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The Security of Using Large Language Models:A Survey With Emphasis on ChatGPT

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 1-26页

作者： Wei Zhou Xiaogang Zhu Qing-Long Han Lin Li Xiao Chen Sheng Wen Yang Xiang the school of Science Computing and Engineering Technologies Swinburne University of Technology IEEE the school of Computer and Mathematical sciences the University of Adelaide Adelaide the Faculty of Science and Engineering Southern Cross University the school of information and Physical sciences the University of Newcastle

ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential security risks that need to be carefully evaluated and addressed. In this survey, we provide an overview of the current state of research on security of using ChatGPT, with aspects of bias, disinformation, ethics, misuse,attacks and privacy. We review and discuss the literature on these topics and highlight open research questions and future *** this survey, we aim to contribute to the academic discourse on AI security, enriching the understanding of potential risks and mitigations. We anticipate that this survey will be valuable for various stakeholders involved in AI development and usage, including AI researchers, developers, policy makers, and end-users.

关键词： Artificial intelligence (AI) ChatGPT large language models (LLMs) security

Characterization of size-resolved aerosol hygroscopicity and liquid water content in Nanjing of the Yangtze River Delta

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Journal of Environmental sciences 2025年第5期151卷 26-41页

作者： Youling Jiang Yan Ma Jun Zheng Nan Ye Cheng Yuan school of Environmental Science and Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044China school of Emergency management Nanjing University of Information Science&TechnologyNanjing 210044China

Aerosol hygroscopicity and liquid water content(ALWC)have important influences on the environmental and climate effect of *** this study,we measured the hygroscopic growth factors(GF)of particles with dry diameters of 40,80,150,and 200 nm during the wintertime in *** the GF-derived hygroscopicity parameter(κ_(gf))and ALWC increased with particle size,but displayed differing diurnal variations,withκ_(gf)peaking around the midday,while ALWC peaking in the early ***,ammonium and oxygenated organic aerosols(OOA)were found as the chemical components mostly strongly correlated with ALWC.A closure study suggests that during midday photo-oxidation and nighttime high ALWC periods,theκof organic aerosols(κ_(org))was underestimated when using previous ***,we re-constructed parameterizations forκ_(org)and the oxidation level of organics for these periods,which indicates a higher hygroscopicity of photochemically formed OOA than the aqueous OOA,yet both being much higher than the generally assumed OOA ***,in a typical high ALWC episode,concurrently increased ALWC,nitrate,OOA as well as aerosol surface area and mass concentrations were observed under elevated ambient *** strongly indicates a coupled effect that the hygroscopic secondary aerosols,in particular nitratewith strong hygroscopicity,led to large increase in ALWC,which in turn synergistically boosted nitrate and OOA formation by heterogeneous/aqueous *** interaction may represent an important mechanism contributing to enhanced formation of secondary aerosols and rapid growth of fine particulate matter under relatively high RH conditions.

关键词： Aerosol hygroscopicity Aerosol liquid water content Photo-oxidation Aqueous/heterogeneous reactions

BEV-Locator:an end-to-end visual semantic localization network using multi-view images

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Science China(information sciences) 2025年第2期68卷 134-150页

作者： Zhihuang ZHANG Meng XU Wenqiang ZHOU Tao PENG Liang LI Stefan POSLAD school of Vehicle and Mobility Tsinghua University school of information Technology & management University of International Business and Economics Qcraft Inc. school of Electronic Engineering and Computer Science Queen Mary University of London

Accurate localization ability is fundamental in autonomous driving. Traditional visual localization frameworks approach the semantic map-matching problem with geometric models, which rely on complex parameter tuning and thus hinder large-scale deployment. In this paper, we propose BEV-Locator: an end-to-end visual semantic localization neural network using multi-view camera images. Specifically, a visual BEV(bird-eye-view) encoder extracts and flattens the multi-view images into BEV space. While the semantic map features are structurally embedded as map query sequences. Then a cross-model transformer associates the BEV features and semantic map queries. The localization information of ego-car is recursively queried out by cross-attention modules. Finally, the ego pose can be inferred by decoding the transformer outputs. This end-to-end model speaks to its broad applicability across different driving environments, including high-speed scenarios. We evaluate the proposed method in large-scale nuScenes and Qcraft datasets. The experimental results show that the BEV-Locator is capable of estimating the vehicle poses under versatile scenarios, which effectively associates the cross-model information from multi-view images and global semantic maps. The experiments report satisfactory accuracy with mean absolute errors of 0.052 m, 0.135 m and 0.251° in lateral, longitudinal translation and heading angle degree.

关键词： visual localization semantic map bird-eye-view transformer pose estimation

Energy injection, transport, and dissipation in Earth's magnetosphere

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Science China Earth sciences 2025年第2期68卷 363-388页

作者： Huishan FU Jinbin CAO school of Space and Earth sciences Beihang UniversityBeijing 100191China Key Laboratory of Space Environment Monitoring and information Processing Ministry of Industry and Information TechnologyBeijing 100191China

The Earth's magnetosphere is a region occupied by many artificial satellites, and also is a region that spacecraft must cruise during the deep-space exploration. In this sense, the Earth's magnetosphere is closely related to human activity and is a candidate for us to expand our living space. Generally, the Earth's magnetosphere can preclude most energetic particles from the Sun and the interstellar space, effectively protecting human beings on the Earth from being attacked and thus making the Earth to be a habitable planet. However, in some conditions, the Earth's magnetosphere becomes dynamic and energetic, and consequently may damage the artificial satellites, threaten the astronauts' health, and disrupt the ground infrastructure, which leads to a decline in the national economy. Therefore, investigating how energy is injected into the magnetosphere, how it is transported in the magnetosphere, and how it is ultimately dissipated in the magnetosphere are the key issues in space physics. Targeting these key issues, in this paper, we review the recent progress on them. Particularly, we introduce the relevant scientific questions,models, methods, and spacecraft missions, for better building a physical link among the energy injection, transport, and dissipation in the magnetosphere, present an energy chain of the magnetosphere, reveal the relationship between such energy chain and the space weather events, and discuss the forecasting and warning methods for energetic-particle events in the magnetosphere. The magnetospheric energy chain discussed in this paper will help us reveal the mechanisms of space weather events, establish the models of space environment, and forecast the disastrous space weather events.

关键词： Earth's magnetosphere Energy injection Energy transport Energy dissipation

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Impacts of ENSO on wintertime total column ozone over the Tibetan Plateau based on the historical simulations of community Earth system model

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Earth and Planetary Physics 2025年第02期 424-434页

作者： XiaoWen Yuan YuZhen Wang Yang Li YuHao Liu WeiLing Xu LiZi Wang RuiHan Deng school of Atmospheric sciences Chengdu University of Information Technology

The ozone over the Tibetan Plateau(TP) plays an important role in protecting the local ecology by absorbing ultraviolet solar rays. The El Ni?o-Southern Oscillation(ENSO), recognized as the strongest interannual climate phenomenon globally, can create ozone variations over the TP. Based on the historical experimental simulation results of two Community Earth System Models(i.e. CESM2-WACCM and CESM2-WACCM-FV2) that include the coupling process of stratospheric chemistry-radiation-dynamics, this study analyzes the impact of ENSO on the wintertime total ozone column(TCO) over the TP, as well as its physical processes, from 1979 to 2014. When compared to observations, the results show that the two models can basically simulate the spatial distribution of the climate state and standard deviation of the TP TCO. In the two models, CESM2-WACCM performs better. During the winter when the ENSO signal is strongest, its warm phase, El Ni?o, cools the tropospheric temperature over the TP by modifying the atmospheric circulation, which induces a decrease in the tropopause height. Such decreases in the tropopause height are responsible for the TP TCO increase. The cool phase La Ni?a is responsible for a TCO decrease over the TP, in a manner resembling the El Ni?o but with the opposite signal. Our results are consistent with previous observational analysis, and the relevant research provides valuable scientific insights for evaluating and improving the Earth System Model that incorporates the coupling process of stratospheric chemistry-radiation-dynamics.

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Privacy-preserving explainable AI: a survey

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Science China(information sciences) 2025年第1期68卷 23-56页

作者： Thanh Tam NGUYEN Thanh Trung HUYNH Zhao REN Thanh Toan NGUYEN Phi Le NGUYEN Hongzhi YIN Quoc Viet Hung NGUYEN school of information and Communication Technology Griffith University school of Computer and Communication sciences Ecole Polytechnique Federale de Lausanne Faculty of Mathematics and Computer Science University of Bremen Faculty of information Technology HUTECH University Department of Computer Science Hanoi University of Science and Technology school of Electrical Engineering and Computer Science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

Graph reinforcement learning with relational priors for predictive power allocation

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Science China(information sciences) 2025年第2期68卷 230-247页

作者： Jianyu ZHAO Chenyang YANG school of Electronics and information Engineering Beihang University

Deep reinforcement learning for resource allocation has been investigated extensively owing to its ability of handling model-free and end-to-end problems. However, its slow convergence and high time complexity during online training hinder its practical use in dynamic wireless systems. To reduce the training complexity, we resort to graph reinforcement learning for leveraging two kinds of relational priors inherent in many wireless communication problems: topology information and permutation properties. To harness the two priors, we first conceive a method to convert the state matrix into a state graph,and then propose a graph deep deterministic policy gradient(DDPG) algorithm with the desired permutation property. To demonstrate how to apply the proposed methods, we consider a representative problem of using reinforcement learning, predictive power allocation, which minimizes the energy consumption while ensuring the quality-of-service of each user requesting video streaming. We derive the time complexity required by training the proposed graph DDPG algorithm and fully-connected neural network-based DDPG algorithm in each time step. Simulations show that the graph DDPG algorithm converges much faster and needs much lower time and space complexity than existing DDPG algorithms to achieve the same learning performance.

关键词： reinforcement learning graph neural network relational priors resource allocation

Design and test of cesium atomic concentration detection system based on TDLAS*1

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Optoelectronics Letters 2025年第3期21卷 167-171页

作者： LIANG Lizhen LIU Shanhu WU Yong WEI Jianglong XIE Yahong Hefei Institutes of Physical Science Chinese Academy of Sciences school of Science Shandong Jianzhu University school of Electronic and information Engineering Anhui Jianzhu University

In order to better build the neutral beam injector with negative ion source (NNBI), the pre-research on key technologies has been carried out for the comprehensive research facility for fusion technology (CRFFT). Cesium seeding into negative-ion sources is a prerequisite to obtain the required negative hydrogen ion. The performance of ion source largely depends on the cesium conditions in the source. It is very necessary to quantitatively measure the amount of cesium in the source during the plasma on and off periods (vacuum stage).

关键词： A

Bifurcations and Spatiotemporal Patterns in the Diffusive Nutrient-Microor ganism Model

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Acta Mathematicae Applicatae Sinica 2025年第1期41卷 162-178页

作者： Ya-di WANG Hai-long YUAN Yan-ling LI school of Arts and sciences Shaanxi University of Science and TechnologyXi'an 710021China school of Mathematics and Statistics Xi'an Jiaotong UniversityXi'an 710049China school of Mathematics and information Science Shaanxi Normal UniversityXi'an 710062China

In this paper,the diffusive nutrient-microorganism model subject to Neumann boundary conditions is *** Hopf bifurcations and steady state bifurcations which bifurcate from the positive constant equilibrium of the system are investigated in *** addition,the formulae to determine the direction of Hopf and steady state bifurcations are *** results show the existence of spatially homogeneous/nonhomogeneous periodic orbits and steady state solutions,which indicates the spatiotemporal dynamics of the *** numerical simulations are also presented to support the analytical results.

关键词： nutrient-microorganism model Hopf bifurcation steady state bifurcation simulations

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