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ETFIDS: An Entropy-Driven, Time-Frequency Analysis Framework for In-Vehicle CAN Signal Intrusion Detection

IEEE Internet of Things Journal 2025年

作者： Liu, Wanning Qin, Guihe Liang, Yanhua Song, Jiaru Liu, Qingxin Zhou, Xue Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Changchun130012 China

In recent years, cyberattacks against automobiles have exposed significant security threats to in-vehicle networks. The vulnerability of communication signals to malicious interference and manipulation can lead to serious system failures or abnormal behavior. The existing in-vehicle network intrusion detection methods do not fully exploit the time-frequency characteristics of Controller Area Network (CAN) signals. This limitation reduces their effectiveness in capturing subtle changes and signal complexity. Based on the above motivation, from the perspective of signal perception, we propose an entropy-driven, time-frequency analysis framework for in-vehicle network intrusion detection. The framework integrates a signal sampler, a frequency-domain detector, and a time-domain detector. The signal sampler, as the system's front-end module, extracts real-time physical signal data streams from CAN messages. The frequency-domain detector identifies frequency components, detecting high-frequency disturbances and cyclic variations. Meanwhile, the time-domain detector captures instantaneous changes and sudden anomalies. It analyzes signal complexity and anomalies through both stream and block detection. Experimental results demonstrate that the proposed method performs well under various attack scenarios, offering superior detection and real-time performance. It effectively senses multiple signal anomalies, providing a robust intrusion detection solution for modern in-vehicle networks. © 2025 IEEE.

关键词： Network intrusion

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Unveiling Vulnerability of Self-Attention 30

Unveiling Vulnerability of Self-Attention

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liong, Khai Jiet Wu, Hongqiu Zhao, Hai Xiaoshan, Li Minjie, Bian Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Technology Innovation Department Shanghai Data Group Co. Ltd. China Shanghai Data Group Co. Ltd. China

ISBN: (纸本)9782493814104

Pre-trained language models (PLMs) are shown to be vulnerable to minor word changes, which poses a big threat to real-world systems. While previous studies directly focus on manipulating word inputs, they are limited by their means of generating adversarial samples, lacking generalization to versatile real-world attack. This paper studies the basic structure of transformer-based PLMs, the self-attention (SA) mechanism. (1) We propose a powerful perturbation technique HackAttend, which perturbs the attention scores within the SA matrices via meticulously crafted attention masks. We show that state-of-the-art PLMs fall into heavy vulnerability that minor attention perturbations (1%) can produce a very high attack success rate (98%). Our paper expands the conventional text attack of word perturbations to more general structural perturbations. (2) We introduce S-Attend, a novel smoothing technique that effectively makes SA robust via structural perturbations. We empirically demonstrate that this simple yet effective technique achieves robust performance on par with adversarial training when facing various text attackers. Code is publicly available at ***/liongkj/HackAttend. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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Entropy engineering in CaZn_(2)Sb_(2)-YbMg_(2)Sb_(2)Zintl alloys for enhanced thermoelectric performance

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Rare Metals 2022年第9期41卷 2998-3004页

作者： Ke-Jia Liu Zong-Wei Zhang Chen Chen Li-Hua Wei Huo-Lun He Jun Mao Qian Zhang School of Materials Science and Engineering and Institute of Materials Genome&Big DataHarbin Institute of TechnologyShenzhen518055China Department of Mechanical Engineering The University of Hong KongHong Kong999077China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin150001China

The significant atomic disorder induced by entropy engineering can effectively suppress lattice thermal conductivity and improve thermoelectric *** variety of compositions of Zintl phases offers a wide range of possibilities for entropy *** we successfully prepared a five-component solid solution(CaZn_(2)Sb_(2))_(0.5)(YbMg_(2)Sb_(2))_(0.5) with a configurational entropy of~1.40R,whereR is the gas *** a result,the room-temperature lattice thermal conductivity was only~0.68 W·m^(-1)·K^(-1),which is lower than that of all AM_(2)Sb_(2) Zintl phases.

关键词： alloys entropy performance

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A Fully 3-D-Printing-Compatible E-Plane Elliptical Waveguide Junction for Power Dividing/Combining Applications

A Fully 3-D-Printing-Compatible E-Plane Elliptical Waveguide...

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2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

作者： Chen, Sicheng Li, Jin Yuan, Tao Guangdong Prov. Mobile Terminal Microwave and Millimeter-Wave Antenna Engineering Research Center College of Electronics and Information Engineering Shenzhen University China Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication China State Key Laboratory of Millimeter Waves China College of Electronics and Information Engineering ATR National Key Laboratory of Defense Technology Shenzhen University China

ISBN: (纸本)9798350347647

In this paper, a new class of 3-D-printing-compatible E-plane elliptical waveguide (EWG) junction is proposed for wideband power dividers/combiners. The junction is based on an EWG architecture with tailored power dividing and impedance-matching structures that are configured in a Y-shape profile. The junction is devised according to a specified orientation for 3-D printing and it features smooth and intrinsically self-supportable waveguide sidewalls. Compared to conventional rectangular waveguide junctions, the proposed EWG junction exhibits dramatically enhanced structural compatibility with additive manufacturing technology. A novel four-way EWG-junction-based power divider is demonstrated at Ka band. The power divider is prototyped monolithically by incorporating Polyjet 3-D printing and electroless copper plating processes. RF performance of the power divider shows a return loss of mostly over 20 dB, transmission coefficients of averagely -6.5 dB, and small amplitude and phase imbalances across the entire Ka band, successfully validating the wideband and low-loss characteristics of the proposed EWG junction. © 2023 IEEE.

关键词： Voltage dividers

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Fault Diagnosis Method for Multiple Sources based on IESFSC-SSRgram

Fault Diagnosis Method for Multiple Sources based on IESFSC-...

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2024 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2024

作者： Zhihao, Wu Shixian, Gong Chenguang, Huang Hang, Jin Zechao, Liu Crrc Qingdao Sifang Locomotive and Rolling Stock Co. Ltd National Engineering Laboratory Qingdao China Behavior and System Safety of Traffic Engineering Structure and School of Mechanical Engineering Shijiazhuang Tiedao University State Key Laboratory of Mechanical Shijiazhuang China Data Management Engineering Center Weichai Power Co. Ltd. Weifang China Institute of Magnetic Levitation and Electromagnetic Propulsion China Aerospace Science and Industry Corporation Limited Beijing China Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University State Key Laboratory of Mechanical Shijiazhuang China

ISBN: (纸本)9798350388855

The division and determination of frequency bands are always core problems in fault diagnosis methods for rotating machinery. Currently, the frequency band division strategy of most fault diagnosis methods is the 1/3-binary tree or realized by wavelet packet transform (such as fast kurtosis diagram and Autogram). This method is relatively fixed, making it difficult to accurately cover the resonance frequency band and achieve multi-source fault identification. To address the above problems, an adaptive frequency band division strategy based on Fast Spectral Correlation (FSC) and Scale-Space Representation (SSR) is proposed. The enhanced enveloping spectrum (EES) of each frequency band after division is obtained, and the improved Fault Quantification Index (IFQI) is used to measure the richness of target information in each enveloped spectrum (ES), generating a two-dimensional diagram. The envelope spectrum with the largest IFQI value is selected as the improved envelope spectrum (IES) obtained by the FSC and SSR division strategy (IESFSC-SSRgram), enabling the fault diagnosis of the axle box bearing. The effectiveness and superiority of the proposed method in identifying multi-source concurrent faults in the wheelset bearing system are verified by comparing it with the traditional method. © 2024 IEEE.

关键词： Binary trees

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Improved Power Conversion Efficiency and Stability of Perovskite Solar Cells Induced by Dual Interface Passivation

Improved Power Conversion Efficiency and Stability of Perovs...

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2023 International Conference on Optoelectronic Materials and Devices, ICOMD 2023

作者： Guan, Nianci Han, Qizhuo Institute of Biomedical Materials & Engineering Northwestern Polytechnical University Xi'an710072 China The School of Computer Science National Engineering Laboratory for Integrated Aero-Space-Ground- Ocean Big Data Application Technology Shaanxi Provincial Key Laboratory of Speech and Image Information Processing Northwestern Polytechnical University Xi’an710072 China

ISBN: (纸本)9781510674509

Efficient and stable Perovskite solar cells (PSCs) have been successfully produced using a dual-layer modified (DLM) perovskite thin film. This method simultaneously modifies both the bottom (SnO2/perovskite) and top (perovskite/SpiroOMeTAD) interfaces of the perovskite. The crystallinity of the perovskite film is enhanced after the DLM treatment. Additionally, thin barrier layers are formed on both its bottom and top surfaces, which reduce surface defect density and non-radiative recombination of carriers. The bottom and top modifier layers prevent direct contact between the hole transport layer and the electron transport layer, forming a high-energy barrier that promotes carrier transmission in PSCs. Consequently, the methylammonium acetate (MAAc)-PSC achieves an efficiency of 21.96%. © 2024 SPIE. All rights reserved.

关键词： Perovskite solar cells

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CLDG: Contrastive Learning on Dynamic Graphs 39

CLDG: Contrastive Learning on Dynamic Graphs

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39th IEEE International Conference on data engineering, ICDE 2023

作者： Xu, Yiming Shi, Bin Ma, Teng Dong, Bo Zhou, Haoyi Zheng, Qinghua Xi'an Jiaotong University Department of Computer Science and Technology China Xi'an Jiaotong University Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering China Xi'an Jiaotong University Department of Distance Education China Beihang University School of Software China Beihang University Advanced Innovation Center for Big Data and Brain Computing China

ISBN: (纸本)9798350322279

The graph with complex annotations is the most potent data type, whose constantly evolving motivates further exploration of the unsupervised dynamic graph representation. One of the representative paradigms is graph contrastive learning. It constructs self-supervised signals by maximizing the mutual information between the statistic graph's augmentation views. However, the semantics and labels may change within the augmentation process, causing a significant performance drop in downstream tasks. This drawback becomes greatly magnified on dynamic graphs. To address this problem, we designed a simple yet effective framework named CLDG. Firstly, we elaborate that dynamic graphs have temporal translation invariance at different levels. Then, we proposed a sampling layer to extract the temporally-persistent signals. It will encourage the node to maintain consistent local and global representations, i.e., temporal translation invariance under the timespan views. The extensive experiments demonstrate the effectiveness and efficiency of the method on seven datasets by outperforming eight unsupervised state-of-the-art baselines and showing competitiveness against four semi-supervised methods. Compared with the existing dynamic graph method, the number of model parameters and training time is reduced by an average of 2,001.86 times and 130.31 times on seven datasets, respectively. The code and data are available at: https://***/yimingxu24/CLDG. © 2023 IEEE.

关键词： Graph neural networks

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Sequence-to-Sequence Multi-Hop knowledge Reasoning Based on Retentive Network 7

Sequence-to-Sequence Multi-Hop Knowledge Reasoning Based on ...

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7th International Conference on Computer Information Science and Application Technology, CISAT 2024

作者： Su, Ruilin Zhang, Wanshan Yu, Dunhui Hubei University Wuhan China Wuhan430062 China Hubei University School of Computer Science and Information Engineering Wuhan430062 China Hubei University Hubei Key Laboratory of Big Data Intelligent Analysis and Application Wuhan430062 China Engineering and Technical Research Center of Hubei Province in Software Engineering Wuhan430062 China

ISBN: (纸本)9798350375107

Multi-hop knowledge Reasoning is a task that involves generating an answer given a query and a knowledge graph. Existing sequence-to-sequence reasoning models use the Transformer to encode and decode sequences, but these models have some flaws, such as the inability to effectively handle long-sequence reasoning and susceptibility to exposure bias. To address these issues, we provides a sequence-to-sequence reasoning model named STSR, which is based on Retentive Network. Aiming at improving training efficiency through parallel training, this model leverages the advantages in Retentive Network, reduce time overhead, and enhance reasoning efficiency through iterative reasoning. It effectively mitigates the problems of high spatial overhead and low efficiency in long-sequence reasoning faced by the Transformer. Moreover, it retains and updates historical information during the encoding and decoding process, enhancing the model's memory and generalization capabilities. Additionally, the Scheduled Sampling method is adopted to alleviate the exposure bias introduced during reasoning, which involves using the model's own output as the input for the next moment with a certain probability during training, instead of using the true label. We conduct the experiment on six public datasets, with the results showing that the proposed model outperforms existing baseline models in terms of precision and generation quality. This paper provides a new solution for the task of sequence-to-sequence multihop knowledge reasoning and also demonstrates the potential application of the Retentive Network in natural language processing. © 2024 IEEE.

关键词： Iterative decoding

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Massively parallel algorithms for fully dynamic all-pairs shortest paths

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Frontiers of Computer Science 2024年第4期18卷 201-203页

作者： Chilei WANG Qiang-Sheng HUA Hai JIN Chaodong ZHENG National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China

1 Introduction In recent years,the Massively Parallel Computation(MPC)model has gained significant ***,most of distributed and parallel graph algorithms in the MPC model are designed for static graphs[1].In fact,the graphs in the real world are constantly *** size of the real-time changes in these graphs is smaller and more *** graph algorithms[2,3]can deal with graph changes more efficiently[4]than the corresponding static graph ***,most studies on dynamic graph algorithms are limited to the single machine ***,a few parallel dynamic graph algorithms(such as the graph connectivity)in the MPC model[5]have been proposed and shown superiority over their parallel static counterparts.

关键词： dynamic shortest gained

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Self-assembly of a new 3D platelike ternary-oxo-cluster:An efficient catalyst for the synthesis of pyrazoles

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Chinese Chemical Letters 2022年第1期33卷 354-357页

作者： Guoping Yang Yufeng Liu Xiaoling Lin Bangming Ming Ke Li Changwen Hu Jiangxi Province Key Laboratory of Synthetic Chemistry Jiangxi Key Laboratory for Mass Spectrometry and InstrumentationEast China University of TechnologyNanchang 330013China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System East China University of TechnologyNanchang 330013China Key Laboratory of Cluster Science of Ministry of Education School of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing 100081China

A new metal-oxo-clusters-based inorganic framework[NaCo_(2)Mo_(2)O_(7)(OH)_(3)]_(n)(NaCoMo),named as 3D platelike ternary-oxo-cluster,has been hydrothermally synthesized and characterized by single-crystal X-ray diffraction structure analysis,FT-IR spectroscopy,powder X-ray diffraction(PXRD),scanning electron microscope(SEM),energy-dispersive X-ray spectroscopy(EDS)analyses,X-ray photoelectron spectroscopy(XPS)and thermogravimetric analysis(TGA).Structure analysis reveals that there are no classical building units in NaCoMo,and the asymmetric units of NaCoMo are directly extended into a new platelike 3D *** functional theory calculations(DFT)indicates that the crystal formation process is exothermic and the structure is extremely *** addition,the compound presents excellent catalytic activity in the condensation and cyclization reaction of sulfonyl hydrazides and 1,3-diketones to synthesize pyrazoles,and the yield of the desired product is up to 99%.The successful synthesis of NaCoMo represents the discovery of a new kind of non-classical polyoxometalates.

关键词： Polyoxometalates Oxo clusters 3D inorganic framework Condensation reaction Pyrazoles

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