检索结果-内蒙古大学图书馆

Informatica (Slovenia) 2025年第16期49卷 21-36页

作者： Zhang, Yuan Xuchang Vocational Technical College Xuchang461000 China Henan Province Data Intelligence and Security Application Engineering Technology Research Center Xuchang461000 China

The popularity and deepening of social networks have increased the risk of personal information leakage for users. To enhance the security of social networks, this study constructed an access control model based on the preferences of social network users. This model utilizes graph neural networks to generate access control strategies based on user preferences, and introduces a multi-layer attention mechanism to optimize the graph neural network. To better capture user preference information, the study sets the learning rate to 0.0001. The experimental results demonstrated that in the Twitter dataset, the accuracy of the proposed model reached 95.7% and the F1 score reached 96.2%, which were significantly higher than those of other models. These results indicated that the model could more accurately classify access control in social networks and reduce false positives. The area under the receiver operation characteristic curve of the proposed model was 0.982, which was higher than other models. The decision time was 13.77 seconds, significantly lower than other models. This indicated that the model could more effectively distinguish different types of user access requests and provide more reliable guarantees for secure access to social networks. The user's preferred social network access control model based on graph neural networks has superior performance, effectively ensuring the information security of social network users and laying the foundation for further development of access control technology. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Access control models

来源：评论

学校读者我要写书评

暂无评论

TPE for JPEG images with Dynamic M-ary Decomposition and Adaptive Threshold Constraints

引用

IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Ma, Yakun Chai, Xiuli Long, Guoqiang Gan, Zhihua Zhang, Yushu Henan University School of Artificial Intelligence Henan Engineering Research Center for Industrial Internet of Things Zhengzhou450046 China Henan University School of Software Intelligent Data Processing Engineering Research Center of Henan Province Institute of Intelligent Network System Kaifeng475004 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing211106 China

Traditional JPEG image encryption that prioritizes solely confidentiality fails to account for the pressing usability requirements of cloud-based environments, thus boosting the boom in thumbnail-preserving encryption (TPE) to balance image privacy and usability. However, existing TPE schemes for JPEG images face numerous challenges, such as insufficient security, inability to achieve lossless decryption, and high file extension. To address these challenges, we propose a TPE scheme based on dynamic M-ary decomposition and adaptive threshold constraints (TPE-MDTC). First, the valid ranges of quantized DC coefficients for JPEG images are determined. Then, a sum-preserving encryption method for quantized DC coefficients with compliance threshold constraints is designed using the bit-plane permutation to preserve thumbnails with high accuracy. Next, the introduction of dynamic M-ary decomposition effectively changes bit statistical characteristics preserved by bit-plane permutation, enhancing the ciphertext security. Finally, a quantized AC encryption method with RV (Run/Value) pair global permutation is proposed, effectively modifying the unit block features, thereby significantly improving the security and attack resistance of encrypted images. Experimental results show that the proposed TPE-MDTC scheme can reconstruct the original JPEG images without loss, and the generated ciphertext images exhibit significant advantages over previous schemes regarding file extension and security. © 1991-2012 IEEE.

关键词： Ciphertext

来源：评论

学校读者我要写书评

暂无评论

Construction of embedded online teaching platform based on AES-RSA encryption algorithm

引用

Discover Artificial intelligence 2024年第1期4卷 1-16页

作者： Kong, Xiaojing Yue, Guanli Xuchang Vocational Technical College Xuchang China Henan Engineering Research Center of Data Intelligence and Security Application Xuchang China

With the development of economy, people's demand for high-quality and diversified educational resources increases. However, under the frequent occurrence of network attacks, data leakage and other events, network security and information security need to be solved urgently by the current online teaching platform. To this end, the research adopts Advanced Encryption Standard encryption algorithm and introduces Rivest-Shamir-Adleman to improve it, and applies it to construct an embedded online teaching platform, aiming to ensure user’s personal information security. Experimentally, the decryption speed of the Advanced Encryption Standard-Rivest-Shamir-Adleman encryption algorithm stays around 100 ms when the number of bytes is below 60. When file size increasing, the encryption time of the proposed algorithm increases minimally. Also, the key generation time of the algorithm is always less than 1500 ms, and the average time taken to defend the online teaching platform against brute force attacks can be up to 232.1 ms. In addition, the research algorithm has the best scalability, the platform obfuscation is better, and the platform always has the lowest ciphertext bit count. In conclusion, it can be seen that the embedded online teaching platform of the study has the best confidentiality of user information, which guarantees the confidentiality and integrity of learners' personal information and teaching resources. Strong encryption technology provides solid security for the application of online education platforms, allowing educational innovation to take place in a more secure and controlled environment. © The Author(s) 2024.

关键词： Encryption algorithms

来源：评论

学校读者我要写书评

暂无评论

Endoplasmic Reticulum Stress and NLRP3 Inflammasome Activation Underlie Silver Nanoparticles-Induced Neurologic Deficits in Adult Mice

引用

Journal of Biochemical and Molecular Toxicology 2025年第6期39卷

作者： Wenhui Zhang Mengdi Zhai Meijia Wu Yongke Yuan Xiao Su Mingzhi Yang Yue Ba Qihong Deng Yu Zhang Lin Han Lihua Gao Hui Huang Department of Environmental Health College of Public Health Zhengzhou University Zhengzhou Henan province China State Key Laboratory of Microbial Technology Qingdao Shandong China Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application Jinan Shandong China Institute of Marine Science and Technology Shandong University Qingdao Shandong China Zhengzhou Center for Disease Control and Prevention Zhengzhou Henan China

Silver nanoparticles (AgNPs) are extensively mass-produced and widely utilized across diverse fields owing to their potent bactericidal properties. Nevertheless, prior research regarding the distribution of AgNPs In Vivo has revealed that they can penetrate into and accumulate in brain tissue, potentially leading to neurotoxicity. In the current study, we initially delved into the impacts of different dosages of AgNPs (10−250 mg/kg body weight) on behavioral cognitive function. After 28 days of oral ingestion of AgNPs, we observed impaired learning and memory performance in the high-dose-treated group of mice. Moreover, we evaluated the alterations in molecules associated with endoplasmic reticulum (ER) stress and the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome, conducting a preliminary exploration of the neurotoxic mechanisms of AgNPs. The results demonstrated that subacute oral exposure to AgNPs might disrupt cognitive function via the ER stress and NLRP3 inflammasome activation pathways. Our data highlight the neurotoxic effects of AgNPs and the significant role played by NLRP3 inflammasome activation in neurological deficits.

关键词： neurological lesion NOD-like receptor protein 3 inflammasome pro-inflammatory cascade silver nanoparticles unfolded protein response

来源：评论

学校读者我要写书评

暂无评论

Adaptive offloading scheme of fine-grained tasks based on reinforcement learning in multi-access edge computing

引用

Simulation Modelling Practice and Theory 2025年

作者： Jie Li Ge Chen Kansong Chen School of Computer Science and Information Engineering Hubei University Wuhan 430062 China Hubei Key Laboratory of Big Data Intelligent Analysis and Application (Hubei University) Wuhan 430062 China Engineering Research Center of Hubei Province in Intelligent Government Affairs and Application of Artificial Intelligence Wuhan 430062 China Key Laboratory of Intelligent Sensing System and Security (Hubei University) Ministry of Education Wuhan 430062 China

In the context of multi-access edge computing, the constraints on device resources and energy pose a challenge in meeting the requirements of delay-sensitive and high-resource demand tasks. In order to address this issue, this paper puts forth an adaptive offloading decision based on fine-grained task sequencing (AOD-FTS). To enhance task execution efficiency and resource utilization, we design scheduling optimization for subtasks algorithm within the fine-grained task model to optimize the execution order of subtasks and improve subtask parallelism. Additionally, to reduce task delay and energy consumption, we propose an adaptive multi-objective reinforcement learning offloading algorithm based on ordered subtasks, formulated through multi-objective Markov decision processes. The scheme dynamically adjusts optimization preferences according to environmental changes and task completion states to make offloading decisions. Simulation results demonstrate that compared with two benchmark algorithms, the proposed AOD-FTS scheme achieves: (1) higher task completion rates, (2) improved resource utilization efficiency, (3) 81.66% and 51.53% reductions in delay respectively, and (4) 39.72% and 71.36% reductions in energy consumption respectively.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A hybrid Chinese named entity recognition method for Internet of Things

A hybrid Chinese named entity recognition method for Interne...

引用

2022 International Conference on Algorithms, Microchips and Network applications

作者： Wang, Ying Wang, Zehao Li, Hong Liu, Peipei Li, Yachao Zuo, Fang Institute of Intelligence Networks System Henan University Henan475001 China Henan Experimental Teaching Demonstration Centre of Modern Network Technology Henan University Henan475001 China Intelligent Data Processing Engineering Research Center of Henan Province Henan University Henan475001 China Institute of Information Engineering Chinese Academy of Sciences Beijing China Henan International Joint Laboratory of Theories and Key Technologies on Intelligence Networks Henan University Henan475001 China

ISBN: (纸本)9781510653290

In order to facilitate government departments to assess security risks and prevent infiltration, it's necessary to recognize the IoT device from open data by the method of Named entity recognition (NER). In this study, a hybrid method of chinese NER which contains neural networks and templates is proposed to extract IoT device information from open web. The model first initiates characters of input through BERT, which can create character embedding while reduce dependency with external datasets. Then, the initiated vectors are fed into a multi-layers BiLSTM model to encode the contextual representation of each character, and a linear CRF layer after BiLSTM is used to assign the scores to every character for entity annotation. In addition, a dictionary and rule base is constructed based on the characteristics of IoT devices to correct the annotation results. We experimented the methods on the dataset of IoT, the results prove the proposed model achieves better recognition effect than other models, and the F-scores value is 88.9%. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

TPE-H2MWD:an exact thumbnail preserving encryption scheme with hidden Markov model and weighted diffusion

引用

Frontiers of Information technology & Electronic engineering 2023年第8期24卷 1169-1180页

作者： Xiuli CHAI Xiuhui CHEN Yakun MA Fang ZUO Zhihua GAN Yushu ZHANG School of Artificial Intelligence Henan Engineering Research Center for Industrial Internet of ThingsHenan UniversityZhengzhou450046China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450001China School of Software Intelligent Data Processing Engineering Research Center of Henan ProvinceInstitute of Intelligent Network SystemHenan UniversityKaifeng475004China College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing211106China

With the substantial increase in image transmission,the demand for image security is ***-like images can be obtained by conventional encryption schemes,and although the security of the images can be guaranteed,the noise-like images cannot be directly previewed and *** on the rank-then-encipher method,some researchers have designed a three-pixel exact thumbnail preserving encryption(TPE2)scheme,which can be applied to balance the security and availability of images,but this scheme has low encryption *** this paper,we introduce an efficient exact thumbnail preserving encryption ***,blocking and bit-plane decomposition operations are performed on the plaintext *** zigzag scrambling model is used to change the bit positions in the lower four bit ***,an operation is devised to permute the higher four bit planes,which is an extended application of the hidden Markov ***,according to the difference in bit weights in each bit plane,a bit-level weighted diffusion rule is established to generate an encrypted image and still maintain the same sum of pixels within the *** results show that the proposed scheme improves the encryption efficiency and can guarantee the availability of images while protecting their privacy.

关键词： Hidden Markov model Weighted diffusion Balance between usability and privacy Image encryption

来源：评论

学校读者我要写书评

暂无评论

research on Sentiment Dictionary Based on Sentiment Analysis in News Domain 7

Research on Sentiment Dictionary Based on Sentiment Analysis...

引用

7th IEEE International Conference on Big data security on Cloud, 7th IEEE International Conference on High Performance and Smart Computing, and 6th IEEE International Conference on Intelligent data and security, Bigdatasecurity/HPSC/IDS 2021

作者： Gao, Yihang Su, Peng Zhao, Hui Qiu, Meikang Liu, Meiqin Henan International Joint Laboratory of Theories Key Technologies on Intelligence Networks Henan University Kaifeng China Intelligent Data Processing Engineering Research Center of Henan Province Henan University Kaifeng China Educational Information Technology Laboratory Henan University Kaifeng China Texas Am University-Commerce Department of Computer Science CommerceTX75428 United States College of Electrical Engineering Zhejiang University Hangzhou310027 China

ISBN: (纸本)9781665439275

The known Chinese sentiment dictionary has universal applicability, lacks the expansion of proprietary domains, and lacks support for network words. This paper proposes a new approach and applies it to the Internet news sentiment analysis text provided by the CCF Big data Computing intelligence Contest. First, the corpus is segmented in Chinese to obtain candidate sentiment words that have not appeared in the sentiment dictionary. The candidate sentiment words are calculated in different sentimental texts. The proportion of appearance is obtained, and the emotional tendency of candidate emotional words is obtained, and then it is merged with the emotional vocabulary ontology database to obtain the expanded emotional dictionary. Experiments show that the expanded sentiment dictionary is better than the known Chinese sentiment vocabulary ontology database in the above corpus. © 2021 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：