As companies grow, the company's talent is growing, its projects are increasing, and its information assets are growing, it becomes essential to protect information security. This paper explains and analyses the security issues by using qualitative analysis approach and gives information security management solutions to protect information assets. By redesigning the company structure, assessing security risks, generating information system security management plan and establishing information security management system.
{"title":"Information security issues analysis and solution","authors":"Zichun Zhao","doi":"10.1117/12.2653836","DOIUrl":"https://doi.org/10.1117/12.2653836","url":null,"abstract":"As companies grow, the company's talent is growing, its projects are increasing, and its information assets are growing, it becomes essential to protect information security. This paper explains and analyses the security issues by using qualitative analysis approach and gives information security management solutions to protect information assets. By redesigning the company structure, assessing security risks, generating information system security management plan and establishing information security management system.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81133130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, the identification system of sugarcane was studied based on the pre-seed cutting sugarcane planter developed in the laboratory to solve the problems of uneven cane discharging and high seed leakage rate. Firstly, simple structure analysis and system design of sugarcane planter are carried out. Secondly, histogram equalization algorithm is applied to enhance the image based on the real-time feedback of the camera. Thirdly, the template matching method is used to extract sugarcane images. Finally, the obtained sugarcane images were morphologic processed to obtain the surface texture information of sugarcane, and the information of sugarcane body and sowing situation were recorded through system recognition feedback.
{"title":"OpenCV based detection and recognition system of pre-seed cutting sugarcane planter","authors":"Haofeng Deng, Jiyue Wang, Liucun Zhu, Mingyou Chen, Hongwei Wu","doi":"10.1117/12.2653446","DOIUrl":"https://doi.org/10.1117/12.2653446","url":null,"abstract":"In this paper, the identification system of sugarcane was studied based on the pre-seed cutting sugarcane planter developed in the laboratory to solve the problems of uneven cane discharging and high seed leakage rate. Firstly, simple structure analysis and system design of sugarcane planter are carried out. Secondly, histogram equalization algorithm is applied to enhance the image based on the real-time feedback of the camera. Thirdly, the template matching method is used to extract sugarcane images. Finally, the obtained sugarcane images were morphologic processed to obtain the surface texture information of sugarcane, and the information of sugarcane body and sowing situation were recorded through system recognition feedback.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76254268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
W. Xie, Xin Pu, Guanghui Tao, Angxuan Li, Chuang Chen, Lili Wang
Aiming at the problems of location and time limitations arising from the field visits in life, and then taking Changchun Institute of Technology as an example, a virtual campus roaming system based on Unity3D was developed to solve the problem of poor environmental simulation of traditional inspection methods. The system can improve the visual tension and expressiveness of users visiting the campus online, so that we can facilitate school publicity and promotion. First of all, the system uses 3DMax to accurately model the campus site, and then uses Unity to design and implement the functions, so that the system has the characteristics of high presence and strong interaction, thereby improving the user experience.
{"title":"Virtual campus roaming system design","authors":"W. Xie, Xin Pu, Guanghui Tao, Angxuan Li, Chuang Chen, Lili Wang","doi":"10.1117/12.2653782","DOIUrl":"https://doi.org/10.1117/12.2653782","url":null,"abstract":"Aiming at the problems of location and time limitations arising from the field visits in life, and then taking Changchun Institute of Technology as an example, a virtual campus roaming system based on Unity3D was developed to solve the problem of poor environmental simulation of traditional inspection methods. The system can improve the visual tension and expressiveness of users visiting the campus online, so that we can facilitate school publicity and promotion. First of all, the system uses 3DMax to accurately model the campus site, and then uses Unity to design and implement the functions, so that the system has the characteristics of high presence and strong interaction, thereby improving the user experience.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85548659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to meet the diversified needs of Japanese learning, this study, combined with the concept of Internet +, conducts research on the construction of WeChat public platform for Japanese learning. Firstly, the relevant research concepts and the basic architecture of the platform are determined, and then the database and relevant important technologies applied in the platform are discussed in detail. Finally, on this basis, the expected functional modules of the WeChat public platform for Japanese learning are described, so as to provide reference for future teaching and learning based on the WeChat public platform.
{"title":"Construction of WeChat public platform for Japanese learning based on Internet+","authors":"Jingshu Yao","doi":"10.1117/12.2653571","DOIUrl":"https://doi.org/10.1117/12.2653571","url":null,"abstract":"In order to meet the diversified needs of Japanese learning, this study, combined with the concept of Internet +, conducts research on the construction of WeChat public platform for Japanese learning. Firstly, the relevant research concepts and the basic architecture of the platform are determined, and then the database and relevant important technologies applied in the platform are discussed in detail. Finally, on this basis, the expected functional modules of the WeChat public platform for Japanese learning are described, so as to provide reference for future teaching and learning based on the WeChat public platform.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77847115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sarcasm detection aims to identify whether a text is sarcastic or not. In this paper, we propose a knowledge- and sentiment-enriched framework. Instead of modeling users' features or searching word pairs and snippets with sentiment conflicts in text, our framework integrates dialogue-related external knowledge and leverages inter-sentence sentiment to aid understanding sarcasm with the discussion context. Experiments on two discussion datasets show that our proposed framework yields better performance with enriched knowledge and sentiment information.
{"title":"Enhancing sarcasm detection with external knowledge","authors":"WangQun Chen, Guowei Li, Zheng You, Bo Liu","doi":"10.1117/12.2653533","DOIUrl":"https://doi.org/10.1117/12.2653533","url":null,"abstract":"Sarcasm detection aims to identify whether a text is sarcastic or not. In this paper, we propose a knowledge- and sentiment-enriched framework. Instead of modeling users' features or searching word pairs and snippets with sentiment conflicts in text, our framework integrates dialogue-related external knowledge and leverages inter-sentence sentiment to aid understanding sarcasm with the discussion context. Experiments on two discussion datasets show that our proposed framework yields better performance with enriched knowledge and sentiment information.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77919533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yanfang Fu, Chengli Wang, Fang Wang, LiPeng S., Zhi-Ye Du, Zijian Cao
To address the scenario that there is the subjectivity of prior probability in the attack graph after the introduction of Bayesian network in the network attack model and the failure of attack nodes is not considered, an optimization scheme of the Bayesian attack graph and an intelligent construction method of attack path based on this scheme are proposed. The risk value of the target network is calculated to avoid the subjectivity of the prior probability and the devices are abstracted as attack graph nodes, and the atomic attacks are used as causal inference relations to reconstruct the attack graph. The analysis results show that the method has a significant improvement in the speed of attack graph and attack path generation and attack success rate, and it can perform the intelligent construction of attack path when the attack nodes fail.
{"title":"An intelligent method for building attack paths based on Bayesian attack graphs","authors":"Yanfang Fu, Chengli Wang, Fang Wang, LiPeng S., Zhi-Ye Du, Zijian Cao","doi":"10.1117/12.2653480","DOIUrl":"https://doi.org/10.1117/12.2653480","url":null,"abstract":"To address the scenario that there is the subjectivity of prior probability in the attack graph after the introduction of Bayesian network in the network attack model and the failure of attack nodes is not considered, an optimization scheme of the Bayesian attack graph and an intelligent construction method of attack path based on this scheme are proposed. The risk value of the target network is calculated to avoid the subjectivity of the prior probability and the devices are abstracted as attack graph nodes, and the atomic attacks are used as causal inference relations to reconstruct the attack graph. The analysis results show that the method has a significant improvement in the speed of attack graph and attack path generation and attack success rate, and it can perform the intelligent construction of attack path when the attack nodes fail.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88440260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Weiqin Huang, Yikai Gu, Yulong Fu, Yongfu Li, Yue Han
To better achieve image correction effect, an image correction method based on corner point detection is proposed. In image preprocessing, firstly, image equalization is achieved based on the contrast limited adaptive histgram equalization to avoid the problems caused by illumination and suppress noise while maintaining details, and then adaptive threshold segmentation is performed using the OTSU to obtain the binarized image. In the corner point detection stage, the contours of the binarized image are extracted firstly and the closed contours are filled to avoid the independent contours from affecting the accuracy of region growth, then the center point of the image is used as the seed pixel for region growth, and finally the four corner points are calculated based on the linear contours of the growth region and Hough theory, where the accurate region growth result can avoid the influence of the background on the corner point detection. In the correction stage, the perspective matrix is calculated by the four corner points, and the image is corrected by the perspective transformation. The experiments show that the proposed method can accurately find the corner points of document images and achieve efficient correction.
{"title":"An image correction method based on corner point detection","authors":"Weiqin Huang, Yikai Gu, Yulong Fu, Yongfu Li, Yue Han","doi":"10.1117/12.2653505","DOIUrl":"https://doi.org/10.1117/12.2653505","url":null,"abstract":"To better achieve image correction effect, an image correction method based on corner point detection is proposed. In image preprocessing, firstly, image equalization is achieved based on the contrast limited adaptive histgram equalization to avoid the problems caused by illumination and suppress noise while maintaining details, and then adaptive threshold segmentation is performed using the OTSU to obtain the binarized image. In the corner point detection stage, the contours of the binarized image are extracted firstly and the closed contours are filled to avoid the independent contours from affecting the accuracy of region growth, then the center point of the image is used as the seed pixel for region growth, and finally the four corner points are calculated based on the linear contours of the growth region and Hough theory, where the accurate region growth result can avoid the influence of the background on the corner point detection. In the correction stage, the perspective matrix is calculated by the four corner points, and the image is corrected by the perspective transformation. The experiments show that the proposed method can accurately find the corner points of document images and achieve efficient correction.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86416844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Deep learning techniques have been widely used in the field of Side Channel Attack (SCA), which poses a serious threat to the security of cryptographic algorithms. However, deep learning-based side channel attack also has problems such as inefficient models, poor robustness, and longtime consumption. To address these problems, this paper focuses on the performance of Long Short-term Memory(LSTM) combining with the dimensional compression technique of Sparse Auto Encoder (SAE), and validates it on fully synchronized and unsynchronized EM traces captured under first-order bool mask protection. The experimental results show that compared with multilayer perceptron (MLP) and convolutional neural network (CNN), LSTM achieves more than 90% training accuracy and test accuracy, with higher robustness, lower parameters and faster convergence speed, even when the jitter in the dataset increases from 0 to 50 and 100.
{"title":"Research on electromagnetic attack of advanced encryption standard based on long short-term memory and sparse autoencoder","authors":"Bo Gao, Lin Chen, Yingjian Yan","doi":"10.1117/12.2653520","DOIUrl":"https://doi.org/10.1117/12.2653520","url":null,"abstract":"Deep learning techniques have been widely used in the field of Side Channel Attack (SCA), which poses a serious threat to the security of cryptographic algorithms. However, deep learning-based side channel attack also has problems such as inefficient models, poor robustness, and longtime consumption. To address these problems, this paper focuses on the performance of Long Short-term Memory(LSTM) combining with the dimensional compression technique of Sparse Auto Encoder (SAE), and validates it on fully synchronized and unsynchronized EM traces captured under first-order bool mask protection. The experimental results show that compared with multilayer perceptron (MLP) and convolutional neural network (CNN), LSTM achieves more than 90% training accuracy and test accuracy, with higher robustness, lower parameters and faster convergence speed, even when the jitter in the dataset increases from 0 to 50 and 100.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81045732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To address the error propagation problem of joint modeling of biomedical named entity recognition and normalization, joint label is designed to combine entity labels with concept labels to jointly label each term in the sentence, the joint learning task is transformed into a multiclass classification problem. A joint model of biomedical entity recognition and normalization labels based on self-attention is designed, the pre-training model BioBERT is used to encode the medical text. After extracting the joint label information using the self-attention mechanism, it is fused with the input sequence information. Finally, the final joint label representation is obtained by softmax. The experimental results show that the F1 values of the entity recognition and normalization tasks on the NCBI dataset reach 83.3% and 84.5%, and the F1 values on the BC5CDR dataset reach 84.2% and 86.6%, which are better compared with existing methods.
{"title":"Joint model of biomedical entity recognition and normalization labels based on self-attention","authors":"Dandan Zhou, Tong Liu","doi":"10.1117/12.2653583","DOIUrl":"https://doi.org/10.1117/12.2653583","url":null,"abstract":"To address the error propagation problem of joint modeling of biomedical named entity recognition and normalization, joint label is designed to combine entity labels with concept labels to jointly label each term in the sentence, the joint learning task is transformed into a multiclass classification problem. A joint model of biomedical entity recognition and normalization labels based on self-attention is designed, the pre-training model BioBERT is used to encode the medical text. After extracting the joint label information using the self-attention mechanism, it is fused with the input sequence information. Finally, the final joint label representation is obtained by softmax. The experimental results show that the F1 values of the entity recognition and normalization tasks on the NCBI dataset reach 83.3% and 84.5%, and the F1 values on the BC5CDR dataset reach 84.2% and 86.6%, which are better compared with existing methods.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75191850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Deep learning technology has yielded good results in remote sensing image recognition of vehicles, but most existing recognition network models have poor interpretability, which limits its wide application. In order to achieve effective detection and recognition of vehicles in the complex environment, in this paper, the YOLOv4 is adopted to realize remote sensing images for vehicle target recognition. In addition, the optimized interpretation method with LIME is used to interpret the recognition results, improving the credibility of the recognition results.
{"title":"Interpretable analysis of remote sensing image recognition of vehicles in the complex environment","authors":"Yuxin Huo, Yizhuo Ai, Chengqiang Zhao, Yuanwei Li","doi":"10.1117/12.2653489","DOIUrl":"https://doi.org/10.1117/12.2653489","url":null,"abstract":"Deep learning technology has yielded good results in remote sensing image recognition of vehicles, but most existing recognition network models have poor interpretability, which limits its wide application. In order to achieve effective detection and recognition of vehicles in the complex environment, in this paper, the YOLOv4 is adopted to realize remote sensing images for vehicle target recognition. In addition, the optimized interpretation method with LIME is used to interpret the recognition results, improving the credibility of the recognition results.","PeriodicalId":32903,"journal":{"name":"JITeCS Journal of Information Technology and Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72934682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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