Zhao State Grid Jiangsu Electric Power Co. Ltd.Information and Telecommunication BranchNanJing210003China Institute of Information and Communication Global Energy Interconnection Research InstituteState Grid Key Laboratory of Information and Network SecurityNanjing210003China Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Research and Development Center of Post Industry Technology of the State Posts Bureau(Internet of Things Technology)Broadband Wireless Communication Technology Engineering Research Center of the Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing210003China Department of Electrical Engineering and Computer Science Cleveland State UniversityCleveland44115USA

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased net-work traffic *** the past few decades,network traffic identification has been a research hotspot in the field of network management and security ***,as more network services use encryption technology,network traffic identification faces many *** classic machine learning methods can solve many problems that cannot be solved by port-and payload-based methods,manually extract features that are frequently updated is time-consuming and *** learning has good automatic feature learning capabilities and is an ideal method for network traffic identification,particularly encrypted traffic identification;Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled ***,in real scenarios,labeled samples are often difficult to *** paper adjusts the structure of the auxiliary classification generation adversarial network(ACGAN)so that it can use unlabeled samples for training,and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised *** results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network(CNN)based classifier.

关键词： Encrypted traffic recognition deep learning generative adversarial network traffic classification semisupervised learning

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Wireless powered Backscatter Communications with Spatially Random Tags

Wireless Powered Backscatter Communications with Spatially R...

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IEEE International Conference on Communications in China (ICCC)

作者： Yingting Liu Yinghui Ye Xingwang Li Zhongyu Ma Zhiyang Zhou School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou China State Grid Gansu Electric Power Research Institute Lanzhou China School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing China Shaanxi Key Laboratory of Information Communication Network and Security Xi’an University of Posts & Telecommunications Xi’an China School of Physics and Electronic Information Engineering Henan Polytechnic University Jiaozuo China College of Computer Science and Engineering Northwest Normal University Lanzhou China

In this paper, a wireless powered backscatter communication (BackCom) system is considered, which consists of one dedicated radio-frequency source node (S), one destination node and multiple tags randomly located in the coverage region of S. The consumed power by tags is considered and an optimal dynamic reflection coefficient (RC) is used to maximize the power of the backscattered signals while just satisfying the tag’s power requirement. The random tag selection (RTS) and nearest tag selection (NTS) schemes are proposed and the corresponding outage probabilities and diversity orders are derived. Numerical results verify the theoretical analysis and show that the NTS scheme has the best performance compared to the RTS and farthest tag selection schemes. Moreover, numerical results also show that the performance of the adopted optimal dynamic RC is superior to that of the fixed RC.

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AsyncSC: An Asynchronous Sidechain for Multi-Domain Data Exchange in Internet of Things

arXiv

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arXiv 2024年

作者： Yang, Lingxiao Dong, Xuewen Wan, Zhiguo Gao, Sheng Tong, Wei Lu, Di Shen, Yulong Du, Xiaojiang The School of Computer Science and Technology Xidian University The Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education China The Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'An710071 China The Zhejiang Lab Hangzhou311121 China The School of Information Central University of Finance and Economics Beijing100081 China The School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China The School of Computer Science and Technology Xidian University China The Shaanxi Key Laboratory of Network and System Security Xi'An710071 China The School of Engineering and Science Stevens Institute of Technology Hoboken07030 United States

Sidechain techniques improve blockchain scalability and interoperability, providing decentralized exchange and cross-chain collaboration solutions for Internet of Things (IoT) data across various domains. However, current state-of-the-art (SOTA) schemes for IoT multi-domain data exchange are constrained by the need for synchronous networks, hindering efficient cross-chain interactions in discontinuous networks and leading to suboptimal data exchange. In this paper, we propose AsyncSC, a novel asynchronous sidechain construction. It employs a committee to provide Cross-Blockchain as a Service (C-BaaS) for data exchange in multi-domain IoT. To fulfill the need for asynchronous and efficient data exchange, we combine the ideas of aggregate signatures and verifiable delay functions to devise a novel cryptographic primitive called delayed aggregate signature (DAS), which constructs asynchronous cross-chain proofs (ACPs) that ensure the security of cross-chain interactions. To ensure the consistency of asynchronous transactions, we propose a multilevel buffered transaction pool that guarantees the transaction sequencing. We analyze and prove the security of AsyncSC, simulate an asynchronous communication environment, and conduct a comprehensive evaluation. The results show that AsyncSC outperforms SOTA schemes, improving throughput by an average of 1.21 to 3.96 times, reducing transaction latency by 59.76% to 83.61%, and maintaining comparable resource overhead. Copyright © 2024, The Authors. All rights reserved.

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LoCoCa: Location-Context-Capacity Aware Cost Economizing in Edge-Cloud Systems

LoCoCa: Location-Context-Capacity Aware Cost Economizing in ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yuanze Li Chao Qiu Xiaofei Wang Cheng Zhang Wenyu Wang Shizhan Lan Jing Jiang College of Intelligence and Computing Tianjin University Tianjin China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen China Institute of Technology Tianjin University of Finance and Economics Tianjin China Shanghai Zhuichu Networking Technologies Co. Ltd. China China Mobile Guangxi institute Co Ltd Guangxi China Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and Telecommunications Xi'an China

Nowadays, real-time interactive content services have been the most dazzling sector of next-generation Internet. The high-quality perceptions of virtual scenes have given rise to the strict requirements of high bandwidth and low latency, where the edge-cloud system promises several benefits. However, there still remain prominent challenges, when taking the economical efficiency into consideration, including location-heterogeneity, context-directability, and capacity-exploitation. In this paper, we propose a location-context-capacity aware bandwidth cost economizing strategy in the edge-cloud system, i.e., LoCoCa. LoCoCa adopts server pools partition mechanism, then achieving the optimal burstable billing in each pool. Here, a location-aware graph construction and partition algorithm is designed to solve the server pools partition problem. Then an improved burstable billing optimization mechanism, with a context index and an adaptive bandwidth capacity, is also proposed to economize bandwidth costs. Finally, the realistic edge-cloud company's trace-based experimental results verify LoCoCa reduces bandwidth costs by 81.83 %, compared with the baselines.

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security risk analysis of on-site terminal of marketing specialty in power industry under the environment of internet of things 12

Security risk analysis of on-site terminal of marketing spec...

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12th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

作者： Yang, Ruxia Gao, Peng Gao, Xianzhou Fang, Zhou Global Energy Interconnection Research Institute State Grid Key Laboratory of Information and Network Security Nanjing China State Grid Zhejiang Electric Power Co. Ltd. Zhejiang China

ISBN: (纸本)9781728170817

Due to the weak protection of the field terminal equipment and the uncontrollable environment, once it is illegally used, it will directly affect the overall security protection system of the State Grid Corporation. The security threat is extremely huge. It is necessary to analyze and identify the safety risks of the field professional terminal in the power industry and make countermeasures. This paper investigates the status quo of on-site terminal security protection in the power industry marketing industry, analyzes the existing security risks, and further analyzes the security risks of the power industry marketing professional field terminal under the Internet of Things environment. And put forward relevant suggestions on the problems existing at the current stage. © 2020 IEEE.

关键词： Internet of things

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Trust and Risk Based on Access Control Model in Social Internet of Things

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International Journal of network security 2023年第5期25卷 736-744页

作者： Zhang, Hongbin Liu, Jian Zhao, Dongmei Liu, Bin Wang, Yanmei Fan, Fan School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang050000 China Hebei Key Laboratory of Network and Information Security Hebei Normal University Shijiazhuang050024 China School of Economics and Management Hebei University of Science and Technology Shijiazhuang050000 China Research Center of Big Data and Social Computing Hebei University of Scienc and Technology Shijiazhuang050000 China Hebei Geological Worker’s University Shijiazhuang050000 China

Integrating social networks and the Internet of Things has formed an emerging field of Social Internet of Things (IoT). Aiming to address the shortcomings of traditional TBAC (Trust based on Access Control) and ABAC (Attribute based on Access Control) in dynamic authorization and security, this paper proposes a hybrid access control model based on trust and risk for SIoT. The model supports social relationship-based trust assessment and risk prediction between SIoT nodes and integrates trust and risk values into SIoT security values through reasonable weight allocation. Furthermore, by simulating the safety requirements of different scenarios, it was verified that the model was efficient and more secure than the current models. © (2023). All Rights Reserved.

关键词： Authorization

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Dimensionality Reduction of Massive I/O Log Data Flow in power System

Dimensionality Reduction of Massive I/O Log Data Flow in Pow...

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2020 International Conference on Communications, information System and Computer Engineering, CISCE 2020

作者： Zhang, Bo Xi, Zesheng Zhang, Tao Ma, Yuanyuan Shao, Zhipeng Li, Hongfa Global Energy Interconnection Research Institute Institute of Information and Communication Nanjing China State Grid Key Laboratory of Information and Network Security Nanjing Jiangsu China State Grid Fujian Electric Power Co. Ltd Information Telecommunication Branch China

ISBN: (纸本)9781728197616

Every day, the power system receives massive I/O logs. The amount of data in these logs is so large that it takes huge computational resources to analyze. Therefore, it is necessary to reduce the size of the massive I/O logs and only analyze the key log data, thereby reducing the workload of invalid analysis. This paper takes the I/O log of the substation as the research object, and studies the dimension reduction method of the massive I/O data flow log, which reduces the computational load brought by the high-dimensional I/O data flow log data and reduces the massive I/O data flow log. This paper proposes a method of secondary dimensionality reduction. Firstly, the high dimensional I/O log data stream is classified, so that the data is transformed from high-dimensional to low-dimensional. Then, the dimension is reduced again in each category, so that the most simplified massive I/O logs are achieved. Through theoretical analysis, we can come to the conclusion that the computational time complexity of the data after dimension reduction is reduced by more than 80%. © 2020 IEEE.

关键词： Data reduction

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Internet of Things Terminal Access security Based on Zero Trust

Internet of Things Terminal Access Security Based on Zero Tr...

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International Symposium on Computer Science and Intelligent Controls (ISCSIC)

作者： RiXuan Qiu JunFeng Zhang Lu Chen Wei Li Nan Lin State Grid Jiangxi Electric Power Co. Ltd. Information & Telcommunication Branch Nanjing China Grid Digitizing Technology Department State Grid Key Laboratory of Information & Network Security State Grid Smart Grid Research Institute Co. Ltd Nanjing China State Grid Jiangxi Electric Power Co. Ltd Nanjing China

At present, production and daily life increasingly rely on the Internet of Things, and the network security problem of the Internet of Things is becoming increasingly prominent. Therefore, it is extremely important to ensure the network security of the Internet of Things through various technical means. The security of IoT terminal access behavior is an important part of IoT network security, so it is an important research object in the field of network security. In order to increase the security of IoT terminal access, a security evaluation model based on zero trust is proposed. After the simulation performance test of the model, it is found that the model shows excellent detection ability of malicious access behavior and system stability in different network environments. Under the premise that some network nodes are infected, the model proposed in the study still shows a significantly higher ratio of trusted nodes than other algorithms, The research results show that the model can improve the security level of the Internet of Things network to a certain extent.

关键词： Computational modeling Production network security Predictive models Stability analysis Behavioral sciences Zero Trust

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The Privacy Data Protection Model Based on Random Projection Technology 2nd

The Privacy Data Protection Model Based on Random Projection...

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2nd International Conference on Big Data and security, ICBDS 2020

作者： Shen, Wen Guo, Qian Zhu, Hui Tang, Kejian Zhan, Shaohui Hao, Zhiguo Global Energy Interconnection Research Institute Co. Ltd. Nanjing210003 China State Grid Key Laboratory of Information & Network Security Nanjing210003 China State Grid Financial Technology Group Xiongan071000 China State Grid Jiangxi Electric Power Co. Ltd. Nanchang330000 China Xingtai Huancheng Power Supply Branch of State Grid Hebei Electric Power Co. Ltd. Xingtai054000 China

ISBN: (纸本)9789811631498

In general, as the technology developed, big data analysis provides opportunities to reduce the implementation time and budget. Compared with traditional methods, big data analysis has a greater advantage. It seeks to establish a privacy framework consistent with the factors and measures of mutual understanding in the context of random projection technology. Privacy concerns and perceived benefits have proven to greatly influence personal data protection. The success of stochastic projection techniques depends on voter privacy and personal data protection needs being met. It explores independent component analysis as a possible tool for breaking privacy with deterministic multiplicative perturbation-based models, for example: random orthogonal transformations and random rotations. An approach based on approximate random projection is then proposed that improves privacy protection while maintaining certain date statistical characteristics. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Data privacy

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Robust Imagined Speech Production from Electrocorticography with Adaptive Frequency Enhancement

Robust Imagined Speech Production from Electrocorticography ...

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International Joint Conference on Neural networks (IJCNN)

作者： Xu Xu Chong Fu Junxin Chen Gwanggil Jeon David Camacho School of Computer Science and Engineering Northeastern University Shenyang China School of Software Dalian University of Technology Dalian China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang China Engineering Research Center of Security Technology of Complex Network System Ministry of Education Shenyang China College of Information Technology Incheon National University Incheon Korea Department of Computer Systems Engineering Universidad Politécnica de Madrid Madrid Spain

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Imagined speech production with electrocorticography (ECoG) plays a crucial role in brain-computer interface system. A challenging issue is the great variation underlying the frequency bands of the ECoG signals’ encode information, which makes current methods difficult to generate imagined speech with stable quality among different persons. To this end, we propose a robust model to generate high-quality imagined speech from ECoG. A frequency enhancement branch is first designed to adaptively modulate the frequency information, whose product is fed into the following multi-scale channel attention module for robust feature extraction and fusion. By incorporating both the mel-spectrum and audio as training constraints, a multi-constraint decoder branch is finally constructed for imagined speech production. The performance of our model is evaluated on a high-quality dateset, i.e, Single Word Production Dutch-iBIDS. It yields Pearson correlation scores that are all above 0.8, and the standard deviationsare are all below 0.2 in different volunteers. Experimental results demonstrate that our model is effective and robust for ECoG based imagined speech production, and has advantages over peer methods.

关键词： Training Adaptation models Frequency modulation Correlation Neuroscience Production Speech enhancement

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