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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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How to Construct Public Timeline for RSA-Formed Time-Lock Cryptography 20th

How to Construct Public Timeline for RSA-Formed Time-Lock ...

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20th International Conference on information security and Cryptology, Inscrypt 2024

作者： Jin, Huixuan Peng, Cong Fu, Jintao Luo, Min Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University Wuhan China Henan Key Laboratory of Network Cryptography Technology Henan Zhengzhou China Inspur Academy of Science and Technology Jinan China

ISBN: (纸本)9789819647330

Time-Locked Puzzle (TLP) and timed-release encryption (T-RE) are both time-based locking mechanisms. The former requires the decryptor to perform a predetermined amount of computation, while the latter requires a trusted server to release the decryption information after a preset time, thereby sending information to the future. As research has progressed, many feature-rich TLPs and TREs have emerged. However, TLP and TRE still face issues in practical deployment. The imbalance in computation load with TLP can result in significant computational burdens in many deployment scenarios, while the timed release in TRE necessitates that the server remains online. To address these issues, our goal is to develop a multifunctional solution to offload the computational burden and allow the server to be offline. Our scheme focuses on RSA-based TLPs and builds upon the sequential TRE schemes proposed by Chvojka and Jager et al.(ESORICS’21). We construct a multi-timeline scheme that aggregates multiple functions and allows the server to be offline. The multi-timeline structure proposed in our scheme, consisting of a main timeline, sub-timelines, and reward timelines, allows different timelines to assume different functions, and the main timeline controls the information release of the remaining timelines to achieve an efficient puzzle-solving release mechanism. The reward timeline provides a transfer account for storing bonuses for entities that solve puzzles, which achieves a self-balancing mechanism for computing resources. Due to the completion of a transaction guaranteed by the adaptor signature and smart contract, which ensure the atomicity of the transaction, the scheme achieves a traceable fair trading mechanism and a public verification mechanism. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： NP-hard

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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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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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From Data Integrity to Global Model Integrity for Federated Learning: An MHT-based Approach

From Data Integrity to Global Model Integrity for Federated ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Nannan Zhang Yao Zhao Y. Neil Qu Bruce Gu Keshav Sood Longxiang Gao Shui Yu 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 Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China School of IT Deakin University VIC Australia School of Computer Science University of Technology Sydney NSW Australia

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Federated Learning (FL) is a distributed machine learning (ML) approach that enables multiple edge nodes to collaboratively train ML models by sharing model parameters, thus addressing privacy concerns. However, in highly distributed, dynamic, and volatile FL environments, the global model is vulnerable to various corruptions. For instance, edge nodes might falsely claim that the received global model is incomplete, or the channel that transmits the global model is untrustworthy. Effectively verifying the integrity of the global model poses a critical challenge. To tackle this issue, we introduce a method for verifying model integrity called Federated learning global Model Integrity Verification (FMIV). It leverages Merkle Hash Tree (MHT) to generate integrity proofs of the global model during verification. To improve security, we integrate random security codes during proof generation. FMIV is capable of verifying the global model updated by the central server and shared with untrusted edge nodes, while efficiently identifying the edge node caching the incomplete global model. Furthermore, we conduct theoretical analysis and extensive experiments to validate the performance of FMIV. Compared to the two state-of-the-art approaches, FMIV consistently exhibits a notable improvement in verification efficiency and effectiveness in detecting model corruption.

关键词： Analytical models Privacy Codes Federated learning Computational modeling Image edge detection Data integrity Data models security Servers

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A Novel Collaborative Edge Caching via User Preference Awareness and Adaptive Clustering in MENs

A Novel Collaborative Edge Caching via User Preference Aware...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Pengfei Gu Huiling Shi Hao Hao Mingfa Li Wei Zhang 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 Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

In this paper, we propose a collaborative caching placement scheme leveraging user preference awareness and adaptive clustering (UPAAC), which jointly considers the heterogeneity of user preferences and user activity to reduce user access latency and improve the quality of service. Specifically, we first utilize Bidirectional Long Short-Term Memory (Bi-LSTM) to capture dynamic user behavior to predict user preferences, and then density-based spatial clustering of applications with noise (DBSCAN) is used to cluster users based on the predicted user preferences for more efficient cache placement. Furthermore, the cache placement optimal problem is defined as the latency reduction maximization problem under the constraint of the cache capacity and latency threshold, and a genetic algorithm (GA) is used to optimize the problem and design the cache placement strategy. The simulation outcomes indicate that the suggested approach outperforms the conventional caching methods by significantly decreasing content access latency and enhancing the cache hit ratio.

关键词： Noise Collaboration Quality of service Prediction algorithms Smart systems Probability distribution Timing History Long short term memory Genetic algorithms

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