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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

Intelligent integrated sensing and communication:a survey

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Science China(Information Sciences) 2025年第03期68卷 5-46页

作者： Jifa ZHANG Weidang LU Chengwen XING Nan ZHAO Naofal AL-DHAHIR George K.KARAGIANNIDIS Xiaoniu YANG school of Information and communication engineering Dalian University of Technology College of Information engineering Zhejiang University of Technology school of Information and Electronics Beijing Institute of Technology Department of Electrical and computer engineering The University of Texas at Dallas Department of Electrical and computer engineering Aristotle University of Thessaloniki

Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

关键词： artificial intelligence deep learning deep reinforcement learning federated learning generative artificial intelligence integrated sensing and communication machine learning transfer learning

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Low-profile,low sidelobe array antenna with ultrawide beam coverage for UAV communication

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Chinese Journal of Aeronautics 2025年第1期38卷 444-454页

作者： Mei LI Zhiliang SHANG Lin PU Ming-Chun TANG Lei ZHU school of Microelectronics and communication engineering Chongqing UniversityChongqing 400044China Department of Electrical and computer engineering University of MacaoMacao SAR 999078China

This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground *** array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low ***,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source ***,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating *** consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation *** indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer *** concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.

关键词： Array antenna Broad beam Fan beam Low sidelobe level Chebyshev synthesis UAV communication

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A Decoupling-Type Strategy for the Allen-Cahn Equation on Curved Surfaces

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Journal of Mathematical Research with Applications 2025年第1期45卷 73-83页

作者： Xiaoman XIE Qing PAN school of computer and communication engineering Changsha University of Science & Technology

In this paper, we construct an efficient decoupling-type strategy for solving the Allen-Cahn equation on curved surfaces. It is based on an FEM-EIEQ(Finite Element Method and explicit-Invariant Energy Quadratization) fully discrete scheme with unconditional energy stability. Spatially the FEM is adopted, using a triangular mesh discretization strategy that can be adapted to complex regions. Temporally, the EIEQ approach is considered, which not only linearizes the nonlinear potential but also gives a new variable that we combine with the nonlocal splitting method to achieve the fully decoupled computation. The strategy can successfully transform the Allen-Cahn system into some completely independent algebraic equations and linear elliptic equations with constant coefficients, we only need to solve these simple equations at each time step. Moreover, we conducted some numerical experiments to demonstrate the effectiveness of the strategy.

关键词： FEM-EIEQ Allen-Cahn equation surface

PriChain: Efficient Privacy-Preserving Fine-Grained Redactable Blockchains in Decentralized Settings

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Chinese Journal of Electronics 2025年第1期34卷 82-97页

作者： Hongchen Guo Weilin Gan Mingyang Zhao Chuan Zhang Tong Wu Liehuang Zhu Jingfeng Xue school of computer Science and Technology Beijing Institute of Technology school of Cyberspace Science and Technology Beijing Institute of Technology school of computer and communication engineering University of Science and Technology Beijing

Recently, redactable blockchain has been proposed and leveraged in a wide range of real systems for its unique properties of decentralization, traceability, and transparency while ensuring controllable on-chain data redaction. However, the development of redactable blockchain is now obstructed by three limitations, which are data privacy breaches, high communication overhead, and low searching efficiency, respectively. In this paper, we propose PriChain, the first efficient privacy-preserving fine-grained redactable blockchain in decentralized settings. PriChain provides data owners with rights to control who can read and redact on-chain data while maintaining downward compatibility, ensuring the one who can redact will be able to read. Specifically, inspired by the concept of multi-authority attribute-based encryption, we utilize the isomorphism of the access control tree, realizing fine-grained redaction mechanism, downward compatibility, and collusion resistance. With the newly designed structure, PriChain can realize O（n） communication and storage overhead compared to prior O（n2） schemes. Furthermore, we integrate multiple access trees into a tree-based dictionary, optimizing searching efficiency. Theoretical analysis proves that PriChain is secure against the chosen-plaintext attack and has competitive complexity. The experimental evaluations show that PriChain realizes 10× efficiency improvement of searching and 100× lower communication and storage overhead on average compared with existing schemes.

关键词： Resistance Access control Data privacy Dictionaries Blockchains Encryption Complexity theory Usability Protection

Deep learning-based software engineering: progress,challenges, and opportunities

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Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG school of Journalism and communication Sun Yat-sen University school of Software Technology Zhejiang University school of Software engineering Sun Yat-sen University school of Software Dalian University of Technology school of computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University school of computer Science and engineering Beihang University Institute of Information engineering Chinese Academy of Sciences school of computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University school of computer and Information Technology Beijing Jiaotong University school of computer Science and Technology Harbin Institute of Technology school of computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

Enhanced rate capability and cycle stability of Ti2C MXene for sodium storage through an aniline molecules welding strategy

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Tungsten 2025年第1期7卷 161-171页

作者： Hao Chen Ya-Qin Wang Dong-Ting Zhang Bei Zhao Min-Peng Li Chen-Yang Li Tian-Peng Xu Mao-Cheng Liu State Key Laboratory of Advanced Processing and Recycling of Non-Ferrous Metals Lanzhou University of Technology school of Materials Science and engineering Lanzhou University of Technology school of computer and communication Technology Lanzhou University of Technology

MXenes obtained significant attention in the field of energy storage devices due to their characteristic layered structure,modifiable surface functional groups,large electrochemically active surface,and regulable interlayer ***,the self-restacking and sluggish ions diffusion kinetics performance of MXenes during the alkali metal ions insertion/extraction process severely impedes their cycle stability and rate *** paper proposes an aniline molecule welding strategy for welding p-phenylenediamine（PPDA） into the interlayers of Ti2C through a dehydration condensation *** welded PPDA molecules can contribute pillar effect to the layered structure of *** pillar effect effectively maintains the structural stability during the sodium ions insertion/extraction process and effectively expands the interlayer spacing of Ti2C from 1.16 to 1.38 nm,thereby enhancing ions diffusion kinetics performance and improving the long-term cycle *** Ti2C-PPDA demonstrates outstanding Na+storage capability,exhibiting a specific capacity of 100.2 mAh·g-1at a current density of 0.1 A·g-1over 960 cycles and delivering a remarkable rate capability 81.2 mAh·g-1at a current density of 5 A·*** study demonstrates that expanding interlayer spacing is a promising strategy to enhance the Na+storage capacity and improve long-term cycling stability,which provides significant guidance for the design of two-dimensional Na+storage materials with high-rate capability and cycle stability.

关键词： Diffusion kinetics Expanding interlayer spacing Rate capability Sodium ions storage Ti2C

Partial multi-label learning via label-specific feature corrections

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Science China(Information Sciences) 2025年第03期68卷 95-109页

作者： Jun-Yi HANG Min-Ling ZHANG school of computer Science and engineering Southeast University Key Laboratory of computer Network and Information Integration(Southeast University) Ministry of Education

Partial multi-label learning（PML） allows learning from rich-semantic objects with inaccurate annotations, where a set of candidate labels are assigned to each training example but only some of them are valid. Existing approaches rely on disambiguation to tackle the PML problem, which aims to correct noisy candidate labels by recovering the ground-truth labeling information ahead of prediction model induction. However, this dominant strategy might be suboptimal as it usually needs extra assumptions that cannot be fully satisfied in real-world scenarios. Instead of label correction, we investigate another strategy to tackle the PML problem, where the potential ambiguity in PML data is eliminated by correcting instance features in a label-specific manner. Accordingly, a simple yet effective approach named PASE, i.e., partial multi-label learning via label-specific feature corrections, is proposed. Under a meta-learning framework, PASElearns to exert label-specific feature corrections so that potential ambiguity specific to each class label can be eliminated and the desired prediction model can be induced on these corrected instance features with the provided candidate labels. Comprehensive experiments on a wide range of synthetic and real-world data sets validate the effectiveness of the proposed approach.

关键词： machine learning multi-label learning partial multi-label learning label-specific features feature correction

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Unmasking Social Robots’Camouflage:A GNN-Random Forest Framework for Enhanced Detection

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computers, Materials & Continua 2025年第1期82卷 467-483页

作者： Weijian Fan Chunhua Wang Xiao Han Chichen Lin school of Data Science and Intelligent Media Communication University of ChinaBeijing100024China school of computer and Cyber Sciences Communication University of ChinaBeijing100024China Institute of communication Studies Communication University of ChinaBeijing100024China State Key Laboratory of Media Convergence and communication Communication University of ChinaBeijing100024China

The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content *** robot detection has emerged as a pivotal yet intricate task,aimed at mitigating the dissemination of misleading *** graphbased approaches have attained remarkable performance in this realm,they grapple with a fundamental limitation:the homogeneity assumption in graph convolution allows social robots to stealthily evade detection by mingling with genuine human *** unravel this challenge and thwart the camouflage tactics,this work proposed an innovative social robot detection framework based on enhanced HOmogeneity and Random Forest(HORFBot).At the core of HORFBot lies a homogeneous graph enhancement strategy,intricately woven with edge-removal techniques,tometiculously dissect the graph intomultiple revealing ***,leveraging the power of contrastive learning,the proposed methodology meticulously trains multiple graph convolutional networks,each honed to discern nuances within these tailored *** culminating stage involves the fusion of these feature-rich base classifiers,harmoniously aggregating their insights to produce a comprehensive detection *** experiments on three social robot detection datasets have shown that this method effectively improves the accuracy of social robot detection and outperforms comparative methods.

关键词： Social robot detection graph neural networks random forest homophily heterophily