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34th General Assembly and Scientific Symposium of the International Union of Radio science, URSI GASS 2021

作者： Ma, Fei Wang, Yuexian Wang, Ling Gong, Yanyun School of Electronics and Information Northwestern Polytechnical University Xi'an China The Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9789463968027

In this paper, a new approach without iteration is proposed for direct position determination (DPD) with Doppler shifts in the presence of unknown direction-dependent mutual coupling (DDMC). The special banded symmetric Toeplitz structure of mutual coupling matrix and Doppler shift containing location information can be exploited for constructing a space-time transformation matrix, and the spectral function which is utilized to obtain the locations of sources is established via the orthogonality between space-time transformation matrix and noise subspace. Simulation results show that our solution can accurately determine the emitter position in a single-step without a priori information of the DDMC. © 2021 URSI.

关键词： Electric fields

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The differential fault analysis on block cipher FeW

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Cybersecurity 2023年第2期6卷 62-74页

作者： Haiyan Xiao Lifang Wang Jinyong Chang School of Computer Science Northwestern Polytechnical UniversityXiAn 710055People's Republic of China Engineering University of PAP XiAn 710055People's Republic of China School of Information and Control Engineering XiAn University of Architecture and TechnologyXi'An 710055People's Republic of China State Key Laboratory of Information Security(SKLOIS) Institute of Information EngineeringChinese Academy of SciencesBeijing 100089People's Republic of China

Feather weight(FeW)cipher is a lightweight block cipher proposed by Kumar et *** 2019,which takes 64 bits plaintext as input and produces 64 bits *** Kumar et ***,FeW is a software oriented design with the aim of achieving high efficiency in software based *** seems that FeW is immune to many cryptographic attacks,like linear,impossible differential,differential and zero correlation ***,in recent work,Xie et *** the security of *** precisely,they proved that under the differential fault analysis(DFA)on the encryption states,an attacker can completely recover the master secret *** this paper,we revisit the block cipher FeW and consider the DFA on its key schedule algorithm,which is rather popular cryptanalysis for kinds of block *** particular,by respectively injected faults into the 30th and 29th round subkeys,one can recover about 55/80~69%bits of master *** the brute force searching remaining bits,one can obtain the full master secret *** simulations and experiment results show that our analysis is practical.

关键词： Differential fault analysis Block cipher FeW Side channel attack

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An analysis of network traffic identification based on decision tree 2

An analysis of network traffic identification based on decis...

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2nd International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2021

作者： Dai, Jiahao Chen, Yongqun Chen, Yucheng Meng, Aodong China Electronic Corporation NO.36 Institute Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781665432658

With the strong development momentum of the Internet, network not only brings convenience to our life, but also poses threats to our network security. Users can hide their IP and identity information through encryption algorithm, and carry out various illegal activities and transactions in the network. Therefore, it will be of great value to identify special traffic which impact on network security and exploring abnormal situations in the network. Special traffic is important to the security of the network space. In this paper, we establish a decision tree model based on C4.5 and random forest to compare the accuracy of the two decision tree algorithms in traffic classification. Experimental results show that these two methods can identify traffic effectively. © 2021 IEEE.

关键词： Decision trees

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DarkSAM: Fooling Segment Anything Model to Segment Nothing 38

DarkSAM: Fooling Segment Anything Model to Segment Nothing

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38th Conference on Neural information Processing Systems, NeurIPS 2024

作者： Zhou, Ziqi Song, Yufei Li, Minghui Hu, Shengshan Wang, Xianlong Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

Segment Anything Model (SAM) has recently gained much attention for its outstanding generalization to unseen data and tasks. Despite its promising prospect, the vulnerabilities of SAM, especially to universal adversarial perturbation (UAP) have not been thoroughly investigated yet. In this paper, we propose DarkSAM, the first prompt-free universal attack framework against SAM, including a semantic decoupling-based spatial attack and a texture distortion-based frequency attack. We first divide the output of SAM into foreground and background. Then, we design a shadow target strategy to obtain the semantic blueprint of the image as the attack target. DarkSAM is dedicated to fooling SAM by extracting and destroying crucial object features from images in both spatial and frequency domains. In the spatial domain, we disrupt the semantics of both the foreground and background in the image to confuse SAM. In the frequency domain, we further enhance the attack effectiveness by distorting the high-frequency components (i.e., texture information) of the image. Consequently, with a single UAP, DarkSAM renders SAM incapable of segmenting objects across diverse images with varying prompts. Experimental results on four datasets for SAM and its two variant models demonstrate the powerful attack capability and transferability of DarkSAM. Our codes are available at: https://***/CGCL-codes/DarkSAM. © 2024 Neural information processing systems foundation. All rights reserved.

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Energy Minimization Oriented Resource Allocation for Relay Assisted NOMA-MEC Networks

Energy Minimization Oriented Resource Allocation for Relay A...

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IEEE Conference on Global communications (GLOBECOM)

作者： Qianru Wang Liping Qian Yuan Wu Xiaoniu Yang College of Information Engineering Zhejiang University of Technology Hangzhou China State Key Laboratory of Internet of Things for Smart City University of Macau China Science and Technology on Communication Information Security Control Laboratory Jiaxing China Institute of Cyberspace Security Zhejiang University of Technology Hangzhou China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

With the growing demand for image transmission, there is a need for solutions that offer low energy consumption and low latency. In this paper, we present a novel relay-assisted system based on non-orthogonal multiple access (NOMA) and mobile edge computing (MEC). Our proposed system compresses images at the device end, decompresses them at either a relay or a cloud server (CS). The primary objective is to minimize system energy consumption under given task delay constraints. Considering that this is a non-convex optimization problem, we solve it by decomposing it into a continuous subproblem and a discrete subproblem. To solve the continuous subproblem, we convexify it by introducing new parameters and change variables to get the optimal the computing power of devices, relay and CS, sampling rate of devices, transmission power of devices and relay. To solve the discrete subproblem, we propose a cross-entropy (CE) algorithm to obtain the optimal decompression decision and subcarrier allocation decision. Simulation results demonstrate the accuracy and effectiveness of our algorithm in optimizing total energy consumption compared to the Linear Interactive and General Optimizer (LINGO) and frequency division multiple access (FDMA) methods.

关键词： Performance evaluation NOMA Energy consumption Image coding Multi-access edge computing Simulation Optimization methods Resource management Servers Relays

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Short-term traffic flow prediction based on BAS-VMD-CEEMDAN and IWOA-RF 11

Short-term traffic flow prediction based on BAS-VMD-CEEMDAN ...

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11th International Conference on information Systems and Computing technology, ISCTech 2023

作者： Tian, Jia Wang, Deyong Fn, Yanyun Zhao, Xueyi Fang, Jian Shi, Wenxi Xinjiang University School of Information Science and Engineering Urumqi830017 China Xinjiang Lianhaichuangzhi Information Technology Co. Ltd Key Laboratory of Big Data of Xinjiang Social Security Risk Prevention and Control Urumqi830011 China Beijing Academy of Science and Technology Beijing100035 China

ISBN: (纸本)9798350342406

Short-term traffic flow forecasting is crucial for intelligent traffic management. In view of the non-linear and random nature of short-term traffic flow, a prediction model based on BAS-VMD-CEEMDAN and IWOA-RF is proposed. Firstly, the parameters of the VMD, namely the modal number (K) and the value of the quadratic penalty term (α), are optimized using the BAS algorithm, and then the traffic flow is decomposed to obtain several VMF components and one RES component, which extracts the smooth information of the traffic flow. Subsequently, the RES component is decomposed using the decomposition completeness of CEEMDAN to obtain several IMF components, refining the complex information of the RES component. Then, the RF model is constructed according to the characteristics of each component, and then the parameters of RF models are optimized using IWOA. Finally, overlay the predictions of each component superimposed to obtain the final predictions. Experimental results show that the short-term traffic flow forecasting model basedon BAS-VMD-CEEMDAN-IWOA-RF has a high accuracy compared to other decomposition models. © 2023 IEEE.

关键词： Forecasting

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Adaptive Load Balancing Routing Algorithm for Low Earth Orbit Satellite Cluster Networks

Adaptive Load Balancing Routing Algorithm for Low Earth Orbi...

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International Conference on Computers, communications, and Systems (ICCCS)

作者： Liming Wang Zhan Xu Ruxin Zhi Jiahui Wang School of Electronics and Communication Engineering Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

Large-scale satellite networks are a crucial component of future communication systems. However, they pose several challenges to satellite routing design and link recovery. This paper proposes an Adaptive Load Balancing routing algorithm for Low Earth Orbit (LEO) Satellite Cluster Networks (ALBSCN) to meet the needs of large-scale Low Earth Orbit LEO satellite networks. The constellation is divided into clusters, with each cluster maintaining the intra-cluster link state by electing a cluster head. The cluster head computes intra-cluster and inter-cluster routes. Messages are forwarded using inter-cluster multipath routing and intra-cluster routing techniques. We validated the algorithm's performance and compared it with other algorithms in terms of packet delivery delay using simulation. Simulation results indicate that the proposed clustering routing scheme effectively reduced packet loss and end-to-end delay, while also increasing network throughput.

关键词： Satellites Adaptive systems Simulation Clustering algorithms Low earth orbit satellites Packet loss Routing

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Quick Routing Response to Link Failure in Low-Earth Orbit Satellite Networks 8

Quick Routing Response to Link Failure in Low-Earth Orbit Sa...

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8th IEEE International Conference on Computer and communications, ICCC 2022

作者： Lu, Zhiping Zhi, Ruxin Ma, Weiguo School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Beijing China Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781665450515

Low earth orbit satellite communication systems are attractive for provisioning global, high-speed and low latency Internet access services. In order to achieve global continuous multiple coverage, the number of satellites is tremendous. But Low earth orbit satellite networks are prone to instability due to unpredictable link failures and frequent topology changes. Therefore, in this paper, a novel routing schemes with quick response to link failures is first proposed. Based on Dijkstra algorithm, a scalable routing algorithm is proposed to minimize the end-to-end transmission delay. It takes advantage of the predictable constellation trajectory, and changes dynamically according to the changes of network topology. It provides the shortest routing path and an alternative path simultaneously. When a link failure is detected by one satellite, notification packets will be sent to its neighbors for adjustment to the alternative routing path. Notification packets also will be sent to the head node for the recalculation of routing table. Finally, extensive simulations have been conducted, and the results show that the proposed scheme is able to produce desired performance. © 2022 IEEE.

关键词： Routing algorithms

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PMB filter based distributed tracking of multiple extended targets under different resolutions

PMB filter based distributed tracking of multiple extended t...

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IEEE Conference on Vehicular technology (VTC)

作者： Yue Li Lin Gao Ping Wei Wanchun Li Huaguo Zhang Hao Mu School of Information and Communication Engineering University of Electronic Science and Technology of China National Key Laboratory of Electromagnetic Space Security

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

A key feature of extended target (ET) is that it can produce multiple measurements, thus providing detailed information such as size, orientation. However, due to the measurement number decrease, the ET tends to be a point target (PT) when it becomes far from the sensor, leading to disability of estimating the extensions. In this paper we consider the problem of distributed ETs tracking based on multiple sensors. In such a case the measurements decrease of an ET can be compensated by other sensors, so that the tracking performance can be maintained. In the proposed algorithm the targets are modeled by Poisson multi-Bernoulli (PMB) random finite set (RFS) and the state of each target consists of two parts representing the possibility of being ET and PT, respectively. In the local filtering state, interaction between ET and PT states is considered in the prediction step for target identity change between ET and PT, based on which the local PMB filter is achieved for seamlessly tracking ETs and PTs. In the fusion part a generalized covariance intersection (GCI) based criterion is proposed to fuse the posteriors of each sensor. The performance of proposed algorithm is verified via simulations.

关键词： Radio frequency Vehicular and wireless technologies Target tracking Fuses Switches Filtering algorithms Prediction algorithms information filters Size measurement Covariance matrices

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A Simple Semi-Supervised Joint Learning Framework for Few-shot Text Classification 5

A Simple Semi-Supervised Joint Learning Framework for Few-sh...

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5th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2022

作者： Lu, Shaoshuai Chen, Long Wang, Wenjing Xu, Cai Zhao, Wei Guan, Ziyu Lu, Guangyue Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and Telecommunications China School of Computer Science and Technology Xidian University China

ISBN: (纸本)9781450396899

The lack of labeled data is the bottleneck restricting deep text classification algorithm. State-of-the-art for most existing deep text classification methods follow the two-step transfer learning paradigm: pre-training a large model on an auxiliary task, and then fine-tuning the model on a labeled data. Their shortcoming is the high cost of training. To reduce training costs as well as alleviate the need for labeled data, we present a novel simple Semi-Supervised Joint Learning (SSJL) framework for few-shot text classification that captures the rich text semantics from large user-tagged data (referred to as weakly-labeled data) with noisy labels while also learning correct category distributions in small labeled data. We refine the contrastive loss function to better exploit inter-class contrastive patterns, making contrastive learning more applicable to the weakly-labeled setting. Besides, an appropriate temperature hyper-parameter can improve model robustness under label noise. The experimental results on four real-world datasets show that our approach outperforms the other baseline methods. Moreover, SSJL significantly boosts the deep models' performance with only 0.5% (i.e. 32 samples) of the labeled data, showing its robustness in the data sparsity scenario. © 2022 ACM.

关键词： Semantics

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