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Trust and Risk Based on Access Control Model in Social Internet of Things

International Journal of network security 2023年第5期25卷 736-744页

作者： Zhang, Hongbin Liu, Jian Zhao, Dongmei Liu, Bin Wang, Yanmei Fan, Fan School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang050000 China Hebei Key Laboratory of Network and Information Security Hebei Normal University Shijiazhuang050024 China School of Economics and Management Hebei University of Science and Technology Shijiazhuang050000 China Research Center of Big Data and Social Computing Hebei University of Scienc and Technology Shijiazhuang050000 China Hebei Geological Worker’s University Shijiazhuang050000 China

Integrating social networks and the Internet of Things has formed an emerging field of Social Internet of Things (IoT). Aiming to address the shortcomings of traditional TBAC (Trust based on Access Control) and ABAC (Attribute based on Access Control) in dynamic authorization and security, this paper proposes a hybrid access control model based on trust and risk for SIoT. The model supports social relationship-based trust assessment and risk prediction between SIoT nodes and integrates trust and risk values into SIoT security values through reasonable weight allocation. Furthermore, by simulating the safety requirements of different scenarios, it was verified that the model was efficient and more secure than the current models. © (2023). All Rights Reserved.

关键词： Authorization

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Efficient Module-Lattice-based Certificateless Online/Offline Signcryption Scheme for Internet of Medical Things

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IEEE Internet of Things Journal 2025年

作者： Bai, Ye He, Debiao Yang, Zhichao Luo, Min Peng, Cong Wuhan University Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan430072 China Wuhan University School of Cyber Science and Engineering Wuhan430072 China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250014 China Naval University of Engineering Department of Information Security Wuhan430000 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250014 China

The Internet of Medical Things (IoMT) has achieved remote diagnosis and real-time health monitoring through intelligent sensor devices and Internet of Things (IoT) technology, providing great convenience for analyzing medical conditions between doctors and patients. However, sensitive information such as patient medical data may face security challenges such as data leakage and abuse during transmission in the IoMT. To ensure the confidentiality and unforgeability of medical data transmission, scholars have proposed many cryptographic schemes. With the development of quantum computers, schemes based on traditional cryptographic primitives have become insecure. Existing cryptographic schemes for IoMT cannot simultaneously meet the security requirements of high communication performance, low computational overhead, and resistance to quantum attacks. Therefore, we propose an efficient module-lattice-based certificateless online/offline signcryption (MLCLOOSC) scheme resistant to quantum attacks while meeting the confidentiality and unforgeability requirements under Type I and Type II attacks. Compared with five recent CLOOSC schemes, theoretical analysis, and experimental test results show that the proposed scheme outperforms the other five schemes regarding computational and communication costs and security. Therefore, our scheme is more suitable for application in IoMT scenarios. © 2014 IEEE.

关键词： Quantum computers

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A Trusted Privacy-Preserving Model for Cross-Chain Transactions Based on zk_SNARKs

A Trusted Privacy-Preserving Model for Cross-Chain Transacti...

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International Conference on networking and network Applications (NaNA)

作者： Yichuan Wang Jianhuan Tie Xinhong Hei Li Zhao Xiaohui Zhang School of Computer Science and Engineering Xi'an University of Technology Xi'an China Shaanxi Key Laboratory for Network Computing and Security Technolog Xi'an China

Currently, the privacy protection technology of blockchain is not mature enough, such as user data leakage and lack of anonymity exist, and these problems are especially serious when conducting cross-chain transactions. In this paper, we propose a method of cross-chain transactions based on zk_SNARKs in a trusted environment for cross-chain transactions for privacy protection. Cross-chain transactions are performed through the features of zk_SNARKs such as efficiency, privacy, and verifiability. zk_SNARKs needs to generate trusted settings with the help of a third party during the transaction, and the process has serious privacy issues, and the private parameters generated during the transaction may be maliciously attacked and thus obtained by attackers. To address this problem, we use a hardware technology SGX for trusted computing to encrypt and store some private parameters generated by zk_SNARKs, thus ensuring the security of cross-chain transactions. The experimental results show that the privacy protection scheme using SGX for cross-chain transactions takes less time than the traditional transaction privacy protection, with a verification time of 1.2s for a number of 10 sidechains, and is more efficient than the traditional cross-chain transaction privacy protection.

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DCCT-Net: A network Combined Dynamic CNN and Transformer for Image Compressive Sensing

DCCT-Net: A Network Combined Dynamic CNN and Transformer for...

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

作者： Lijuan Xu Haixiao Mei Fenghua Tong Dawei Zhao Fuqiang 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 Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Recent end-to-end image compressive sensing networks primarily use Convolutional Neural networks (CNNs) and Transformers, each with distinct limitations: CNNs struggle with global feature capture, while Transformers lack local feature extraction. We propose a novel network, DCCT-Net, which combines Dynamic CNN (DCNN) and Transformer. This integration leverages DCNN’s local feature strengths and the Transformer’s global representation capabilities, resulting in superior image reconstruction quality. To further enhance the network’s performance, we propose a Feature Dynamic Augment Module (FDAM), which dynamically extracts features based on the saliency of segmented image regions, thereby amplifying the CNN’s local feature expression. Additionally, we design a Weighted Fusion Module (WFM), which optimizes the combination of local and global features extracted by the DCNN and Transformer, respectively. Extensive experiments demonstrate that our proposed DCCT-Net significantly outperforms most existing state-of-the-art methods in the field.

关键词： Image segmentation Image coding Signal processing Transformers Feature extraction Sensors Convolutional neural networks Speech processing Compressed sensing Image reconstruction

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An Enhanced RT-DETR Model for Improved Fabric Defect Detection in Industrial Environments

An Enhanced RT-DETR Model for Improved Fabric Defect Detecti...

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International Conference on Computer Supported Cooperative Work in Design

作者： Huijuan Hao Lei Xu Qingyan Ding Hu Zhang Jinqiang Bai Guanghe Cheng Fengqi Hao 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 Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Fabric defect detection is critical for quality control in the textile industry. However, current challenges include the scarcity of high-quality datasets, the difficulty of detecting small defects in complex environments, and suboptimal detection performance for elongated defects. To address these issues, we propose an improved Real-Time Detection Transformer (RT-DETR) model specifically designed for fabric defect detection in industrial settings. A custom fiber defect dataset was created with random augmentations for improved diversity. We designed the Global Attention-based Instance Feature Interaction (GA-AIFI) module to enhance local feature extraction, improving the model's detection capability for small defects. Additionally, to address the prevalence of elongated defects in industrial fabric production, we introduced the Aspect Ratio-aware Distance-IoU (AR-DIoU) loss function, which further improves bounding box localization accuracy. Experiments conducted on both the custom dataset and the MVTec dataset demonstrate significant improvements, with mAP@.5 increasing by 3.5% and 3.6%,respectively, confirming the model's effectiveness.

关键词： Location awareness Adaptation models Accuracy Computational modeling Feature extraction Transformers Fabrics Real-time systems Textile industry Defect detection

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Petri Net Model of MITM Attack Based on NDP Protocol

Petri Net Model of MITM Attack Based on NDP Protocol

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2022 International Conference on networking and network Applications, NaNA 2022

作者： Zhang, Liumei Han, Yu Wang, Yichuan Quan, Ruiqin School of Computer Science Xi’an Shiyou University Xi’an China School of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Key Laboratory for Network Computing and Security Technology Xi’an China Xinjiang Institute of Engineering China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

Neighbor Discovery Protocol (NDP) is one of the core protocols of IPv6 networks. Since NDP messages are an unauthenticated stateless protocol, they are vulnerable to various types of attacks, and Man-In-The-Middle (MITM) attacks are one of the most well-known attacks in the computer field. During NDP address resolution, attackers change their own IP-MAC mapping relationships by sniffing NA (Neighbor Advertisement) messages, thus spoofing the source host's neighbor cache table and compromising the confidentiality, integrity and availability of the IPv6 network. Therefore, this paper focuses on the MITM attack in the NDP address resolution process, and performs a fine-grained analysis and Petri Net modelling of the attack process. © 2022 IEEE.

关键词： Petri nets

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A Lightweight Identity Privacy Protection Scheme For Electric Vehicles Based On Consortium Blockchain

A Lightweight Identity Privacy Protection Scheme For Electri...

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International Conference on Computer Supported Cooperative Work in Design

作者： Shuhui Zhang Ting Gao Lianhai Wang Shujiang Xu Wei Shao Qizheng 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 Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

As electric vehicle (EV) utilization in energy trading expands, protecting user identity privacy during transactions has become a critical area of research. Current privacy protection schemes face significant challenges, including the risks of identity leakage, insufficient protection against double signatures, and low verification efficiency. To address these challenges, this document proposes a lightweight identity privacy protection scheme based on blockchain technology from the consortium. The scheme introduces an improved linkable ring signature algorithm, which guarantees identity anonymity while effectively preventing double signature attacks. In addition, this paper develops a batch aggregation signature and verification algorithm designed to significantly improve verification efficiency in highly concurrent environments. Theoretical analysis and simulation experiments demonstrate that the proposed scheme outperforms existing solutions in security, computational efficiency, and communication overhead. Compared to existing solutions, this approach provides substantial improvements, making it a promising approach to secure user privacy within the rapidly evolving domain of EV energy trading.

关键词： Privacy Data privacy System performance Heuristic algorithms Electric vehicles Blockchains Computational efficiency Protection Vehicle dynamics Interoperability

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Dense Student Behavior Recognition Algorithm for Classroom Surveillance Based on Improved Real-Time Detection Transformer

Dense Student Behavior Recognition Algorithm for Classroom S...

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International Conference on Computer Supported Cooperative Work in Design

作者： Hao Zhang Xiangzhi Liu Xiaoming Wu Chunlin Zhao 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 Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Accurate detection of students' behaviors in class-rooms through video surveillance is crucial for improving teaching quality. This paper presents LAF -DETR, a novel algorithm designed to address challenges such as dense student interactions and multi-scale variations in complex classroom environments. key contributions include a lightweight convolution module to enhance the extraction of multi-scale features, a feature fusion module to reduce background noise and improve multi-scale feature integration, and a downsampling module to capture compre-hensive information across various behavior scales. Experiments on three public datasets (SCB-Dataset3-S, CrowdHuman, Smart-Classroom-Student-Behavior) show that LAF-DETR outperforms the baseline model by 2.8%, 1.9%, and 2.1 % in Average Precision (AP), respectively, demonstrating its effectiveness in handling occlusion and multi-scale detection challenges.

关键词： Accuracy Federated learning Education Feature extraction Video surveillance Transformers Robustness Real-time systems Data mining Image enhancement

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Research on Firmware Simulation of Windows Embedded Compact System

Research on Firmware Simulation of Windows Embedded Compact ...

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International Conference on Computer Supported Cooperative Work in Design

作者： Dawei Zhao Zhen Zhang Lei Zhang Lijuan Xu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Shandong Academy of Sciences Qilu University of Technology Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Firmware simulation of embedded devices is an important technology to support security testing of embedded devices. However, most of the current firmware emulation targets are bare-metal or Linux-based firmware. The number of embedded devices based on Windows Embedded Compact (Windows CE) as the operating system occupies a certain market size, and there are certain security risks. Firmware extraction and system state simulation of embedded devices based on Windows CE are difficult. In order to solve the problem that embedded devices based on Windows CE system need firmware simulation methods and better support the security testing of embedded devices using Windows CE system, We propose a firmware simulation method for Windows CE systems. Combining the development board framework supported by QEMU and the specific application of embedded devices to be simulated, we make a simulation image that can run in QEMU. We verify our method on two commercial PLCs, and the experimental results show that our method can simulate the system state of PLC firmware.

关键词： Federated learning Operating systems Industrial control Emulation security Microprogramming Testing

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Cetus: an efficient symmetric searchable encryption against file-injection attack with SGX

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Science China(Information Sciences) 2021年第8期64卷 195-212页

作者： Yanyu HUANG Siyi LV Zheli LIU Xiangfu SONG Jin LI Yali YUAN Changyu Dong College of Cyber Science and the College of Computer Science Tianjin Key Laboratory of Network and Data Security TechnologyNankai University School of Computer Science and Technology Shandong University School of Computer Science Guangzhou University Department of Computer Science University of G?ttingen School of Computing Newcastle University

Symmetric searchable encryption(SSE) allows the users to store and query their private data in the encrypted database. Many SSE schemes for different scenarios have been proposed in the past few years, however, most of these schemes still face more or fewer security issues. Using these security leakages,many attacks against the SSE scheme have been proposed, and especially the non-adaptive file injection attack is the most serious. Non-adaptive file injection attack(NAFA) can effectively recover some extremely important private information such as keyword plaintext. As of now, there is no scheme that can effectively defend against such attacks. We first propose the new security attribute called toward privacy to resist nonadaptive file injection attacks. We then present an efficient SSE construction called Cetus to achieve toward privacy. By setting up a buffer and designing the efficient oblivious reading algorithm based on software guard extensions(SGX), we propose the efficient one-time oblivious writing mechanism. Oblivious writing protects the update pattern and allows search operations to be performed directly on the data. The experiment results show that Cetus achieves O(aw) search time and O(1) update communication. The practical search time, communication, and computation overheads incurred by Cetus are lower than those of state-of-the-art.

关键词： searchable encryption SGX technique file injection attack forward/toward privacy cloud databases

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