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Unknown Application Layer Protocol Recognition Method Based on Deep Clustering

China Communications 2024年第12期21卷 275-296页

作者： Wu Jisheng Hong Zheng Ma Tiantian Si Jianpeng Institute of Command and Control Engineering Army Engineering University of PLANanjing 210007China

In recent years,many unknown protocols are constantly emerging,and they bring severe challenges to network security and network *** unknown protocol recognition methods suffer from weak feature extraction ability,and they cannot mine the discriminating features of the protocol data *** address the issue,we propose an unknown application layer protocol recognition method based on deep *** clustering which consists of the deep neural network and the clustering algorithm can automatically extract the features of the input and cluster the data based on the extracted *** with the traditional clustering methods,deep clustering boasts of higher clustering *** proposed method utilizes network-in-network(NIN),channel attention,spatial attention and Bidirectional Long Short-term memory(BLSTM)to construct an autoencoder to extract the spatial-temporal features of the protocol data,and utilizes the unsupervised clustering algorithm to recognize the unknown protocols based on the *** method firstly extracts the application layer protocol data from the network traffic and transforms the data into one-dimensional ***,the autoencoder is pretrained,and the protocol data is compressed into low dimensional latent space by the autoencoder and the initial clustering is performed with ***,the clustering loss is calculated and the classification model is optimized according to the clustering *** classification results can be obtained when the classification model is *** with the existing unknown protocol recognition methods,the proposed method utilizes deep clustering to cluster the unknown protocols,and it can mine the key features of the protocol data and recognize the unknown protocols *** results show that the proposed method can effectively recognize the unknown protocols,and its performance is better than other methods.

关键词： attention mechanism clustering loss deep clustering network traffic unknown protocol recognition

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Adaptive dynamic reconfiguration mechanism of unmanned swarm topology based on an evolutionary game

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Journal of Systems engineering and Electronics 2023年第3期34卷 598-614页

作者： YU Minggang NIU Yanjie LIU Xueda ZHANG Dongge ZHENG Peng HE Ming LUO Ling Institute of Command and Control Engineering Army Engineering University of the PLANanjing 210007China Institute of Communication Engineering Army Engineering University of the PLANanjing 210007China

Autonomous cooperation of unmanned swarms is the research focus on“new combat forces”and“disruptive technologies”in military *** mechanism design is the fundamental way to realize autonomous *** the realistic requirements of a swarm network dynamic adjustment under the background of high dynamics and strong confrontation and aiming at the optimization of the coordination level,an adaptive dynamic reconfiguration mechanism of unmanned swarm topology based on an evolutionary game is *** paper analyzes military requirements and proposes the basic framework of autonomous cooperation of unmanned swarms,including the emergence of swarm intelligence,information network construction and collaborative mechanism ***,based on the framework,the adaptive dynamic reconfiguration mechanism is discussed in detail from two aspects:topology dynamics and strategy ***,the unmanned swarms’community network is designed,and the network characteristics are ***,the mechanism characteristics are analyzed by numerical simulation,focusing on the impact of key parameters,such as cost,benefit coefficient and adjustment rate on the level of swarm ***,the conclusion is made,which is expected to provide a theoretical reference and decision support for cooperative mode design and combat effectiveness generation of unmanned swarm operations.

关键词： unmanned swarm operation autonomous collaboration topology reconstruction evolutionary game

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Satellite Navigation Method Based on High-Speed Frequency Hopping Signal

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China Communications 2023年第7期20卷 321-337页

作者： En Yuan Peng Liu Weiwei Chen Rui Wang Bing Xu Wenyu Zhang Yanqin Tang Command&Control Engineering College Army Engineering University of PLANanjing 210007China

Global navigation satellite system has been widely used,but it is vulnerable to *** military satellite communications,frequency hopping(FH)signal is usually used for anti-jamming *** the FH signal can be used in satellite navigation,the anti-jamming ability of satellite navigation can be *** a recently proposed timefrequency matrix ranging method(TFMR)can use FH signals to realize pseudorange measurement,it cannot transmit navigation messages using the ranging signal which is crucial for satellite *** this article,we propose dual-tone binary frequency shift keyingbased TFMR(DBFSK-TFMR).DBFSK-TFMR designs an extended time-frequency matrix(ETFM)and its generation algorithm,which can use the frequency differences in different dual-tone signals in ETFM to modulate data and eliminate the negative impact of data modulation on pseudorange *** ETFM,DBFSK-TFMR not only realizes the navigation message transmission but also ensures the precision and unambiguous measurement range of pseudorange ***-TFMR can be used as an integrated solution for anti-jamming communication and navigation based on FH *** results show that DBFSK-TFMR has almost the same ranging performance as TFMR.

关键词： satellite navigation frequency hopping ranging navigation message transmission

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planning,monitoring and replanning techniques for handling abnormity in HTN-based planning and execution

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Journal of Systems engineering and Electronics 2024年第5期35卷 1264-1275页

作者： KANG Kai CHENG Kai SHAO Tianhao ZHANG Hongjun ZHANG Ke Command and Control Engineering College Army Engineering University of PLANanjing 210000China The 63rd Research Institute of National University of Defense Technology Nanjing 210000China

A framework that integrates planning,monitoring and replanning techniques is *** can devise the best solution based on the current state according to specific objectives and properly deal with the influence of abnormity on the plan *** framework consists of three parts:the hierarchical task network(HTN)planner based on Monte Carlo tree search(MCTS),hybrid plan monitoring based on forward and backward and norm-based replanning method *** HTN planner based on MCTS selects the optimal method for HTN compound task through *** on specific objectives,it can identify the best solution to the current *** hybrid plan monitoring has the capability to detect the influence of abnormity on the effect of an executed action and the premise of an unexecuted action,thus trigger the *** norm-based replanning selection method can measure the difference between the expected state and the actual state,and then select the best replanning *** experimental results reveal that our method can effectively deal with the influence of abnormity on the implementation of the plan and achieve the target task in an optimal way.

关键词： hierarchical task network Monte carlo tree search(MCTS) planning execution abnormity

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Dual Attribute Adversarial Camouflage toward camouflaged object detection

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Defence Technology（防务技术） 2023年第4期22卷 166-175页

作者： Yang Wang Zheng Fang Yun-fei Zheng Zhen Yang Wen Tong Tie-yong Cao Institute of Command and Control Engineering Peoples Liberation Army Engineering UniversityNanjing210007China The Army Artillery and Defense Academy of PLA Nanjing210007China PLA University of Foreign Language Luoyang471000China

The object detectors can precisely detect the camouflaged object beyond human *** investigations reveal that the CNNs-based(Convolution Neural Networks)detectors are vulnerable to adversarial *** works can fool detectors by crafting the adversarial camouflage attached to the object,leading to wrong *** is hard for military operations to utilize the existing adversarial camouflage due to its conspicuous *** by this,this paper proposes the Dual Attribute Adversarial Camouflage(DAAC)for evading the detection by both detectors and *** DAAC includes two steps:(1)Extracting features from a specific type of scene to generate individual soldier digital camouflage;(2)Attaching the adversarial patch with scene features constraint to the individual soldier digital camouflage to generate the adversarial attribute of *** visual effects of the individual soldier digital camouflage and the adversarial patch will be improved after integrating with the scene *** results show that objects camouflaged by DAAC are well integrated with background and achieve visual concealment while remaining effective in fooling object detectors,thus evading the detections by both detectors and humans in the digital *** work can serve as the reference for crafting the adversarial camouflage in the physical world.

关键词： Adversarial camouflage Digital camouflage generation Visual concealment Object detection Adversarial patch

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A UAV Target State Estimation Method by Fusing Game Reasoning to Eliminate Negative Particles 3rd

A UAV Target State Estimation Method by Fusing Game Reasonin...

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3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Han, Wei Yang, Guang Luo, Ling Dong, Jingwei Xu, Peng Sun, Xuefei Command and Control Engineering College Army Engineering University of PLA Nanjing210007 China

ISBN: (纸本)9789819624676

Aiming at Unmanned Aerial Vehicle (UAV) target state estimation, a dynamic space model between the electro-optical platform and the target is established, and a target state estimation method by fusing game reasoning is proposed. The payoff matrix is defined according to the game concept. Then, the proposed density distribution function of particle swarm is established, and the particle filter method is improved by fusing the game reasoning. The state of the moving target can be accurately estimated by the retained effective particles. Through simulation experiments, the validity of state estimation results of moving target under different moving trajectories is analyzed and verified. The research in this paper can meet the requirements of the current UAV velocity measurement of maneuvering targets in terms of real-time and reliability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Unmanned aerial vehicles (UAV)

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PR-GNN: Enhancing PoC Report Recommendation with Graph Neural Network 40

PR-GNN: Enhancing PoC Report Recommendation with Graph Neura...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Lu, Jiangtao Huang, Song College of Command and Control Engineering Army Engineering University of PLA Nanjing China

ISBN: (纸本)9798350317152

There has been a growing number of software supply chain vulnerabilities disclosed annually, posing increasingly formidable challenges to vulnerability validation. Timely validation plays a critical role in mitigating the security risks across the entire software supply chain. Whenever a new vulnerability is disclosed, it may be difficult to generate a corresponding PoC for verification in a short time. Expediting the validation process can be achieved through reference to similar PoC reports, potentially reducing this time. Retrieving similar PoC reports manually is labor-intensive and time-consuming due to their distributed nature across different data sources. Moreover, PoC reports encompass diverse trigger methods, including code, instruction, and action. There is a limitation in the current modeling of different types of trigger methods in PoC reports, as it mainly focuses only on code-based trigger methods while disregarding other types of trigger methods. To tackle the issues, this Ph.D. research uses graph-based method to model all types of PoC and proposes a PoC report recommendation model utilizing graph neural network (PR-GNN) to provide related PoC reports when facing a new vulnerability. In this work, a collection of heterogeneous PoC reports from various sources is assembled and modeled as PoC heterogeneous graphs. PR-GNN accurately measures similarity by incorporating graph-level embedding comparison and fine-grained comparison of trigger method type nodes. To our knowledge, this research represents the first attempt to provide more accurate and efficient recommendations for PoC reports to assist security professionals in timely vulnerability verification and maintaining software supply chain security. © 2024 IEEE.

关键词： Network security

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Direction-of-Arrival Estimation Based on the Moving Array With/Without Model Mismatch 7

Direction-of-Arrival Estimation Based on the Moving Array Wi...

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7th IEEE Information Technology, Networking, Electronic and Automation control Conference, ITNEC 2024

作者： Wu, Shaozhuang Su, Qiao Bai, Lu Yang, Sihang Yang, Chen Ma, Zhiqing College of Communications Engineering Army Engineering University of Pla China College of Command and Control Engineering Army Engineering University of Pla Nanjing210007 China

ISBN: (纸本)9798350370782

This paper proposes the Direction-of-Arrival (DOA) estimation algorithms based on the moving array with and without model mismatch. Firstly, without model mismatch, dividing the uniform linear subarray extracted from the extended model based on the moving array into two parts, two selected receive signal vectors are obtained. By calculating the auto-covariance matrix and the cross-covariance matrix of these receive signal vectors, the DOAs can be estimated though eigenvalue decomposition. As for the model mismatch case, another receive signal vector can be gotten by introducing more delays, then, the DOAs can be obtained similarly with the proposed algorithm without model mismatch. Simulation results testify the effectiveness of the proposed algorithms, and provide the suggestions of the scope of application of two proposed algorithms. © 2024 IEEE.

关键词： Covariance matrix

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Investigating the Logical Capability of Graph Neural Networks via the Connection to C_(2)

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Data Intelligence 2024年第3期6卷 720-748页

作者： Zhangquan Zhou Shijiao Tang School of Command and Control Engineering Army Engineering University of PLA Nanjing 210001China School of Information Science and Engineering Nanjing Audit University Jinshen College Nanjing 210023China

Graph neural networks(GNNs)have garnered substantial application across a spectrum of real-world scenarios due to their remarkable ability to handle data organized in the form of ***,the full extent of GNNs'computational properties and logical capability remains a subject of ongoing *** study undertakes an exploration of the logical capabilities intrinsic to GNNs,approaching the matter from a theoretical *** this pursuit,a pivotal connection is established between GNNs and a specific fragment of first-order logic known as C_(2),which serves as a logical framework for modeling graph *** research further amplifies this discourse,introducing a subcategory of GNNs named ACR-GNN,illustrating that GNNs are capable of emulating the evaluation process of unary C,*** on these insights,we introduce an innovative version of GNN architectures capable of dealing with general C,*** attain this,we employ a mechanism known as message passing for GNN *** proposed GNN adaptations allow for simultaneous updating of node and node pair features,thereby enabling the management of both unary and binary C,*** prove that the proposed models exhibit the equivalent expressiveness to C_(2).This underpins the profound alignment between the logical capability of GNNs and the inherent nature of the logical language C,.We conduct several experiments on both of synthetic and real-world datasets to support our *** the experiments,we verify that our suggested models outperform both ACR-GNN and a commonly used model,GIN,when it comes to evaluating C,formulas.

关键词： Graph neural networks Logical capabilities C_(2)logical language

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A Novel Subcharacter-enhanced Hybrid Network for Chinese Text Classification

A Novel Subcharacter-enhanced Hybrid Network for Chinese Tex...

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2023 International Conference on Frontiers of Robotics and Software engineering, FRSE 2023

作者： Chen, Lei Wang, Yang Zheng, Yun Fei Yang, Zhen Cao, Tieyong Institute of Command-and-Control Engineering The Army Engineering University of Pla The Army Artillery and Denfense Academy of Pla Nanjing China

ISBN: (纸本)9798350301113

Chinese text classification aimed to set pre-defined labels to given documents, and it is a very important research field. To deal with this problem, a novel subcharacter-enhanced hybrid network model called SHN is proposed. The proposed SHN can hierarchically extract the text semantic features. Firstly, our model decomposes Chinese words by Cangjie-code into subcharacters. Secondly, both word embeddings and subcharacters n-grams vectors are used as the input part of SHN, which is aimed to fuse both internal structure information and semantic information. Thirdly, SHN makes use of a bidirectional GRU module that contains word-level attention, to obtains semantic information from the sentences in document. Finally, a dynamic convolution neural network module is used by SHN, which aimed to extract high level features. Experiments carried out on two datasets show that SHN can obtain better results than conventional methods and is effective. © 2023 IEEE.

关键词： Classification (of information)

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