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ID-based Signcryption KEM to Multiple Recipients

Chinese Journal of Electronics 2023年第2期20卷 317-322页

作者： Yinxia Sun Hui Li Key Laboratory of Computer Networks and Information Security Ministry of Education Xidian University Xi'an China

Identity based signcryption key encapsulation mechanism (KEM) is used to encapsulate a symmetric key during the construction of hybrid signcryption in the identity based setting. We introduce the notion of Identity based signcryption KEM to multiple recipients (mIDSC-KEM), and define security models for this new primitive. We illustrate by proposing an efficient mIDSC-KEM scheme. Our scheme is proved secure in the random oracle model under the Gap bilinear Diffie-Hellman (Gap-BDH) and the Computational Diffie-Hellman (CDH) assumption.

关键词： Encapsulation Costs Computational modeling security Research and development Standards

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A Privacy-friendly sequential progressive framework for segmented decision making

A Privacy-friendly sequential progressive framework for segm...

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2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Liu, Peng Yu, Zhiyong Huang, Fangwan Fuzhou University College of Computer and Data Science Fuzhou China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

ISBN: (纸本)9798350312270

To achieve progressive and accurate decision-making for long-term time series data while meeting the needs of privacy-friendly and early, this paper proposes a universal framework for sequential progressive decision-making (SPD). This framework first segments the data and sets up multiple columns of neural networks according to the number of segments. Each column can make segmented decisions based on the inputs for the period. Additionally, without sharing the original data, the framework leverages lateral hidden layer connections between preceding and succeeding columns to obtain useful features for subsequent decision-making, gradually improving accuracy while avoiding the risk of data leakage. SPD has the advantages of privacy friendliness, column model diversification, prior knowledge reuse, and easy scalability, making it an effective framework for continuous decision-making. The effectiveness of that was validated using various network models in handwritten digit recognition and electrocardiogram classification tasks. The obtained experimental results reveal that SPD not only enables early decision-making while ensuring accuracy but also achieves accuracy levels comparable to or even surpassing those obtained using complete data, with the added benefit of privacy protection. © 2023 IEEE.

关键词： Decision making

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Large Model-Based Data Augmentation for Imbalanced Text Classification 5

Large Model-Based Data Augmentation for Imbalanced Text Clas...

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5th International Seminar on Artificial Intelligence, networking and information Technology, AINIT 2024

作者： Zhang, Dawei Mi, Rongxin Zhou, Peiyao Jin, Dawei Zhang, Manman Song, Tianhang School of Computer Science Jiangsu University of Science and Technology Jiangsu Zhenjiang China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China Key Laboratory of Intelligent Information Processing Beijing China

ISBN: (纸本)9798350385557

This study focuses on the application of large models to deal with imbalanced data problems in text classification. In view of the central position of text in web data and the negative impact of class imbalance on classifier performance, researchers have explored the method of using large models to generate high-quality minority class samples to enhance model performance. This paper reviews the technical progress of machine learning, deep learning, and large language models and their applications in text classification tasks. Although large models perform well in complex tasks due to their excellent language understanding ability, traditional machine learning and deep learning methods are popular in text classification scenarios that require fast response due to their simple structure and higher computational efficiency. This study proposes a data augmentation technique inspired by SMOTE, which uses a large language model combined with a simple prompt engineering strategy to generate high-quality minority samples. The experimental results show that the proposed method significantly improves the macro average precision, recall and F1 score on multiple text classification models, and effectively alleviates the challenge of class imbalance. © 2024 IEEE.

关键词： Computational efficiency

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Research on Cross-site Scripting Vulnerability of XSS Based on International Student Website 5

Research on Cross-site Scripting Vulnerability of XSS Based ...

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5th International Conference on computer network, Electronic and Automation, ICCNEA 2022

作者： Wang, Tianma Zhao, Dongmei Qi, Jianjun International Education Institute North China Electric Power University Beijing China Hebei Normal University College of Computer and Cyber Security Shijiazhuang China Key Laboratory of Network and Information Security in Hebei Province Shijiazhuang China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

The international student website is the window of the school's external publicity. Through the website, international students can understand the school in a wider range and in all aspects. The website is often attacked by network hackers. How to ensure the security of the website? Cross site scripting attack (XSS) is the most common web application security vulnerability. Through the analysis of cross site scripting attack (XSS), this paper puts forward the preventive methods for input verification, output coding, clearly specifying the coding mode of output, paying attention to the limitations of blacklist verification mode, being alert to standardization errors, and gives examples of not inserting untrusted data in the allowed position, and HTML coding these data when inserting untrusted data between HTML tags, Before inserting untrusted data into common HTML attributes, encode HTML attributes;before inserting untrusted data into HTML JavaScript, encode JavaScript;before inserting untrusted data into HTML style attribute values, encode CSS;before inserting untrusted data into HTML URL attributes, encode URL;when using rich text, use XSS rule engine to encode and filter and other corresponding defense rules. © 2022 IEEE.

关键词： Websites

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A Power IoT Terminal Asset Identification Technology Suitable for Modbus Protocol

A Power IoT Terminal Asset Identification Technology Suitabl...

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2024 International Conference on Interactive Intelligent Systems and Techniques, IIST 2024

作者： Li, Yong Ma, YuanYuan Chen, Mu Wang, Chao State Grid Smart Grid Research Enstitute Co. Ltd State Grid Key Laboratory of Information & Network Security Nanjing210003 China State Grid Beijing Electric Power Research Institute Beijing100075 China

ISBN: (纸本)9798350374421

In the new power system scenario, Power IoT terminals have new characteristics such as diverse hardware heterogeneity and complex subject ownership, which make it technically difficult to achieve secure access authentication based on traditional terminal hardware fingerprint recognition technology. A power IoT terminal fingerprint recognition technology suitable for the Modbus protocol is proposed to solve this problem. This method combines the characteristics of Modbus protocol packet parsing, which is a common industrial control communication protocol. Firstly, based on active packet detection technology, it realizes the survival judgment of business terminals and constructs a coarse-grained topology image of terminal production. Then, by passively monitoring and analyzing the characteristics of terminal interaction traffic behavior, a terminal behavior fingerprint recognition model is constructed based on the deep learning algorithm BiLSTM to achieve accurate terminal type discrimination, thereby establishing a power IoT terminal fingerprint recognition model. The experimental results in a distributed photovoltaic scenario show that the method has an average classification and recognition accuracy of 89.6% for common power business terminals, which can basically meet the lightweight and non-invasive business requirements of terminal fingerprint recognition in new power system scenarios. © 2024 IEEE.

关键词： Deep learning

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Scheduling Multiple Mobile Agents with Abilities of Sensing and Executing Simultaneously

Scheduling Multiple Mobile Agents with Abilities of Sensing ...

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2023 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2023

作者： Guo, Zhipeng Yu, Zhiyong Huang, Fangwan Tu, Chunyu Fuzhou University College of Computer and Data Science Fuzhou China Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

ISBN: (纸本)9798350312270

How to schedule public resources to maximize the coverage of crowds has always been a hot topic. There are mainly two types of research. One is the scheduling of static resources, whose coverage efficiency is lower because the resources cannot be moved;the other is the dynamic scheduling of movable public resources, but the existing methods require additional devices to collect crowd volume data. To address this issue, this article introduces a new category of mobile agents that can sense and execute simultaneously. This means that an agent can simultaneously perform crowd volume data collection tasks and crowds coverage tasks in its area. Taking these multi-ability agents as public resources, this article proposes a scheduling method called GE-STMC (Greedy Execute - Spatial and Temporal Monte-Carlo dropout). The method considers the spatiotemporal correlation between areas and evaluates the sensing value and the executing value of areas comprehensively to allocate the agents accordingly. Through the experimental on the real data of Beijing Happy Valley, this method can get 16% larger crowds volume coverage than other baseline methods with the same number of agents. © 2023 IEEE.

关键词： Mobile agents

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Energy Efficiency Maximization for Aerial RIS-Aided Over-the-Air Federated Learning

Energy Efficiency Maximization for Aerial RIS-Aided Over-the...

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IEEE Conference on Wireless Communications and networking

作者： Yuan Ren Zeyang Wang Xuewei Zhang Guangyue Lu Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Compared with terrestrial reconfigurable intelligent surface (RIS), aerial RIS provides improved transmission performance owing to its high adaptability in three-dimensional space and the existence of established line-of-sight links. In this paper, we study an aerial RIS-aided over-the-air federated learning (AirFL) system and propose an effective resource allocation scheme to maximize the energy efficiency (EE) of the AirFL system, where the transmit power of the Internet-of-Things devices, the receive scalar at the base station (BS), and the phase shifts of the RIS are jointly optimized. Since the formulated EE maximization problem consists of coupled variables, it is essentially non-convex. The original problem is then transformed into several sub-problems, which are addressed by adopting Dinkelbach's method, successive convex approximation and difference-of-convex programming approach. Finally, simulation results demonstrate that the proposed scheme is superior in terms of the EE performance for RIS-aided AirFL system compared with the existing scheme.

关键词： Performance evaluation Federated learning Wireless networks Simulation Reconfigurable intelligent surfaces Programming Energy efficiency

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A Task Offloading and Resource Allocation Strategy Based on Improved WSO for Internet of Vehicles

A Task Offloading and Resource Allocation Strategy Based on ...

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2023 IEEE/CIC International Conference on Communications in China, ICCC Workshops 2023

作者： Jiang, Fan He, Guangxue Liu, Lei Su, Heyu Wang, Chaowei Shaanxi Key Laboratory of Information Communication Network and Security Xi'an China Xi'an University of Posts and Telecommunications Xi'an China Beijing University of Posts and Telecommunications School of Electronic Engineering Beijing China

ISBN: (纸本)9798350345407

In this paper, we investigate a task offloading and resource allocation strategy concerning multi-access edge computing (MEC) servers and multi-vehicles in the Internet of Vehicles (IoV). Aiming at dealing with resource allocation issues involved with the task offloading procedure, we first formulate the task offloading problem to minimize the average cost. Next, the improved War Strategy optimization (WSO) algorithm is introduced to solve the resource allocation issue. In particular, combined with stringent delay and energy requirements, the improved WSO algorithm is employed in several iterations processes to achieve optimal offloading decisions and resource allocation policies. Simulation results further demonstrate that the proposed strategy significantly reduces the average cost and improves the task offloading efficiency in the IoV compared with benchmark schemes. © 2023 IEEE.

关键词： Resource allocation

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YOLOv5 Algorithm Optimization: Precise Target Detection Amidst Background Interference 4

YOLOv5 Algorithm Optimization: Precise Target Detection Amid...

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4th International Conference on Consumer Electronics and computer Engineering, ICCECE 2024

作者： Xiong, Bingbing Shi, Wenxi Fu, Yanyun Zhu, Zhansheng Wang, Deyong Jia, Bin School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Lianhaichuangzhi Information Technology Co. Ltd. Key Laboratory of Big Data of Xinjiang Social Security Risk Beijing China Beijing Academy of Science and Technology Beijing China Xinjiang Lianhaichuangzhi Information Technology Co. Ltd. Key Laboratory of Big Data of Xinjiang Social Security Risk Urumqi China

ISBN: (纸本)9798350384062

This paper solves the challenge that the target is submerged in the background in the border security scenario, and proposes the enhancement of YOLOv5 algorithm. EfficientViT replaces the DarkNet backbone, leveraging Transformer models for improved feature extraction. Modifications to the Spatial Pyramid Pooling-Fast (SPPF) module enhance the algorithm's robustness to scale variations. Introducing SCYLLA-IoU (SIoU) in the loss function improves model convergence speed and accuracy. Validated on a custom border security dataset, the enhancements show an improved average precision mean (mAP) of 48.3%, a 2.2 percentage point increase over the original YOLOv5s model. © 2024 IEEE.

关键词： Border security Target Detection Transformer YOLOv5

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Structured Fourier Contour Embedding for Arbitrary-shaped Slender Text Detection 3

Structured Fourier Contour Embedding for Arbitrary-shaped Sl...

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3rd International Conference on Artificial Intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Chen, Jianyong Liang, Lingyu Xiao, Wocheng South China University of Technology Guangzhou China Guangzhou China Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing China

ISBN: (纸本)9781510671485

Arbitrary-shaped text detection is a challenging task where a text instance representation should be well designed to cover diverse text geometry variances. Most of current methods represent text instances as image mask or contour point sequences, but they might lead to expensive post-processing or restricted capability of shape modeling. Most recently, Zhu et al. proposed Fourier Contour Embedding (FCE) method to represent arbitrary shaped text contours in the Fourier domain, and constructed FCENet to obtain state-of-the-art (SOTA) performance. However, even the FCE signature and FCENet may suffer significant detection performance degradation on slender-shaped text instances like most other text detectors because of the mismatch between the square-shaped receptive fields and the large aspect ratio of arbitrary-shaped slender text}. To tackle this problem, we designed Structured Fourier Contour Embedding (Structured-FCE) to encode both instance-level features and local geometric features of the boundaries. Then, we constructed Structured-FCENet to predict and merge Structured-FCE signatures to construct the boundaries of arbitrary-shaped slender texts. Qualitative and quantitative results illustrate that Structured-FCENet obtain SOTA performance on CTW1500, Total-Text and DAST1500 benchmark datasets, especially for the challenging slender text instances of various shape. © 2023 SPIE.

关键词： computer vision

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