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2021 International Conference on Computer Network Security and Software engineering, CNSSE 2021

作者： Zhao, Chenxia Kang, Fei Yang, Ju Shu, Hui Zhengzhou University Zhengzhou Henan450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan450001 China

Aiming at the cryptographic algorithm that may be contained in the binary program, combined with existing research results, several cryptographic algorithm identification techniques are analyzed, including control flow graphs, data flow graphs, feature matching, selection of command statistical attributes, and semantic-based behavior analysis. The recognition effects of related technologies are discussed respectively. © Published under licence by IOP Publishing Ltd.

关键词： Graphic methods

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Efficient Sparse Attention needs Adaptive Token Release

arXiv

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arXiv 2024年

作者： Zhang, Chaoran Zou, Lixin Luo, Dan Tang, Min Luo, Xiangyang Li, Zihao Li, Chenliang Wuhan University China Lehigh University United States Monash University Australia State Key Lab of Mathematical Engineering and Advanced Computing China

In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide array of text-centric tasks. However, their 'large' scale introduces significant computational and storage challenges, particularly in managing the key-value states of the transformer, which limits their wider applicability. Therefore, we propose to adaptively release resources from caches and rebuild the necessary key-value states. Particularly, we accomplish this by a lightweight controller module to approximate an ideal top-K sparse attention. This module retains the tokens with the highest top-K attention weights and simultaneously rebuilds the discarded but necessary tokens, which may become essential for future decoding. Comprehensive experiments in natural language generation and modeling reveal that our method is not only competitive with full attention in terms of performance but also achieves a significant throughput improvement of up to 221.8%. The code for replication is available on the https://***/WHUIR/ADORE. © 2024, CC BY.

关键词： Modeling languages

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A Multi-Variant Voting Algorithm Based on Dynamic Feedback 2

A Multi-Variant Voting Algorithm Based on Dynamic Feedback

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2nd International Conference on Computer Communication and Network Security, CCNS 2021

作者： Yuwen, Shao Zheng, Zhang Bingzheng, Li Xinsheng, Ji State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China National Digital Switching System Engineering Technological RD Center Zhengzhou China

ISBN: (纸本)9781665427111

Multi-variant execution framework can protect software security. For the problem of performance loss caused by too many voting times in the existing multi-variant execution framework, this paper proposes a multi-variant voting algorithm based on dynamic feedback, which can make the multi-variant continuously improve its corresponding voting strategy at runtime. Using this algorithm, the multi-variant can get a stable voting range, reduce the number of voting, and effectively improve the performance of multi-variant. © 2021 IEEE.

关键词： Runtime Heuristic algorithms Software algorithms Network security Software Computer security

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A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data

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National Science Review 2025年第5期12卷 362-381页

作者： Yurun Lu Dan Liu Zhongming Liang Rui Liu Pei Chen Yitong Liu Jiachen Li Zhanying Feng Lei M.Li Bin Sheng Weiping Jia Luonan Chen Huating Li Yong Wang Center for Excellence in Mathematical Sciences National Center for Mathematics and Interdisciplinary Sciences Hua Loo-Keng Center for Mathematical Sciences Key Laboratory of Management Decision and Information System Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematics University of Chinese Academy of SciencesChinese Academy of Sciences Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences BGI-Research School of Mathematics South China University of Technology Department of Statistics Department of Biomedical Data Science Bio-X ProgramStanford University Department of Computer Science and Engineering Shanghai Jiao Tong University State Key Laboratory of Cell Biology Center for Excellence in Molecular Cell Science Shanghai Institute of Biochemistry and Cell Biology Chinese Academy of Sciences Guangdong Institute of Intelligence Science and Technology Pazhou Laboratory (Huangpu)

Continuous glucose monitoring(CGM) technology has grown rapidly to track real-time blood glucose levels and trends with improved sensor accuracy. The ease of use and wide availability of CGM will facilitate safe and effective decision making for diabetes management. Here, we developed an attention-based deep learning model, CGMformer, pretrained on a well-controlled and diverse corpus of CGM data to represent individual's intrinsic metabolic state and enable clinical applications. During pretraining, CGMformer encodes glucose dynamics including glucose level, fluctuation, hyperglycemia, and hypoglycemia into latent space with self-supervised learning. It shows generalizability in imputing glucose value across five external datasets with different populations and metabolic states(MAE = 3.7 mg/d L). We then fine-tuned CGMformer towards a diverse panel of downstream tasks in the screening of diabetes and its complications using task-specific data, which demonstrated a consistently boosted predictive accuracy over direct fine-tuning on a single task(AUROC = 0.914 for type 2 diabetes(T2D) screening and 0.741 for complication screening). By learning an intrinsic representation of an individual's glucose dynamics,CGMformer classifies non-diabetic individuals into six clusters with elevated T2D risks, and identifies a specific cluster with lean body-shape but high risk of glucose metabolism disorders, which is overlooked by traditional glucose measurements. Furthermore, CGMformer achieves high accuracy in predicting an individual's postprandial glucose response with dietary modelling(Pearson correlation coefficient = 0.763)and helps personalized dietary recommendations. Overall, CGMformer pretrains a transformer neural network architecture to learn an intrinsic representation by borrowing information from a large amount of daily glucose profiles, and demonstrates predictive capabilities fine-tuned towards a broad range of downstream applications, holding promise for the ear

关键词： pretrained model diabetes continuous glucose monitoring glucose dynamics

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Tuning 2D magnetism in Fe3+XGeTe2 films by element doping

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National Science Review 2022年第6期9卷 163-170页

作者： Shanshan Liu Zihan Li Ke Yang Enze Zhang Awadhesh Narayan Xiaoqian Zhang Jiayi Zhu Wenqing Liu Zhiming Liao Masaki Kudo Takaaki Toriyama Yunkun Yang Qiang Li Linfeng Ai Ce Huang Jiabao Sun Xiaojiao Guo Wenzhong Bao Qingsong Deng Yanhui Chen Lifeng Yin Jian Shen Xiaodong Han Syo Matsumura Jin Zou Yongbing Xu Xiaodong Xu Hua Wu Faxian Xiu State Key Laboratory of Surface Physics and Department of Physics Fudan University Institute for Nanoelectronic Devices and Quantum Computing Fudan University College of Science University of Shanghai for Science and Technology Laboratory for Computational Physical Sciences(MOE) Fudan University Solid State and Structural Chemistry Unit Indian Institute of Science School of Electronic Science and Engineering Nanjing University Department of Physics University of Washington Department of Electronic Engineering Royal Holloway University of London Materials Engineering The University of Queensland Beijing Key Laboratory of Microstructure and Property of Advanced Materials Institute of Microstructure and Property of Advanced Materials Beijing University of Technology The Ultramicroscopy Research Center Kyushu University State Key Laboratory of ASIC and System School of Microelectronics Fudan University Collaborative Innovation Center of Advanced Microstructures Department of Applied Quantum Physics and Nuclear Engineering Kyushu University Centre for Microscopy and Microanalysis The University of Queensland Shanghai Research Center for Quantum Sciences

Two-dimensional（2D） ferromagnetic materials have been discovered with tunable magnetism and orbital-driven nodal-line features. Controlling the 2D magnetism in exfoliated nanoflakes via electric/magnetic fields enables a boosted Curie temperature（TC） or phase transitions. One of the challenges, however, is the realization of high TC2D magnets that are tunable, robust and suitable for large scale fabrication. Here, we report molecular-beam epitaxy growth of wafer-scale Fe3+XGeTe2films with TCabove room temperature. By controlling the Fe composition in Fe3+XGeTe2, a continuously modulated TCin a broad range of 185–320 K has been achieved. This widely tunable TCis attributed to the doped interlayer Fe that provides a 40% enhancement around the optimal composition X = 2. We further fabricated magnetic tunneling junction device arrays that exhibit clear tunneling signals. Our results show an effective and reliable approach, i.e. element doping, to producing robust and tunable ferromagnetism beyond room temperature in a large-scale 2D Fe3+XGeTe2fashion.

关键词： 2D ferromagnetic material Fe3+XGeTe2 film element doping above room temperature TC tunability

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HRPDF: A Software-Based Heterogeneous Redundant Proactive Defense Framework for Programmable Logic Controller

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Journal of Computer Science & Technology 2021年第6期36卷 1307-1324页

作者： Ke Liu Jing-Yi Wang Qiang Wei Zhen-Yong Zhang Jun Sun Rong-Kuan Ma Rui-Long Deng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China College of Computer Science and Technology Guizhou UniversityGuiyang 550025China School of Information Systems Singapore Management UniversitySingapore 689867Singapore

Programmable logic controllers(PLCs)play a critical role in many industrial control systems,yet face increasingly serious cyber *** this paper,we propose a novel PLC-compatible software-based defense mechanism,called Heterogeneous Redundant Proactive Defense Framework(HRPDF).We propose a heterogeneous PLC architecture in HRPDF,including multiple heterogeneous,equivalent,and synchronous runtimes,which can thwart multiple types of attacks against PLC without the need of external *** ensure the availability of PLC,we also design an inter-process communication algorithm that minimizes the overhead of *** implement a prototype system of HRPDF and test it in a real-world PLC and an OpenPLC-based device,*** results show that HRPDF can defend against multiple types of attacks with 10.22%additional CPU and 5.56%additional memory overhead,and about 0.6 ms additional time overhead.

关键词： industrial control system programmable logic controller proactive defense heterogeneous redundant architecture

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A Cross-Platform Instant Messaging User Association Method Based on Spatio-temporal Trajectory 8th

A Cross-Platform Instant Messaging User Association Method B...

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8th International Conference on Artificial Intelligence and Security , ICAIS 2022

作者： Zhou, Pei Luo, Xiangyang Du, Shaoyong Li, Lingling Yang, Yang Liu, Fenlin School of Cyber Science and Engineering Zhengzhou University Zhengzhou450000 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Intelligent Engineering Zhengzhou University of Aeronautics Zhengzhou450000 China School of Computing and Information Systems Singapore Management University Singapore188065 Singapore

ISBN: (纸本)9783031067600

The current research on cross-platform instant messaging user association is mainly divided into two categories: based on user attributes and based on user behavior. Methods based on user attributes mainly identify users through multiple attributes such as user name and multi-platform user information association based on cell phone number, but user association is not possible when multi-platform user information is inconsistent and users do not grant their address book permissions. Methods based on user behavior mainly calculate the similarity between user trajectories features such as geographic location frequency and co-occurrence, but this method lacks the user’s information, which leads to the inability to fully excavate the sequential features of the trajectory and affects the accuracy of trajectory matching. In order to solve this problem, this paper proposes a cross-platform instant messaging user association algorithm based on temporal trajectories (CPTrajst). We firstly place probes in the area where the target may appear so as to obtain user information, gets user trajectory, then processes the trajectory and performs two trajectory matches, finally associate users of different platforms whose trajectories match, thus increasing the accuracy and reliability of cross-platform instant messaging user association. We conducts specific experiments for users of WeChat and Momo, the most commonly used instant messengers in China. The results show that we can achieve reliable association for these two types of instant messaging users and the user association accuracy can reach 99.5%, which is better than the existing user association algorithms based on trajectory matching. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Trajectories

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KextFuzz: fuzzing macOS Kernel EXTensions on apple silicon via exploiting mitigations 23

KextFuzz: fuzzing macOS Kernel EXTensions on apple silicon v...

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Proceedings of the 32nd USENIX Conference on Security Symposium

作者： Tingting Yin Zicong Gao Zhenghang Xiao Zheyu Ma Min Zheng Chao Zhang Tsinghua University and Ant Group State Key Laboratory of Mathematical Engineering and Advanced Computing Hunan University Tsinghua University Ant Group Tsinghua University and Zhongguancun Laboratory

ISBN: (纸本)9781939133373

macOS drivers, i.e., Kernel EXTensions (kext), are attractive attack targets for adversaries. However, automatically discovering vulnerabilities in kexts is extremely challenging because kexts are mostly closed-source, and the latest macOS running on customized Apple Silicon has limited tool-chain support. Most existing static analysis and dynamic testing solutions cannot be applied to the latest macOS. In this paper, we present the first smart fuzzing solution KextFuzz to detect bugs in the latest macOS kexts running on Apple Silicon. Unlike existing driver fuzzing solutions, KextFuzz does not require source code, execution traces, hypervisors, or hardware features (e.g., coverage tracing) and thus is universal and practical. We note that macOS has deployed many mitigations, including pointer authentication, code signature, and userspace kernel layer wrappers, to thwart potential attacks. These mitigations can provide extra knowledge and resources for us to enable kernel fuzzing. KextFuzz exploits these mitigation schemes to instrument the binary for coverage tracking, test privileged kext code that is guarded and infrequently accessed, and infer the type and semantic information of the kext interfaces. KextFuzz has found 48 unique kernel bugs in the macOS kexts and got five CVEs. Some bugs could cause severe consequences like non-recoverable denial-of-service or damages.

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Thermally Evaporated ZnSe for Efficient and Stable Regular/Inverted Perovskite Solar Cells by Enhanced Electron Extraction

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Energy & Environmental Materials 2023年第5期6卷 440-448页

作者： Xin Li Guibin Shen Xin Ren Ng Zhiyong Liu Yun Meng Yongwei Zhang Cheng Mu Zhi Gen Yu Fen Lin Solar Energy Research Institute of Singapore(SERIS) National University of SingaporeSingapore 117574Singapore Key Laboratory of Advanced Light Conversion Materials and Biophotonics Department of ChemistryRenmin University of ChinaBeijing 100872China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Shandong Provincial Engineering and Technical Center of Light Manipulation and Shandong Provincial Key Laboratory of Optics and Photonic Devices School of Physics and ElectronicsShandong Normal UniversityJinan 250014China Institute of High Performance Computing A^(*)STARSingapore 138632Singapore

Electron transport layers(ETLs)are crucial for achieving efficient and stable planar perovskite solar cells(PSCs).Reports on versatile inorganic ETLs using a simple film fabrication method and applicability for both low-cost planar regular and inverted PSCs with excellent efficiencies(>22%)and high stability are very ***,we employ a novel inorganic ZnSe as ETL for both regular and inverted PSCs to improve the efficiency and stability using a simple thermal evaporation *** TiO_(2)-ZnSe-FAPbl_(3)heterojunction could be formed,resulting in an improved charge collection and a decreased carrier recombination further proved through theoretical *** optimized regular PSCs based on TiO_(2)/ZnSe have achieved 23.25%efficiency with negligible *** addition,the ZnSe ETL can also effectively replace the unstable bathocuproine(BCP)in inverted ***,the ZnSe-based inverted device realizes a champion efficiency of 22.54%.Moreover,the regular device comprising the TiO_(2)/ZnSe layers retains 92%of its initial PCE after 10:00 h under 1 Sun continuous illumination and the inverted device comprising the C_(60)/ZnSe layers maintains over 85%of its initial PCE at 85℃for 10:00 *** highlights one of the best results among universal ETLs in both regular and inverted perovskite photovoltaics.

关键词： high efficiency long-term stability planar regular/inverted perovskite solar cells thermal evaporation ZnSe electron transport layer

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BA-Audit: Blockchain-Based Public Auditing for Aggregated Data Sharing in Edge-Assisted IoT 1

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4th EAI International Conference on Security and Privacy in New computing Environments, SPNCE 2021

作者： Liu, Mingxi Lu, Ning Yin, Jingli Cheng, Qingfeng Shi, Wenbo School of Computer Science and Engineering Northeastern University Shenyang China School of Computer Science and Technology Xidian University Xi’an China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Strategic Support Force Information Engineering University Zhengzhou China

ISBN: (数字)9783030967918

ISBN: (纸本)9783030967901

With the massive placement of sensors leading to a surge in IoT data, it is wise for system administrators to use data aggregation strategies to collect and share data in edge-assisted IoT scenarios because traditional methods will exhaust bandwidth resources. Users need to verify the integrity of aggregated data to ensure security sharing. However, existing data auditing technologies are disabled because aggregate data has no metadata. This paper proposes a blockchain-based auditing scheme for aggregated data to achieve efficient and secure data sharing. First, we design a hash index balanced tree (HIBT) to reduce the computational expense of signature retrieval. Then, we propose an audit protocol to protect aggregated data immutability. Also, we provide security and performance analysis at the end of the paper. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Blockchain

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