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Digital Society and Intelligent Systems (DSInS), International Conference on

作者： Zheming Li Hengwei Zhang Junqiang Ma Bo Yang Chenwei Li Jingwen Li State Key Laboratory of Mathematical Engineering and Advanced Computing Key Laboratory of Information Security of Henan Provincial Zhengzhou China PLA Army Beijing China

ISBN: (纸本)9781665406314

Convolutional neural network models are fragile to adversarial examples. Adding disturbances that humans cannot observe in clean images can make the model classification error. Among the adversarial attack methods, white-box attacks have achieved a high attack success rate, but the "overfitting" between the adversarial examples and the model has led to a low success rate of black-box attacks. To this end, this paper introduces the data augmentation method into the adversarial examples generation process, establishes a probability model to perform random rotation transformation on clean images, improves the mobility of adversarial examples, and improves the success rate of adversarial examples under black-box setting. The experimental results on ImageNet show that the RO-MI-FGSM method we proposed has a stronger attack effect, achieving a black-box attack success rate up to 80.3%.

关键词： Solids Data models Convolutional neural networks Intelligent systems

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Low dose PET image reconstruction using diffusion sampling with posterior iterative correction

Low dose PET image reconstruction using diffusion sampling w...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： B. Qi R. Hu D. Wu N. Guo Q. Li H. Liu Department of Optical Engineering the State Key Laboratory of Modern Optical Instrumentation Zhejiang University Hangzhou China Massachusetts General Hospital/Harvard Medical School The Center for Advanced Medical Computing and Analysis Boston Massachusetts United States of America

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

Low dose PET image reconstruction is a crucial technique in functional imaging, addressing both patient safety and diagnostic needs by minimizing radioactive exposure. However, as dosage is reduced, the increasing noise makes reconstruction challenging. This study leverages a diffusion model in a pre-training mode to learn PET image priors from existing PET data, establishing a sampling framework for low-dose PET reconstruction. By constraining the sampling process with a data fidelity correction term through iterative reconstruction and implementing posterior iterative correction, we achieve 50x down-sampled PET reconstruction without the need for training with paired data. Experiments demonstrate that our method achieves excellent performance compared with MLEM, EMTV and DeepPET method.

关键词： Training Microwave integrated circuits Semiconductor detectors Noise Diffusion models Safety Iterative methods

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NGDcrm:a numeric graph dependency-based conflict resolution method for knowledge graph

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High Technology Letters 2021年第2期27卷 153-162页

作者： Ma Jiangtao Wang Yanjun Chen Xueting Qiao Yaqiong College of Computer and Communication Engineering Zhengzhou Universily of Lighl IndustryZhengzhou 450002P.R.China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450002P.R.China School of Computer&Communication Engineering University of Science and Technology BeijingBeijing 100083P.R.China School of Information Engineering North China University of W ater Resources and Electric PowerZhengzhou 450046P.R.China

Knowledge graph(KG)conflict resolution is to solve knowledge conflicts problem in the construction of *** at the problem of KG conflict resolution,a KG conflict resolution algorithm NGDcrm is proposed,which is a numeric graph dependency-based conflict resolution *** utilizes the dependency graph to perform arithmetic calculation and predicate comparison of numerical entity knowledge in the *** first uses a parallel segmentation method to segment the KG;then,it extracts the features of the KG according to KG embedding;finally,it uses numerical graph dependencies to detect and correct the wrong facts in the KG based on the extracted *** experimental results on real data show that NGDcrm is better than the state-of-the-art knowledge conflict resolution *** them,the AUC value of NGDcrm on the DBpedia dataset is 15.4%higher than the state-of-the-art method.

关键词： dependency graph knowledge conflict resolution knowledge graph(KG) numeric graph dependency(NGD)

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SPECWANDS: An Efficient Priority-based Scheduler Against Speculation Contention Attacks

arXiv

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arXiv 2023年

作者： Tang, Bowen Wu, Chenggang Yew, Pen-Chung Zhang, Yinqian Xie, Mengyao Lai, Yuanming Kang, Yan Wang, Wei Wei, Qiang Wang, Zhe SKLP Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Zhongguancun Laboratory Beijing China Computer Science & Engineering Department The University of Minnesota-Twin Cities MN55455 United States Department of Computer Science and Engineering The Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000 China

Transient Execution Attacks (TEAs) have gradually become a major security threat to modern high-performance processors. They exploit the vulnerability of speculative execution to illegally access private data, and transmit them through timing-based covert channels. While new vulnerabilities are discovered continuously, the covert channels can be categorised to two types: 1) Persistent Type, in which covert channels are based on the layout changes of buffering, e.g. through caches or TLBs;2) Volatile Type, in which covert channels are based on the contention of sharing resources, e.g. through execution units or issuing ports. The defenses against the persistent-type covert channels have been well addressed, while those for the volatile-type are still rather inadequate. Existing mitigation schemes for the volatile type such as Speculative Compression and Time-Division-Multiplexing will introduce significant overhead due to the need to stall the pipeline or to disallow resource sharing. In this paper, we look into such attacks and defenses with a new perspective, and propose a scheduling-based mitigation scheme, called SPECWANDS. It consists of three priority-based scheduling policies to prevent an attacker from transmitting the secret in different contention situations. SPECWANDS not only can defend against both inter-thread and intra-thread based attacks, but also can keep most of the performance benefit from speculative execution and resource-sharing. We evaluate its runtime overhead on SPEC 2017 benchmarks and realistic programs. The experimental results show that SPECWANDS has a significant performance advantage over the other two representative schemes. Copyright © 2023, The Authors. All rights reserved.

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Computer Information Science and Artificial Intelligence (CISAI), International Conference on

作者： Di Zhu Jianmin Pang Xin Zhou Wenjie Han Zhengzhou University Zhengzhou China Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665406932

As the mainstream of smart contract research, most Ethereum smart contracts do not open their source code, and the bytecode of smart contracts has attracted the attention of researchers. Based on the similarity measurement of smart contract bytecode, a series of tasks such as vulnerability mining, contract upgrading and malicious contract detection can be carried out. This paper proposes a method to measure the similarity of smart contract bytecode. Firstly, the key opcode combination of smart contract is summarized. When traversing the CFG(control flow graph) constructed by decompilation of smart contract bytecode, the opcodes in the basic block are pattern matched, and the features between the basic blocks are extracted according to the in-out degree, so as to enhance the similarity measurement effect of contract semantics in vector space. The experimental results show that the proposed method is greatly improved compared with the baseline.

关键词： Information science Smart contracts Semantics Euclidean distance Feature extraction Extraterrestrial measurements Flow graphs

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Implementing a modified Smith predictor using chemical reaction networks and its application to protein translation 4

Implementing a modified Smith predictor using chemical react...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Xiao, Yijun Lv, Hui Wang, Xing'an School of Software Engineering Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Liaoning Dalian116622 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Liaoning Shenyang110004 China College of Environmental and Chemical Engineering Dalian University Liaoning Dalian116622 China Dalian Chivy Biotechnology Co. Ltd Liaoning Dalian116622 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

In this article, a special attention is paid to the biochemical controller synthesis for time delay systems and try to implement the well-established Smith predictor approach in the context of biochemical systems. Then, chemical reaction networks (CRNs) are adopted to construct a modified Smith predictor scheme (integrating Smith predictor and feedback compensation controllers) for the first time. Taking a delayed protein translation model as the background, the CRNs-based proposed scheme has access to a method that can solve the effect of co-translated mRNA decay in protein translation. In addition, considering that the decay of mRNA affects mRNA stability and protein production, the co-translated mRNA degradation is treated as an interference input of the protein translation process. Our results show that the impact of a disturbance input (mRNA degradation) is restrained by the modified control strategy. The CRNs-based modified Smith predictor makes the protein translation process more robust and achieves protein output quickly and stably. © 2022 IEEE.

关键词： Time delay

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The Lattice Sieve Field Selection of Cado-NFS 2

The Lattice Sieve Field Selection of Cado-NFS

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2019 2nd International Conference on Computer Information Science and Artificial Intelligence, CISAI 2019

作者： Xue, Ping Chen, Shaozhen Fu, Zhixin Institute of Cyberspace Security PLA Information Engineering University Hennan450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Hennan450001 China

The software application of the discrete logarithms on the "large" finite field is studied. The most effective algorithm for the problem is the general number field sieve (GNFS). Focusing on the theory of GNFS of solving software Cado-NFS and lattice sieves, we find the selection of lattice sieve which improve efficiency of CADO-NFS. This is the first parameter modification suggest. The efficiency of our selection is better than the current by experiment. © Published under licence by IOP Publishing Ltd.

关键词： Sieves

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A Blockchain-Based CP-ABE Scheme with Partially Hidden Access Structures

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Security and Communication Networks 2021年第1期2021卷

作者： Ba, Yang Hu, Xuexian Chen, Yue Hao, Zenghang Li, Xuewei Yan, Xincheng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China Kunming Audit Center Kunming650001 China State Key Laboratory of Space Medicine Fundamentals and Application Beijing100094 China

Data sharing has become a key technology to break down data silos in the big data era. Ciphertext-policy attribute-based encryption (CP-ABE) is widely used in secure data-sharing schemes to realize flexible and fine-grained access control. However, in traditional CP-ABE schemes, the access structure is directly shared along with the ciphertext, potentially leading to users' private information leakage. Outsourcing data to a centralized third party can easily result in privacy leakage and single-point bottlenecks, and the lack of transparency in data storage and sharing casts doubts whether users' data are safe. To address these issues, we propose a blockchain-based CP-ABE scheme with partially hidden access structures (BCP-ABE-PHAS) to achieve fine-grained access control while ensuring user privacy. First, we propose an efficient CP-ABE scheme with partially hidden access structures, where the ciphertext size is constant. To assist data decryption, we design a garbled Bloom filter to help users quickly locate the position of wildcards in the access structure. Then, to improve storage efficiency and system scalability, we propose a data storage scheme that combines blockchain technology and the interplanetary file system, ensuring data integrity. Finally, we employ smart contracts for a transparent data storage and sharing process without third-party participation. Security analysis and performance evaluation show that the proposed BCP-ABE-PHAS scheme can preserve policy privacy with efficient storage and low computational overhead. © 2021 Yang Ba et al.

关键词： Blockchain

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Auto-MatRegressor材料性能自动预测器:解放材料机器学习"调参师"

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Science Bulletin 2023年第12期68卷 1259-1270,M0004页

作者：刘悦王双燕杨正伟 Maxim Avdeev 施思齐 School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Shanghai Engineering Research Center of Intelligent Computing System Shanghai 200444China State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China Materials Genome Institute Shanghai UniversityShanghai 200444China Zhejiang Laboratory Hangzhou 311100China Australian Nuclear Science and Technology Organisation Sydney 2232Australia School of Chemistry The University of SydneySydney 2006Australia

机器学习因其能够快速、精准拟合数据的潜在模式而被广泛应用于材料构效关系研究。然而,材料科学家往往需要进行繁琐的模型选择及参数寻优才能构建出高精度预测模型,为了解放材料机器学习"调参师",本文研发了基于元学习的材... 详细信息

机器学习因其能够快速、精准拟合数据的潜在模式而被广泛应用于材料构效关系研究。然而,材料科学家往往需要进行繁琐的模型选择及参数寻优才能构建出高精度预测模型,为了解放材料机器学习"调参师",本文研发了基于元学习的材料性能自动预测器,采集了60份文献公开数据集与60份标准数据集,基于此训练18种常用回归算法并获得其预测性能,定义与计算了27个刻画数据集特点的元特征,以此构建了一份蕴含建模经验的元数据集;同时,创建了表征数据集所属材料类型的类别树,将其嵌入基于距离的元学习算法,进一步耦合贝叶斯优化算法,实现领域知识和元数据协同驱动下的自动算法推荐和模型参数确定,实验结果表明,材料科学家仅需为新材料性能预测任务提供数据集,便可利用该预测器高效地构建具有与文献报道相当或更高预测精度的机器学习模型.

关键词：机器学习贝叶斯优化算法预测器材料科学家元数据参数寻优预测性能材料性能

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A Review of Field Text Analysis

A Review of Field Text Analysis

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Telecommunications, Optics and Computer Science (TOCS), IEEE Conference on

作者： Zhuolun Li Fei Kang Pu Yu Hui Shu School of Software Zhengzhou University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing MEAC Zhengzhou China

ISBN: (纸本)9781665424998

Field text analysis is the process of using natural language processing technology to understand the Text and extract information from unstructured text data. In recent years, due to the increasing maturity of machine learning technology, higher requirements have been put forward for field text analysis. This review first introduces the process of Text preprocessing and the development of text representation. Secondly, it summarizes the four typical techniques of text analysis, including named entity recognition, relation extraction, extractive text summarization, and text classification. Finally, for each typical technology, it introduces the commonly used methods and part of the researcher’s exploration of this technology.

关键词： Computer science Text analysis Text recognition Conferences Text categorization Machine learning Optics

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