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23rd IEEE International Conference on Software Quality, Reliability, and Security, QRS 2023

作者： Jia, Yetao Meng, Yangyang Zhuang, Honglin National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9798350319583

The use of malware for illicit cyber activities, including network attacks and information theft, poses a severe threat to cybersecurity. In comparison to traditional malware detection methods based on signature and heuristics, machine learning and deep learning-based malware detection methods demonstrate superior generalization ability. However, existing research still faces challenges such as reliance on relatively single malware features, inadequate ability to describe malware features, and overdependence on labeled data. In this paper, we propose an image-based malware classification method using self-supervised and contrastive learning, named IMCSCL. We visualize malware using opcode semantic features, and then detect malware using a contrastive learning method with improved feature encoder network. Experimental results demonstrate that IMCSCL achieves higher detection accuracy compared to supervised malware detection methods, achieving 98.85% accuracy on the Microsoft Malware Classification Challenge dataset. Fine-tuning the model using randomly selected 5% labeled samples from the training set still achieved high accuracy of 94.22%. IMCSCL exhibits superior generalization ability, faster convergence speed, and better training stability. Moreover, contrastive learning significantly reduces malware labeling costs while effectively enhancing detection performance. © 2023 IEEE.

关键词： Image classification

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Adversarial Example Detection for Deep Neural Networks: A Review 8

Adversarial Example Detection for Deep Neural Networks: A Re...

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8th International Conference on Data science in Cyberspace, DSC 2023

作者： Zhao, Chongyang Li, Hu Wang, Dongxia Liu, Ruiqi National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9798350331035

Deep neural networks have been widely applied in various critical domains. However, they are vulnerable to the threat of adversarial examples. It is challenging to make deep neural networks inherently robust to adversarial examples, while adversarial example detection offers advantages such as not affecting model classification accuracy. This paper introduces common adversarial attack methods and provides an explanation of adversarial example detection. Recent advances in adversarial example detection methods are categorized into two major classes: statistical methods and adversarial detection networks. The evolutionary relationship among different detection methods is discussed. Finally, the current research status in this field is summarized, and potential future directions are highlighted. © 2023 IEEE.

关键词： adversarial detection adversarial example deep neural network

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Lead-free perovskites-based photonic synaptic devices with zero electric energy consumption

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science China(information sciences) 2024年第6期67卷 433-441页

作者： Dandan HAO Di YANG Haixia LIANG Jia HUANG Fukai SHAN College of Electronics and Information Qingdao University Key Laboratory of Biofuels Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of Sciences School of Materials Science and Engineering Tongji University National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University

The von Neumann bottleneck is a critical limitation in synaptic devices. Therefore, artificial synaptic devices resembling biological neuromorphic synapses have been developed to overcome the von Neumann bottleneck. However, synaptic devices require voltages, which results in considerable energy consumption. Here, photonic synaptic devices with the vertical structure of indium tin oxide（ITO）/SnO2/Al2O3/CsBi3I10/Au are fabricated, which can work in the self-powered mode owing to the photovoltaic effect endowed by a vertical multilayer structure. Several fundamental synaptic functions, such as excitatory postsynaptic current, paired-pulse facilitation, short-term plasticity（STP）, long-term plasticity（LTP）, pulse-frequency-dependent plasticity, transition of STP to LTP, and the learning experience are emulated. Moreover, Morse-coded external light information is decoded by self-powered photonic synaptic devices. The results indicate that self-powered photonic synaptic devices based on lead-free perovskites exhibit great potential for efficient neuromorphic computing and optical wireless communication.

关键词： photonic synaptic devices lead-free perovskites zero energy consumption synaptic plasticity Morse code

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Technologies for investigating single-molecule chemical reactions

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national science Review 2024年第8期11卷 322-352页

作者： Chunyan Gao Qinghua Gao Cong Zhao Yani Huo Zhizhuo Zhang Jinlong Yang Chuancheng Jia Xuefeng Guo Center of Single-Molecule Sciences Institute of Modern OpticsFrontiers Science Center for New Organic MatterTianjin Key Laboratory of Micro-Scale Optical Information Science and TechnologyCollege of Electronic Information and Optical EngineeringNankai University Hefei National Research Center for Physical Sciences at Microscale University of Science and Technology of China Beijing National Laboratory for Molecular Sciences National Biomedical Imaging CenterCollege of Chemistry and Molecular Engineering Peking University

Single molecules,the smallest independently stable units in the material world,serve as the fundamental building blocks of *** different branches of single-molecule sciences,single-molecule chemical reactions,by revealing the behavior and properties of individual molecules at the molecular scale,are particularly attractive because they can advance the understanding of chemical reaction mechanisms and help to address key scientific problems in broad fields such as physics,chemistry,biology and materials *** review provides a timely,comprehensive overview of single-molecule chemical reactions based on various technical platforms such as scanning probe microscopy,single-molecule junction,single-molecule nanostructure,single-molecule fluorescence detection and crossed molecular *** present multidimensional analys es of single-molecule chemical reactions,offering new perspectives for research in different areas,such as photo catalysis/electrocatalysis,organic reactions,surface reactions and biological ***,we discuss the opportunities and challenges in this thriving field of single-molecule chemical reactions.

关键词： chemical reaction scanning probe microscopy single-molecule junction single-molecule fluorescence crossed molecular beam

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Safe Q-Learning for Data-Driven Nonlinear Optimal Control With Asymmetric State Constraints

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2408-2422页

作者： Mingming Zhao Ding Wang Shijie Song Junfei Qiao the School of Information Science and Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of Technology.Beijing 100124China IEEE the School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

This article develops a novel data-driven safe Q-learning method to design the safe optimal controller which can guarantee constrained states of nonlinear systems always stay in the safe region while providing an optimal ***,we design an augmented utility function consisting of an adjustable positive definite control obstacle function and a quadratic form of the next state to ensure the safety and ***,by exploiting a pre-designed admissible policy for initialization,an off-policy stabilizing value iteration Q-learning(SVIQL)algorithm is presented to seek the safe optimal policy by using offline data within the safe region rather than the mathematical ***,the monotonicity,safety,and optimality of the SVIQL algorithm are theoretically *** obtain the initial admissible policy for SVIQL,an offline VIQL algorithm with zero initialization is constructed and a new admissibility criterion is established for immature iterative ***,the critic and action networks with precise approximation ability are established to promote the operation of VIQL and SVIQL ***,three simulation experiments are conducted to demonstrate the virtue and superiority of the developed safe Q-learning method.

关键词： Adaptive critic control adaptive dynamic programming(ADP) control barrier functions(CBF) stabilizing value iteration Q-learning(SVIQL) state constraints

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A Tibetan Sentence Boundary Disambiguation Model Considering the Components on information on Both Sides of Shad

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Tsinghua science and technology 2023年第6期28卷 1085-1100页

作者： Fenfang Li Hui Lv Yiming Gao Dolha Yan Li Qingguo Zhou School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China Key Laboratory of China’s National Linguistic Information Technology Northwest Minzu UniversityLanzhou 730030China

Sentence Boundary Disambiguation(SBD)is a preprocessing step for natural language *** text into sentences is essential for Deep Learning(DL)and pretraining language *** punctuation marks may involve ambiguity about the sentences’beginnings and ***,the ambiguous punctuation marks must be distinguished,and the sentence structure must be correctly encoded in language *** study proposed a component-level Tibetan SBD approach based on the DL *** models can reduce the error amplification caused by word segmentation and part-of-speech *** most SBD methods have only considered text on the left side of punctuation marks,this study considers the text on both *** this study,465669 Tibetan sentences are adopted,and a Bidirectional Long Short-Term Memory(Bi-LSTM)model is used to perform *** experimental results show that the F1-score of the Bi-LSTM model reached 96%,the most efficient among the six *** are performed on low-resource languages such as Turkish and Romanian,and high-resource languages such as English and German,to verify the models’generalization.

关键词： Sentence Boundary Disambiguation(SBD) punctuation marks ambiguity Bidirectional Long Short-Term Memory(Bi-LSTM)model

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Vibration-Based Fault Diagnosis for Railway Point Machines Using VMD and Multiscale Fluctuation-Based Dispersion Entropy

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Chinese Journal of Electronics 2024年第3期33卷 803-813页

作者： Yongkui SUN Yuan CAO Peng LI Guo XIE Tao WEN Shuai SU National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University School of Electronic and Information Engineering Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University

As one of the most important railway signaling equipment,railway point machines undertake the major task of ensuring train operation *** fault diagnosis for railway point machines becomes a hot *** the advantage of the anti-interference characteristics of vibration signals,this paper proposes an novel intelligent fault diagnosis method for railway point machines based on vibration signals.A feature extraction method combining variational mode decomposition(VMD) and multiscale fluctuation-based dispersion entropy is developed,which is verified a more effective tool for feature ***,a two-stage feature selection method based on Fisher discrimination and ReliefF is proposed,which is validated more powerful than single feature selection ***,support vector machine is utilized for fault *** comparisons show that the proposed method performs *** diagnosis accuracies of normal-reverse and reverse-normal switching processes reach 100% and 96.57% ***,it is a try to use new means for fault diagnosis on railway point machines,which can also provide references for similar fields.

关键词： Fault diagnosis Vibrations Support vector machines Diversity reception Switches Feature extraction Rail transportation

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Non-conjugated polymer as printable electron transport layer for efficient and stable organic photovoltaic cells

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Journal of Energy Chemistry 2025年第6期105卷 835-842页

作者： Hao Hou Qian Kang Yafei Wang Wenxuan Wang Jianqiu Wang Yong Cui Qing Liao Jianhui Hou College of Materials Science and Engineering Beijing University of Technology School of Information Science and Technology Beijing University of Technology State Key Laboratory of Polymer Physics and Chemistry Beijing National Laboratory for Molecular Sciences CAS Research/Education Center for Excellence in Molecular Sciences Institute of Chemistry Chinese Academy of Sciences University of Chinese Academy of Sciences College of Materials Science and Engineering Fuzhou University

With the continuous improvement of photovoltaic efficiency in the organic photovoltaic(OPV),interface engineering has emerged as a pivotal issue in their practical ***,the robust crystallinity of small molecule electron transport layers(ETLs) and the poor film-forming abilities of conjugated polymer ETLs are a huge obstacle in this ***,an innovative and efficient nonconjugated polymer ETL,namely PNDI-SO,which contains polar cationic segments for solubility and conjugated units for efficient charge transport in stable OPV cells,is *** with suitable energy levels and excellent electron extraction capabilities,PNDI-SO-based OPV cells attain a power conversion efficiency(PCE) of 18.54%.Furthermore,compared with conventional OPV cells utilizing PFN-Br or PDINN,PNDI-SO substantially enhances long-term stability under continuous illumination,evidenced by a T80 lifetime(signifying retention of 80% of initial performance) exceeding 1250 ***,through scanning electron microscope,we verified that PNDI-SO achieves a harmonious balance between film-forming ability and charge transport properties for ETL,enabling the blade-coating OPV based on PBDB-TF:BTP-eC9 to achieve a PCE of 17.47%.These results suggest the potential of PNDI-SO as a promising interface material for industrial printing applications in OPV fabrication.

关键词： Blade-coating Electron transport layer Naphthalene diimide Organic solar cell Power conversion efficiency

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Broadband Chaos Generation and Synchronization Induced by Integrated Tri-section Laser

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IEEE Access 2024年 13卷 1-1页

作者： Guo, Yuanyuan Wei, Wuyin Gao, Hua Zhang, Yuanye Zhao, Tong Jia, Zhiwei Chang, Pengfa Wang, Longsheng Wang, Anbang Wang, Yuncai Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan China College of Information Engineering Shanxi Vocational University of Engineering Science and Technology Taiyuan China School of Information Engineering Guangdong University of Technology Guangzhou China

Broadband chaos generation is numerically demonstrated using an integrated tri-section laser which is composed of mutually coupled distributed feedback (DFB) lasers with a phase section, and the broadband chaos synchronization of two DFB lasers is achieved using the integrated laser as a driver. The simulation results indicate that the integrated tri-section laser with optical feedback can generate broadband chaos with a bandwidth up to 34 GHz, based on dual-mode beating effect. The influence of feedback strength and frequency interval on the chaos bandwidth are studied in detail. As a common driving signal, the broadband chaos signal can induce the response DFB lasers to generate chaos signals with a bandwidth of no less than 25 GHz and meanwhile achieve chaos synchronization with a correlation coefficient beyond 0.98. The low correlation coefficient between the drive signal and the response signal ensures the security of the chaos carrier from the public channel. Moreover, the dynamic properties of the integrated laser and the influence of the external parameters on chaotic synchronization are also investigated. Authors

关键词： Distributed feedback lasers

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A merged machine learning model for seasonal climate prediction in China

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science China Earth sciences 2025年第5期68卷 1469-1484页

作者： Danwei QIAN Yanyan HUANG Huijun WANG State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences

Improving the current level of skill in seasonal climate prediction is urgent for achieving sustainable socioeconomic development, and this is especially true in China where meteorological disasters are experienced frequently. In this study, based upon big climate data and traditional statistical prediction experiences, a merged machine learning model(Y-model) was developed to address this, as well as to further explore unknown potential predictors. In Y-model, empirical orthogonal function analysis was firstly applied to reduce the data dimensionality of the target predictand(temperature and precipitation in the four seasons over China). Image recognition techniques were used to automatically identify possible predictors from the big climate data. These predictors, associated with significant circulation anomalies, were recombined into a large ensemble according to different threshold settings for five factors determining the statistical forecast skill. Facebook Prophet was chosen to conduct the independent hindcasts for each season's climate at a lead time of two months. During 2011–2022, the seasonal climate in China was skillfully predicted by Y-model, with an averaged pattern correlation coefficient skill of 0.60 for temperature and 0.24 for precipitation, outperforming CFSv2. Potential predictor analysis for recent extreme events suggested that prior signals from the Indian Ocean and the stratosphere were important for determining the super Mei-yu in 2020, while the prior sea surface temperature over the western Pacific and the soil temperature over West Asia may have contributed to the extreme high temperatures in 2022. Our study provides new insights for seasonal climate prediction in China.

关键词： Machine learning Seasonal climate prediction China’s climate Image recognition techniques Large ensemble

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