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20th International Conference on Information Security and Cryptology, Inscrypt 2024

作者： Chen, Yanqi Li, Ting Sun, Yao Key Laboratory of Cyberspace Security Defense Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Laboratory for Advanced Computing and Intelligence Engineering Wuxi China

ISBN: (纸本)9789819647330

The cube attack is a powerful cryptanalysis technique used against stream ciphers. It enables the retrieval of secret key information by computing the values of superpolys, with unknown secret key bits as variables. A practical key-recovery attack seeks to recover all key bits within a reasonable time complexity. The complexity of such attacks typically involves two main components: (1) the complexity of calculating the superpoly values under the real key, which depends on the size of the mother cube, and (2) the complexity of solving the superpoly system, guess-and-determine techniques are often used to solve the system especially when superpolys are nonlinear. In this paper, we improve the best-known practical key-recovery attack on Trivium by enhancing the techniques used in these two areas. First, we introduce a heuristic method to search for good mother cubes, enabling many balanced superpolys to recover. Second, we propose an efficient MILP-based model to search for a minimal number of guessed variables to solve the balanced superpoly systems, thus reducing the complexity of solving the system. With these advancements, we achieve key-recovery attacks on the 830- and 832-round Trivium within practical time complexity, surpassing the previous best result of 825 rounds. Additionally, we applied our new model to attack ACORN with 128-bit keys, achieving practical key-recovery attacks on the 507- and 611-round versions, compared to the previous highest of 477 rounds. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Heuristic methods

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Open Set Recognition for Encrypted Traffic using Intra-class Partition and Boundary Sample Generation 5

Open Set Recognition for Encrypted Traffic using Intra-class...

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5th IEEE advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2022

作者： Li, Xue Fei, Jinlong Qi, Zan Lv, Zhuo Jiang, Heng PLA Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China PLA Information Engineering University National Digital Switching System Engineering Technological Research Center Zhengzhou China

ISBN: (纸本)9781665479677

Existing deep learning-based encrypted traffic recognition methods can achieve high precision identification performance while protecting user privacy, but almost all of them focus on closed sets, in which training data and test data come from the same label space. However, the real network environment is open, and it is necessary for traffic identification systems to deal with previously unseen categories. To classify known categories at a fine granularity and identify unknown ones, we propose a novel open-set recognition method for encrypted traffic. The decision boundary sample generation method based on constrained Generative Adversarial Networks is presented to generate samples from low-density regions in the known data space. Furthermore, an end-to-end open-set classifier is built using the accurate and diverse simulative samples of unknown classes through intra-class partition and boundary sample generation. Finally, the effectiveness of the proposed method is validated through numerical experiments. © 2022 IEEE.

关键词： Deep learning

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Blockchain Privacy Protection Based on Post Quantum Threshold Algorithm

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Computers, Materials & Continua 2023年第7期76卷 957-973页

作者： Faguo Wu Bo Zhou Jie Jiang Tianyu Lei Jiale Song Institute of Artificial Intelligence Beihang UniversityBeijing100191China Zhongguancun Laboratory Beijing100094China Key Laboratory of Mathematics Informatics and Behavioral Semantics(LMIB)Beihang UniversityBeijing100191China Bejing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang UniversityBeijing100191China LMIB and School of Mathematical Sciences Beihang UniversityBeijing100191China

With the rapid increase in demand for data trustworthiness and data security,distributed data storage technology represented by blockchain has received unprecedented *** technologies have been suggested for various uses because of their remarkable ability to offer decentralization,high autonomy,full process traceability,and tamper *** enables the exchange of information and value in an untrusted *** has been a significant increase in attention to the confidentiality and privacy preservation of blockchain *** data privacy is a critical concern in cryptography,and one of the most important protocols used to achieve this is the secret-sharing *** dividing the secret into shares and distributing them among multiple parties,no one can access the secret without the cooperation of the other ***,Attackers with quantum computers in the future can execute Grover’s and Shor’s algorithms on quantum computers that can break or reduce the currently widely used ***,centralized management of keys increases the risk of key *** paper proposed a post-quantum threshold algo-rithm to reduce the risk of data privacy leakage in blockchain *** algorithm uses distributed key management technology to reduce the risk of individual node private key leakage and provide post-quantum *** proposed privacy-preserving cryptographic algorithm provides a post-quantum threshold architecture for managing data,which involves defining users and interaction processes within the *** paper applies a linear secret-sharing solution to partition the private key of the Number Theory Research Unit(NTRU)algorithm into n *** constructs a t–n threshold that allows recovery of the plaintext only when more than t nodes participate in *** characteristic of a threshold makes the scheme resistant to collusion attacks from members whose combined credibility is less than the

关键词： Blockchain post-quantum cryptography threshold cryptography privacy protection

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MFN: Explainable DNA triple helixes Stabilized Design based on mCGR and flow network

MFN: Explainable DNA triple helixes Stabilized Design based ...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Wen, Xiaoru Sun, Lijun Xie, Lei Zheng, Yanfen Cao, Ben Wang, Bin Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian China Dalian University of Technology School of Computer Science and Technology Dalian China

ISBN: (纸本)9798350386226

DNA triple helix structure, as a highly specific gene targeting tool, enable gene regulation by precisely identifying and binding to target DNA sequences. However, the limits of design quality and efficiency affect their wide application in gene therapy. Therefore, in this paper, we propose an antiparallel DNA triple helixes design method-MFN based on matrix chaotic game representation (mCGR) and flow network. Leveraging the structural characteristics of DNA sequences, this method employs the mCGR algorithm to construct an initial matrix, generating a set of DNA sequences that conform to foundational constraints. Then, these sequences are mapped as stream network nodes to screen crosstalk structures by path search, and the whole process is observable and interpretable. Experimental results show that MFN significantly improves the design efficiency of triple helix structure and reduces crosstalk phenomenon. Wet experiments further verify the effectiveness of the method. In summary, MFN achieves an efficient and high-quality design of DNA triple helixes and provides a new idea for targeted gene therapy. © 2024 IEEE.

关键词： Crosstalk

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Convergence of Physics-Informed Neural Networks Applied to Linear Second-Order Elliptic Interface Problems

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Communications in Computational Physics 2023年第2期33卷 596-627页

作者： Sidi Wu Aiqing Zhu Yifa Tang Benzhuo Lu State Key Laboratory of Scientific and Engineering Computing National Center for Mathematics and Interdisciplinary SciencesAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China.

With the remarkable empirical success of neural networks across diverse scientific disciplines,rigorous error and convergence analysis are also being developed and ***,there has been little theoretical work focusing on neural networks in solving interface *** this paper,we perform a convergence analysis of physics-informed neural networks(PINNs)for solving second-order elliptic interface ***,we consider PINNs with domain decomposition technologies and introduce gradient-enhanced strategies on the interfaces to deal with boundary and interface jump *** is shown that the neural network sequence obtained by minimizing a Lipschitz regularized loss function converges to the unique solution to the interface problem in H2 as the number of samples *** experiments are provided to demonstrate our theoretical analysis.

关键词： Elliptic interface problems generalization errors convergence analysis neural networks.

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ThickV-Stain: Unprocessed Thick Tissues Virtual Staining for Rapid Intraoperative Histology 7

ThickV-Stain: Unprocessed Thick Tissues Virtual Staining for...

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7th International Conference on Medical Imaging with Deep Learning, MIDL 2024

作者： Shi, Lulin Hou, Xingzhong Wong, Ivy H.M. Chan, Simon C.K. Chen, Zhenghui Lo, Claudia T.K. Wong, Terence T.W. Translational and Advanced Bioimaging Laboratory Department of Chemical and Biological Engineering The Hong Kong University of Science and Technology Hong Kong State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

Virtual staining has shown great promise in realizing a rapid and low-cost clinical alternative for pathological examinations, eliminating the need for chemical reagents and laborious staining procedures. However, most of the previous studies mainly focus on thin slice samples, which still require tissue sectioning and are unsuitable for intraoperative use. In this paper, we propose a multi-scale model to virtually stain label-free and slide-free biological tissues, allowing hematoxylin- and eosin- (H&E) staining generation in less than a minute for an image with 100 million pixels. We name this ThickV-Stain model, specifically developed to virtually stain intricated and unprocessed thick tissues. We harness the ability of a multi-scale network to encourage the model to capture multiple-level micromorphological characteristics from low-resolution images. Experimental results highlight the advantages of our method for virtual staining on unprocessed thick samples. We also show the effectiveness of ThickV-Stain on thin sections, showing generalizability to other clinical workflows. The proposed method enables us to obtain virtually stained images from unstained samples within minutes and can be seamlessly integrated with downstream pathological analysis tasks, providing an efficient alternative scheme for intraoperative assessment as well as general pathological examination. © 2024 CC-BY 4.0, L. Shi, X. Hou, I.H.M. Wong, S.C.K. Chan, Z. Chen, C.T.K. Lo & T.T.W. Wong.

关键词： Tissue

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Boosting cationic and anionic redox activity of Li-rich layered oxide cathodes via Li/Ni disordered regulation

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Journal of Energy Chemistry 2025年第1期100卷 533-543页

作者： Zewen Liu Zhen Wu Hao Wang Xudong Zhang Yuanzhen Chen Yongning Liu Shengwu Guo Shenghua Chen Yanli Nan Yan Liu State Key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina School of Materials Science and Engineering Xi’an University of Architecture and TechnologyXi’an 710055ShaanxiChina Hefei Advanced Computing Center Operation Management Corp Ltd Hefei 230088AnhuiChina Network Information Center Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina

Lithium-rich layered oxides (LLOs) are increasingly recognized as promising cathode materials for nextgeneration high-energy-density lithium-ion batteries (LIBs).However,they suffer from voltage decay and low initial Coulombic efficiency (ICE) due to severe structural degradation caused by irreversible O ***,we introduce a three-in-one strategy of increasing Ni and Mn content,along with Li/Ni disordering and TM–O covalency regulation to boost cationic and anionic redox activity simultaneously and thus enhance the electrochemical activity of *** target material,Li_(1.2)Ni_(0.168)Mn_(0.558)Co_(0.074)O_(2)(L1),exhibits an improved ICE of 87.2%and specific capacity of 293.2 mA h g^(-1)and minimal voltage decay of less than 0.53 m V cycle-1over 300 cycles at 1C,compared to Li_(1.2)Ni_(0.13)Mn_(0.54)Co_(0.13)O_(2)(Ls)(274.4 mA h g^(-1)for initial capacity,73.8%for ICE and voltage decay of 0.84 mV/cycle over 300 cycles at 1C).Theoretical calculations reveal that the density of states (DOS) area near the Fermi energy level for L1 is larger than that of Ls,indicating higher anionic and cationic redox reactivity than ***,L1 exhibits increased O-vacancy formation energy due to higher Li/Ni disordering of 4.76%(quantified by X-ray diffraction Rietveld refinement) and enhanced TM–O covalency,making lattice O release more difficult and thus improving electrochemical *** increased Li/Ni disordering also leads to more Ni^(2+)presence in the Li layer,which acts as a pillar during Li+de-embedding,improving structural *** research not only presents a viable approach to designing low-Co LLOs with enhanced capacity and ICE but also contributes significantly to the fundamental understanding of structural regulation in high-performance LIB cathodes.

关键词： Low-Co Li-rich layered oxides Li/Ni disordering TM-O covalency Cationic and anionic redox activity

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Duen: Dynamic Ensemble Handling Class Imbalance in Network Intrusion Detection

SSRN

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SSRN 2023年

作者： Ren, Huajuan Tang, Yonghe Dong, Weiyu Ren, Shuai Jiang, Liehui State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Henan Province Key Laboratory of Cyberspace Situation Awareness Zhengzhou China

Network intrusion detection is an important technology for maintaining cybersecurity. The inherent difficulties co-existing in network traffic datasets, such as class imbalance, class overlapping, and noises, limit detection accuracy. However, existing research has only focused on the disproportion between classes. Considering these difficulties, a novel ensemble method is proposed for network intrusion detection called DUEN. Dynamic undersampling is incorporated into the Boosting framework to provide a relatively balanced training subset for each iteration to achieve a strong ensemble. In dynamic undersampling, the sampling number is determined based on data distribution learning to cope with the small sample overfitting problem caused by simple undersampling. The concept of classification hardness for integrating data difficulties is employed to identify samples as easy, borderline, and noisy types. Boundary samples importance enhancement mechanism is proposed for the undersampling process, preventing overfitting noise samples. The proposed sampling method does not involve distance calculation, achieving very low computational costs. Experiments show the effectiveness of DUEN with multiclass classification on two widely used datasets for evaluating intrusion detection. DUEN has high detection accuracy for both minority and majority class samples and a significant time efficiency advantage. The Macro.F1 of the NSL-KDD and UNSW-NB15 datasets reached 70.7% and 50.1%, achieving 6.32% and 1.42% improvement compared with the suboptimal network intrusion detection methods. Moreover, the experimental analysis shows that DUEN has strong generalization and robustness to noise samples. © 2023, The Authors. All rights reserved.

关键词： Intrusion detection

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Heterostructured Mn_(3)O_(4)-MnS Multi-Shelled Hollow Spheres for Enhanced Polysulfide Regulation in Lithium-Sulfur Batteries

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Energy & Environmental Materials 2023年第6期6卷 436-444页

作者： Bin Qin Qun Wang Weiqi Yao Yifei Cai Yuhan Chen Pengcheng Wang Yongchun Zou Xiaohang Zheng Jian Cao Junlei Qi Wei Cai State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China College of Chemistry and Chemical Engineering Taiyuan University of TechnologyTaiyuan 030024China State Key Laboratory of Chemical Engineering East China University of Science and TechnologyShanghai 200237China Department of Mechanical Engineering City University of Hong KongHong KongChina Center of Analysis Measurement and Computing Harbin Institute of TechnologyHarbin 150001China School of Materials Science and Engineering Harbin Institute of Technology Harbin 150001China

Constructing heterojunctions and hollow multi-shelled structures can render materials with fascinating physicochemical properties,and have been regarded as two promising strategies to overcome the severe shuttling and sluggish kinetics of polysulfide in lithium-sulfur(Li-S)***,a single strategy can only take limited *** catalytic hosts with synergistic effects are urgently ***,Mn_(3)O_(4)-MnS heterogeneous multi-shelled hollow spheres are meticulously designed by controlled sulfuration of Mn2O3 hollow spheres,and then applied as advanced encapsulation hosts for Li-S *** from the separated spatial confinement by hollow multi-shelled structure,ample exposed active sites and built-in electric field by heterogeneous interface,and synergistic effects between Mn_(3)O_(4)(strong adsorption)and MnS(fast conversion)components,the assembled battery achieves prominent rate capability and decent cyclability(0.016%decay per cycle at 2 C,1000 cycles).More crucially,satisfactory areal capacity reaches up to 7.1 mAh cm^(-2)even with high sulfur loading(8.0 mg cm^(-2))and lean electrolyte(E/S=4.0 pL mg^(-1))*** work will provide inspiration for the rational design of hollow multi-shelled heterostructure for various electrocatalysis applications.

关键词： electrocatalyst heterojunction host hollow multi-shelled structure Li-S battery Mn_(3)O_(4)-MnS

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Asymmetric scattering behaviors of spin wave dependent on magnetic vortex chirality

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Chinese Physics B 2023年第10期32卷 635-640页

作者：张雪枫沈帝虎马晓萍宋成于海明朴红光 Hubei Engineering Research Center of Weak Magnetic-Field Detection China Three Gorges UniversityYichang 443002China Department of Physics College of ScienceYanbian UniversityYanji 133002China Key Laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Fert Beijing Institute School of Integrated Circuit Science and EngineeringBeijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China

We investigate asymmetric spin wave scattering behaviors caused by vortex chirality in a cross-shaped ferromagnetic system by using the micromagnetic *** the system,four scattering behaviors are found:(i)asymmetric skew scattering,depending on the polarity of vortex core,(ii)back scattering(reflection),depending on the vortex core stiffness,(iii)side deflection scattering,depending on structural symmetry of the vortex circulation,and(iv)geometrical scattering,depending on waveguide *** first and second scattering behaviors are attributed to nonlinear topological magnon spin Hall effect related to magnon spin-transfer torque effect,which has value for magnonic exploration and application.

关键词： magnonics magnetic vortex spin wave magnetic chirality

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