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3rd China Intelligent Robotics Annual Conference, CCF CIRAC 2022

作者： Shi, Junfei He, Tiansheng Jin, Haiyan Wang, Hua Xu, Weinan State Key Laboratory of Geo-Information Engineering Shaanxi Xi’an710048 China School of Computer Science and Engineering Xi’an University of Technology Shaanxi Xi’an710048 China Shaanxi Key Laboratory for Network Computing and Security Technology Shaanxi Xi’an710048 China

ISBN: (纸本)9789819903009

Polarimetric Synthetic Aperture Radar (PolSAR) images have attracted much attention with abundant polarimetric scattering information. In recent years, many deep learning models have been proposed and highly expanded to PolSAR image classification. However, how to learn the complex matrix information is an indispensable problem. To address this problem, a Wishart Deeplab network is developed, which can not only learn the polarimetric matrix structure by designing Wishart network level but also learn multi-scale polarimetric scattering features by incorporating dilated convolution. Specifically, the Wishart-Deeplab based PolSAR classification model is constructed by designing the Wishart convolution operation to learn the statistical information of PolSAR data. Then, a deeplabV3 + network is followed to obtain the multi-scale semantic features by dilated convolution. By this way, statistical distrubtion-based and high-level semantic features are adaptively learned to improve the performance of the network. The experiments are conducted on two sets of real PolSAR data and results show that this method can obtain better classification results. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image classification

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network Topology Overlapping Group Detection Based on h-Core Pruning 6

Network Topology Overlapping Group Detection Based on h-Core...

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6th IEEE International Conference on Intelligent computing and Signal Processing, ICSP 2021

作者： Zhang, Qi Liu, Yan Cai, Yuheng Zhong Yuan Network Security Research Institute Zhengzhou University Zhengzhou China Pla Strategic Support Force Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9780738143705

The network group detection has a large number of application researches and has achieved certain results in network security, IP entity location and load balancing. However, due to the large scale of the network topology graph and the large number of terminal nodes, most of the existing overlapping group detection algorithms are relatively complex, and the data size that can be processed is limited, and cannot be directly applied to the network topology. This paper proposes a network topology overlapping group detection algorithm based on h-core pruning. This algorithm decomposes the network into smaller strong connected components, reduces the interference of noisy nodes to overlapping group discovery, and more efficiently detect the largest k-plex group on the target network. A large number of experiments show that the method in this paper is effective. Compared with the full-enum algorithm, our method increases the network size that can be handled by the largest k-plex group by two orders of magnitude, and can detect overlapping groups in the network topology more efficiently. © 2021 IEEE.

关键词： network topology

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A firmware upgrade solution based on hardware unique ID and SM4 cryptographic algorithm

A firmware upgrade solution based on hardware unique ID and ...

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2023 International Conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2023

作者： Gao, Shaofeng Wang, Kun Chen, Xinze Fu, Yong Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Jinan250000 China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan250000 China

ISBN: (纸本)9781510677685

This article presents and implements a firmware upgrade solution for embedded systems, which aims to address the vulnerability of using the same file that can be easily copied or stolen. When upgrading firmware, a txt file is sent by the upper-level software, which is encrypted using the SM4 algorithm. This encryption is based on a hardware-unique ID and a pre-stored upper-level software-unique ID, which act as encryption keys. During the upgrade, a secure downloader utilizes its hardware-unique ID and a pre-stored upper-level software-unique ID as decryption keys to decrypt the file. If the decryption key does not match the encryption key, the decrypted txt file will not be readable. Once decrypted, the firmware is downloaded to the target device using BSL (Bootstrap Loader) technology. Practical tests have shown that this method can achieve "one file, one key,"effectively preventing unauthorized use of the upgraded firmware. © 2024 SPIE.

关键词： Firmware

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Channel Drop Out: A Simple Way to Prevent CNN from Overfitting in Motor Imagery Based BCI 7th

Channel Drop Out: A Simple Way to Prevent CNN from Overfitti...

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7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021

作者： Luo, Jing Wang, Yaojie Xu, Rong Liu, Guangming Wang, Xiaofan Gong, Yijing Shaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Province Institute of Water Resources and Electric Power Investigation and Design Xi’an China

ISBN: (纸本)9789811659393

With the development of deep learning, many motor imagery brain-computer interfaces based on convolutional neural networks (CNNs) show outstanding performances. However, the trial number of EEG in the training set is usually limited, and redundancy extensively exists in multiple channel EEG. Thus, overfitting often appears in CNN based motor imagery recognition model and greatly affects the performances of model. In this paper, channel drop out is proposed to address this problem by data augmentation and ensemble learning. Specifically, one of all EEG channels will be dropped and replaced by the mean signal of all EEG channels. In this way, the trial number in the training set was enlarged by channel drop out. And at the testing stage, all the EEG trials processed by channel drop out were fed to the CNN model and the average output probabilities of them were applied to determine the prediction. The experiments were conducted on two popular CNN models applied in motor imagery BCI and BCI Competition IV datasets 2a to verify the performances of the proposed channel drop out approach. The results show that average improvements provided by channel drop out in two-category or four-category motor imagery classification are 2.83% and 2.65% compared with the original CNN model. So the channel drop out approach significantly improves the performances of motor imagery based BCI. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Brain computer interface

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information system security function validating using model checking

Information system security function validating using model ...

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2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010

作者： Ma, Jianli Xu, Guoai Yang, Yixian Ji, Yong Information Security Center State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Network and Information Attack Defense Technology of MOE Beijing University of Posts and Telecommunications Beijing China China Electronics System Engineering Computing station Beijing China

ISBN: (纸本)9781424463503

information systems will be encountered more and more security threats due to the development of computer attack method and technology. Generally, different security policies are used to protect the sensitive information in these systems. There has been a lot of study on security policy conformance and completeness verification and validation. However, there have few researches to validate whether the system behaviors satisfy the security policies. A model checking based information system security function validation method is proposed to validate the conformance between the system security solutions and the security policies in this paper. The system behaviors and the security policies are modeled separately, and the consistency between them is validated using the model checker SPIN. © 2010 IEEE.

关键词： Model checking

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Research on Classification Method of Sensitive Structural Data of Electric power 12

Research on Classification Method of Sensitive Structural Da...

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12th IEEE International Conference on Electronics information and Emergency Communication, ICEIEC 2022

作者： Guan, Xiaojuan Zhou, Cheng Cao, Wantian Security State Grid Smart Grid Research Institute Co. Ltd State Grid Key Laboratory of Information & Network Power Grid Digitizing Technology Department Jiangsu Province Nanjing China

ISBN: (数字)9781665407540

ISBN: (纸本)9781665407540

This paper analyzes the necessity of classification of sensitive data from the importance of electric power structured data, and puts forward the classification identification method of structural sensitive data of electric power enterprises from data survey, data classification to construction of sensitive field database. © 2022 IEEE.

关键词： Sensitive data

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security risk analysis of on-site terminal of marketing specialty in power industry under the environment of internet of things 12

Security risk analysis of on-site terminal of marketing spec...

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12th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

作者： Yang, Ruxia Gao, Peng Gao, Xianzhou Fang, Zhou Global Energy Interconnection Research Institute State Grid Key Laboratory of Information and Network Security Nanjing China State Grid Zhejiang Electric Power Co. Ltd. Zhejiang China

ISBN: (纸本)9781728170817

Due to the weak protection of the field terminal equipment and the uncontrollable environment, once it is illegally used, it will directly affect the overall security protection system of the State Grid Corporation. The security threat is extremely huge. It is necessary to analyze and identify the safety risks of the field professional terminal in the power industry and make countermeasures. This paper investigates the status quo of on-site terminal security protection in the power industry marketing industry, analyzes the existing security risks, and further analyzes the security risks of the power industry marketing professional field terminal under the Internet of Things environment. And put forward relevant suggestions on the problems existing at the current stage. © 2020 IEEE.

关键词： Internet of things

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A survey on cryptographic techniques for protecting big data security: present and forthcoming

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Science China(information Sciences) 2022年第10期65卷 73-106页

作者： Siqi LU Jianhua ZHENG Zhenfu CAO Yongjuan WANG Chunxiang GU School of Cyberspace Security Information Engineering University Henan Key Laboratory of Network Cryptography Technology Institute of Security Technology Shanghai Key Laboratory of Trustworthy Computing East China Normal University Cyberspace Security Research Center Peng Cheng Laboratory Shanghai Institute of Intelligent Science and Technology Tongji University

Big data drive multidimensional convergence and profound innovations among industries and provide novel ways of exploring the world. As they significantly create economic and social value, big data meaningfully impact the implementation and management of information security and privacy *** technologies are used to protect the security and entire life cycle of big data. The demand for this technology is multiplied when the data are stored in the cloud. They are stored in the cloud in the form of ciphertext, and the driving requirement for data retrieval, sharing, and manipulation places the security of data at risk. The all-or-nothing approach of traditional cryptography systems cannot realize the release and processing of data information with flexible and increasingly fine granularity. Consequently, dealing with the relationship between privacy protection and data utilization, as well as navigating the blurry boundaries between subverting either plaintext or ciphertext, has become a research focus of the current cryptographic trend for protecting big data security. Presently, there are many studies designed to solve these ***, security requirements and source encryption mode for future big data systems and applications are elaborated. Then, focusing on the practical security and functionality of the big data life cycle, including storage, retrieval, sharing, calculation, statistical analysis, and utilization, the research being conducted based on those functions is reviewed. For each cryptographic technology that meets the requirement of each type of big data security or application, security and efficiency comments and sufficient comparison analyses of cryptography schemes or protocols are provided; moreover, the current general problems and development trends are expounded. Because the current innovative research on cryptographic technology was primarily based on the development or improvement of a single solution, the study on

关键词： big data security cryptographic techniques ciphertext-based data sharing and computing authenticated encryption functional encryption homomorphic encryption secure multi-party computing

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A Light-weight Kernel-level Mandatory Access Control Framework for Android

A Light-weight Kernel-level Mandatory Access Control Framewo...

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2019 IEEE International Conference on power, Intelligent computing and Systems, ICPICS 2019

作者： Wu, Fei Luo, Fucai Chen, Kuosong Lin, Wei Lu, Ziang State Grid Fujian Electric Power Company Fuzhou Fujian China Fujian Yirong Information Technology Co. Ltd Fuzhou Fujian China State Grid Key Laboratory of Information Network Security Nanjing Jiangsu China

ISBN: (纸本)9781728137209

With the rapid development of mobile communication technology and mobile Internet technology, mobile terminals are becoming more and more irreplaceable in people's life and work. In the present power industry, Android-based smart mobile terminals are widely used to carry out various kinds of operations. Compared with traditional desktop computers, smart mobile terminals provide users with convenience and are more vulnerable to attack and control. Considering the security protection of the core layer of smart mobile terminal, this paper designs an Android lightweight kernel layer mandatory access control framework, deeply analyses and discusses the necessity of terminal kernel layer security protection, proposes a verifiable lightweight kernel layer access control model, and formalizes the model. This paper describes and uses FVT method to discuss security policy conflict detection technology. Finally, the availability and shortcomings of the model on three typical smart mobile terminals are verified by experiments. © 2019 IEEE.

关键词： Access control

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A Semi-supervised Protein Complex Identification Algorithm Based on Sparseness Constraint

A Semi-supervised Protein Complex Identification Algorithm B...

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2024 International Conference on Applied Mathematics, Modelling and Statistics Application, AMMSA 2024

作者： Liu, Guangming Dang, Fengqing Wang, Bin Peng, Yonghong Wang, Xiaofan Tan, Li School of Computer Science and Engineering Shaanxi Key Laboratory for Network Computing and Security Technology Xi'An University of Technology Shaanxi Xi'an China Faculty of Science and Engineering Computing and Information Science Cambridge United Kingdom School of Computer and Information Engineering Beijing Technology and Business University Beijing China

Recognising protein complexes in protein interaction networks is crucial, but poses a major challenge due to the frequency of noisy interactions. These networks typically involve numerous protein complexes, with each protein generally only participating in a few complexes. Current recognition models often ignore this aspect. To address this problem, we present a semi-supervised protein complex identification algorithm that extends non-negative matrix factorization (NMF) with sparsity constraints. In contrast to conventional approaches that apply a global sparsity constraint to the entire matrix, our method imposes individual sparsity constraints on protein membership indicator vectors. This targeted strategy controls the algorithm more effectively. Our experimental results with yeast and human protein interaction networks show that our algorithm achieves higher accuracy in identifying protein complexes than leading contemporary methods. © Published under licence by IOP Publishing Ltd.

关键词： Non-negative matrix factorization

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