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10th China International Conference on Electricity Distribution, CICED 2022

作者： Li, Nige Zhou, Peng Wang, Tengyan Chen, Jingnan State Grid Smart Grid Research Institute Co. Ltd. State Grid Key Laboratory of Information & Network Security Nanjing210003 China State Grid Zhejiang Electric Power Corporation Information &Telecommunication Branch Hangzhou China

ISBN: (数字)9781665452687

ISBN: (纸本)9781665452687

This paper proposes a control flow integrity checking method based on the LBR register: through an analysis of the static target program loaded binary modules, gain function attributes such as borders and build the initial transfer of legal control flow boundary, real-time maintenance when combined with the dynamic execution of the program flow of control transfer record, build a complete profile control flow transfer security;Get the call location of/bin/sh or system() in the program to build an internal monitor for control-flow integrity checks. In the process of program execution, on the one hand, the control flow transfer outside the outline is judged as the abnormal control flow transfer with attack threat;On the other hand, abnormal transitions across the contour are picked up by an internal detector. In this method, by identifying abnormal control flow transitions, attacks are initially detected before the attack code is executed, while some attacks that bypass the coarse-grained verification of security profile are captured by the refined internal detector of control flow integrity. This method reduces the cost of control flow integrity check by using the safety profile analysis of coarse-grained check. In addition, a fine-grained shell internal detector is inserted into the contour to improve the safety performance of the system and achieve a good balance between performance and efficiency. © 2022 IEEE.

关键词： Internet of things

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Neural network-Based Safety Optimization Control for Constrained Discrete-Time Systems

Neural Network-Based Safety Optimization Control for Constra...

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Annual Conference of Industrial Electronics Society

作者： Xueli Wang Shangwei Zhao Ming Yang Xiaoming Wu Xin Wang Shuo Xu Xu Hu Key Laboratory of Computing Power Network and Information Security Shandong Computer Science Center Qilu University of Technology Jinan China Department of Automation Shanghai Jiao Tong University Shanghai China Public Security Bureau of Jinan Jinan China

This paper proposes a constraint-aware safety control approach via adaptive dynamic programming (ADP) to address the control optimization issues for discrete-time systems subjected to state constraints. First, the constrained control framework is established via the primal-dual approach with the modified Lagrangian based on the relaxed barrier function. Herein, the Lagrangian multiplier is designed to achieve the trade-off between optimization performance and state constraints. In addition, the sub optimality of the dual method is built by proving that the dual gap can be arbitrarily small. And the value iteration algorithm is utilized to implement the constraint-aware ADP controller. Furthermore, the weight estimation error is proved to be bounded when the learning rate satisfies a given sufficient condition. Finally, numerical simulation proves the effectiveness and superiority of the proposed method.

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MEDIAN: Adaptive Intermediate-grained Aggregation network for Composed Image Retrieval

MEDIAN: Adaptive Intermediate-grained Aggregation Network fo...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Qinlei Huang Zhiwei Chen Zixu Li Chunxiao Wang Xuemeng Song Yupeng Hu Liqiang Nie School of Software Shandong University Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) School of Computer Science and Technology Shandong University School of Computer Science and Technology Harbin Institute of Technology (Shenzhen)

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The Composed Image Retrieval (CIR) task aims to retrieve a target image that meets the requirements based on a given multimodal query (includes a reference image and modification text). Most existing works align multimodal semantics at both local and global granularity. However, they have failed to consider the mining of semantic correspondences at the intermediate-grained level, which has resulted in sub-optimal model performance. In this paper, we propose an adaptive interMEDiate-graIned Aggregation network (MEDIAN). Compared with the conventional CIR models, MEDIAN is capable of generating intermediate-grained feature aggregation supervised signals and constructing graph attention networks to extract intermediate-grained features. Concurrently, MEDIAN also devises cross-modal semantic correspondence aligning guided by the target image, which in turn enables accurate multi-grained feature composition. The superiority of MEDIAN is demonstrated by extensive experiments on three benchmark datasets. Our code is available at https://***/***/.

关键词： Adaptation models Adaptive systems Accuracy Codes Semantics Image retrieval Benchmark testing Signal processing Feature extraction Speech processing

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PAIR: Complementarity-guided Disentanglement for Composed Image Retrieval

PAIR: Complementarity-guided Disentanglement for Composed Im...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhiheng Fu Zixu Li Zhiwei Chen Chunxiao Wang Xuemeng Song Yupeng Hu Liqiang Nie School of Software Shandong University Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) School of Computer Science and Technology Shandong University School of Computer Science and Technology Harbin Institute of Technology (Shenzhen)

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Composed Image Retrieval (CIR) is a novel image retrieval paradigm that aims at searching for the target images via the multimodal query including a reference image and a modification text. Although existing works have made significant progress, they overlook the inter-modal coherence and incoherence relations modeling, hindering the retrieval accuracy of CIR models. This limitation is non-trivial due to the following two challenges: 1) inter-modal incoherence and 2) intra-modal entanglement. To address the above challenges, we propose a comPlementArity-guided dIsentanglement network (PAIR), which can disentangle the features of multimodal queries from a semantic coherence perspective, thereby facilitating the identification of both complementary coherent and incoherent features. Furthermore, based on disentangled features, PAIR develops an asymmetric feature composition module, which is designed to enhance the retrieval performance of the model. Extensive experiments on three benchmark datasets demonstrate the superiority of PAIR. The code is available at https://***/***/.

关键词： Codes Accuracy Image retrieval Semantics Coherence Benchmark testing Signal processing Acoustics Speech processing Protection

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Revisiting the Application of Twin Connected Parallel networksand Regression Loss Functions in Industrial Defect Detection

SSRN

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SSRN 2023年

作者： Su, Zhanzhi Zhou, Mingle Li, Min Zhang, Zekai Zhang, Cheng Xing, Rui Li, Gang 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 Jinan250353 China

Industrial product surface defects can affect the reliability and lifetime of products. However, industrial scenes are complex, with a wide variety of products, and product surface defects often have characteristics such as large-scale variations and tiny targets, which makes it challenging to achieve the expected results in defect detection. To this end, this paper designs a Twin-Connected Parallel network (TCPNet) for high-precision defect detection and recognition. The innovative features of TCPNet include three points: First, a twin-connected parallel network is designed to efficiently extract semantic and texture information of objects through parallel networks, enhance important feature information of different branch networks in real-time, and ensure local-to-global feature extraction. Second, Differential Feature Remodeling Module(DFRM) modules designed. Carry out feature differentiation processing, and reshape the different features in the local feature extraction module to highlight the defective features. Third, Considering the difficulty of regression and model convergence for small objects, this paper designs the Dynamic Variation regression loss function (DVIoU) based on the dynamic distance relationship between the four pairs of vertices of the target frame and the real frame. Finally, this paper proposes an industrial defect dataset for bottlebody and practically applies TCPNet to industrial scenarios, with experimental results reaching SOTA. © 2023, The Authors. All rights reserved.

关键词： Surface defects

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Provably Secure Authenticated key-Management Mechanism for e-Healthcare Environment

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IEEE Internet of Things Journal 2025年

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Ghaffar, Zahid Xie, Yong Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan Qinghai Institute of Technology School of Computer and Information Science China Qinghai Provincial Laboratory for Intelligent Computing and Application China Key Laboratory of Computing Power Network and Information Security Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security China Shandong Fundamental Research Center for Computer Science Jinan250353 China

The Internet of Things (IoT) is rapidly permeating all aspects of human life, involving a network of devices that share sensitive data. A notable application is the e-healthcare systems, which employ connected sensors, medical servers, and wearable devices. However, the public nature of communication in e-healthcare systems poses challenges such as security, privacy, and authentication of participating entities. Recently, many authentication protocols have been introduced to address these challenges. However, most of these protocols remain vulnerable to various security attacks, including device or medical server impersonation, denial of service, physical or cloning, and de-synchronization attacks. Therefore, we introduce an authenticated key-management protocol utilizing hash functions and Cipher-Block Chaining-Advanced Encryption Standard encryption (CBC-AES) encryption. The proposed protocol also employs the Physical Unclonable Function (PUF), which makes it more robust and efficient in resisting physical or cloning attacks. Additionally, the proposed scheme resists various security threats, including impersonation, session key leakage, ephemeral secret leakage, and de-synchronization attacks. We analyze the scheme’s security and reliability through formal and informal analysis. The informal analysis demonstrates that the scheme encompasses crucial security features, while the formal analysis substantiates. Moreover, performance analysis of the proposed protocol with various competing results indicates that our protocol achieves an average reduction in communication and computation overheads by 36.03.% and 41.79%, respectively. © 2014 IEEE.

关键词： Electronic health record

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A Cloud computing User Experience Focused Load Balancing Method Based on Modified CMA-ES Algorithm 18th

A Cloud Computing User Experience Focused Load Balancing Met...

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18th International Conference on Green, Pervasive, and Cloud computing, GPC 2023

作者： Luo, Jihai Dong, Chen Chen, Zhenyi Xu, Li Chen, Tianci College of Computer and Data Science - Fuzhou University Xueyuan Road Fujian Fuzhou360108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China Department of Computer Science and Engineering University of South Florida TampaFL33620 United States College of Computer and Cyber Security Fujian Normal University Fuzhou350007 China

ISBN: (纸本)9789819998951

The development of the software and hardware has brought about the abundance and overflow of computing resources. Many Internet companies can lease idle computing resources based on the peak and valley cycles of usage load to provide IaaS service. After the surging development, more and more companies are gradually paying attention to the specific user experience in cloud computing. But there are few works about that aspect in load balance problem. Therefore, we consider the load balancing resource allocation problem, from the perspective of user experience, mainly based on geographical distance and regional Equilibrium, combined with user usage habits, in multiple service periods. A detailed mathematical definition has been established for this problem. This article proposes a mathematical model for the problem, along with an modified CMA-ES (Covariance Matrix Adaptation Evolution Strategy) algorithm, called WS-ESS-CMA-ES algorithm, to allocate computing resources and solve the above problem. The process of using the proposed algorithm to solve the problem of cloud computing resource allocation in real scenarios is simulated, and compared with some other algorithms. The experiment results show that our algorithm performs well. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Cloud computing

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FAST: a dual-tier few-shot learning paradigm for whole slide image classification 24

FAST: a dual-tier few-shot learning paradigm for whole slide...

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Proceedings of the 38th International Conference on Neural information Processing Systems

作者： Kexue Fu Xiaoyuan Luo Linhao Qu Shuo Wang Ying Xiong Ilias Maglogiannis Longxiang Gao Manning Wang 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) Jinan China and Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Digital Medical Research Center School of Basic Medical Sciences Fudan University and Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Fudan University University of Piraeus

ISBN: (纸本)9798331314385

The expensive fine-grained annotation and data scarcity have become the primary obstacles for the widespread adoption of deep learning-based Whole Slide Images (WSI) classification algorithms in clinical practice. Unlike few-shot learning methods in natural images that can leverage the labels of each image, existing few-shot WSI classification methods only utilize a small number of fine-grained labels or weakly supervised slide labels for training in order to avoid expensive fine-grained annotation. They lack sufficient mining of available WSIs, severely limiting WSI classification performance. To address the above issues, we propose a novel and efficient dual-tier few-shot learning paradigm for WSI classification, named FAST. FAST consists of a dual-level annotation strategy and a dual-branch classification framework. Firstly, to avoid expensive fine-grained annotation, we collect a very small number of WSIs at the slide level, and annotate an extremely small number of patches. Then, to fully mining the available WSIs, we use all the patches and available patch labels to build a cache branch, which utilizes the labeled patches to learn the labels of unlabeled patches and through knowledge retrieval for patch classification. In addition to the cache branch, we also construct a prior branch that includes learnable prompt vectors, using the text encoder of visual-language models for patch classification. Finally, we integrate the results from both branches to achieve WSI classification. Extensive experiments on binary and multi-class datasets demonstrate that our proposed method significantly surpasses existing few-shot classification methods and approaches the accuracy of fully supervised methods with only 0.22% annotation costs. All codes and models will be publicly available on https://***/fukexue/FAST.

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Bat-FG: A Broad Attention Based Fine-Grained Offloading in Green computing power networks

Bat-FG: A Broad Attention Based Fine-Grained Offloading in G...

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IEEE International Conference on Communications (ICC)

作者： Zhutao Liu Chao Qiu Yunfeng Zhao Xiaofei Wang Jing Jiang College of Intelligence and Computing Tianjin University Tianjin China Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and Telecommunications Xi'an China

computing power network (CPN) is an evolution of multi-access edge computing. Since the skyrocketing proliferation of CPN s, energy consumption aggravates explosively. However, majority of energy is wasted due to the incomplete analysis of tasks and resources, such as coarse-grained tasks consideration, coarse-grained resources integration, and unfocused complex information. In this paper, we propose a broad attention based fine-grained task offloading approach in green CPNs, i.e., Bat-FG. Specifically, for fine-grained tasks, we establish directed acyclic graphs (DAGs) subtasks offloading problem for green CPNs under the dependency and service constraints. For finegrained resources, decentralized resources are integrated into resource pools. Bridging the gap between fine-grained tasks and resource pools, we design a novel broad attention meta-reinforcement learning approach, i.e., Bat-MRL to focus on the main information for reducing the tasks' latency and energy consumption. Finally, extensive simulations show that Bat-FG significantly reduces 25.6 % task latency and 72.9 % energy consumption.

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Scenario based intelligent desensitization and dynamic access control technology for power distribution and distributed new energy data resources 6

Scenario based intelligent desensitization and dynamic acces...

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6th International Conference on Intelligent computing, Communication, and Devices, ICCD 2023

作者： Min, Xu Aihua, Zhou Yiqing, Wang Xiaofeng, Shen Lin, Peng Nige, Li Gang, Wang He, Wang State Grid Smart Grid Research Institute Co. LTD. Jiangsu Nanjing210003 China State Grid Key Laboratory of Information and Network Security Nanjing210003 China State Grid Jiangsu Electric Power Co. Ltd Jiangsu Nanjing210024 China State Grid Shanghai Electric Power Company Shanghai200122 China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

The new power system has a new operation mode of "the source follows the load, the load follows the network, and the source loads interact". With the continuous excavation of flexible regulation resources, new third-party entities such as virtual power plants or load integrators need to consider implementing differentiated network security protection requirements to ensure their fair access to business. At the same time, with the clarity of the regulation level of the new power system and the continuous participation of various entities in the construction, the company's network security protection boundary will no longer be "horizontal and vertical", but will become more uneven, with more types of interfaces and interfaces. It is necessary to refine the boundary protection measures according to different interaction needs. The new regulatory subject on the demand side of the new power system involves the privacy information of a large number of users. Data flow and sharing, cross access and collaborative analysis among the subjects have security problems such as unauthorized access and privacy leakage. This paper focuses on the scenario based intelligent desensitization and dynamic access control technology for power distribution and distributed new energy data resources, and combs various factors involved in the data access process, On the basis of obtaining the data access authority, the dynamic correlation analysis of the three elements of user role and access authority, sensitive data level, power allocation and distributed new energy business scenario is integrated, and finally the appropriate desensitization method is selected from the desensitization algorithm library, and finally the appropriate desensitization method is selected from the desensitization algorithm library to ensure the security protection capability of the new distribution network under the flexible, open and interactive energy scenario, Effectively respond to new major network security ris

关键词： network security

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