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JITeCS Journal of Information Technology and Computer Science最新文献

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Research on vulnerability of classification method of a complex information system 复杂信息系统分类方法脆弱性研究
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653789
Yuan Wei, Keli Zhang, Ning Yang, G. Li
{"title":"Research on vulnerability of classification method of a complex information system","authors":"Yuan Wei, Keli Zhang, Ning Yang, G. Li","doi":"10.1117/12.2653789","DOIUrl":"https://doi.org/10.1117/12.2653789","url":null,"abstract":"With the development of science and technology, the demand for automation and intelligence has nearly penetrated every corner of society. Single software and specific needs of information systems can no longer meet the growing needs of people. A complex information system composed of various systems, smart devices, and software emerged. The security of such complex information systems is becoming increasingly important. Attacks on complex information systems have become an important factor in harming national security, political stability, economic lifeline, and citizen security. Risk factors are weak links in the information system that may be threatened to cause damage, and the risk factors are transformed into damage to assets under certain conditions. Although the existing vulnerability management specification standards contain relevant content of risk assessment, the scope is not enough to support and cover the assessment of risk factors in information systems. In this paper, we comprehensively investigate and analyze the vulnerability standards of various vulnerability classification for information systems, and propose a classification standard for the analysis and grading of risk factors of complex information systems, which can provide a reference for the classification of information system risk factors in finance, public communications, and energy industries.","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":"88483119","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}
引用次数: 0
SGCN: spatially gradient convolution network for certificate document image manipulation localization SGCN:用于证书文档图像处理定位的空间梯度卷积网络
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653519
Baoxiang Jiang, Jingbo Xia, Bingjing Wu, Zhigong Wei
{"title":"SGCN: spatially gradient convolution network for certificate document image manipulation localization","authors":"Baoxiang Jiang, Jingbo Xia, Bingjing Wu, Zhigong Wei","doi":"10.1117/12.2653519","DOIUrl":"https://doi.org/10.1117/12.2653519","url":null,"abstract":"Current tampering detection methods pay more attention to natural content images. The research on tampering algorithms for certificate document images is relatively limited, but certificate document images are the most commonly tampered with images, and they cause great harm to society. Our work presents a method for detecting certificate-like image manipulation using the ASGC-Net network. To achieve a network that can better localize text tampering cues. In addition, we propose a spatially constrained convolution that can effectively suppress image content and learn manipulation detection features by capturing different features between the neighborhood and the center of the convolution space. To increase the network's ability to capture tampering cues at multiple scales of images, we add multilayer cross-scale connections inspired by FPN networks. Experiments show that the algorithm is more accurate than general-purpose manipulation detection algorithms in locating tampered regions of certificate document images.","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":"84052501","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}
引用次数: 1
A feature extraction algorithm for missing trajectory data clustering 缺失轨迹数据聚类的特征提取算法
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653456
Xintai He, Qing Li, Runze Wang, Kung-Hao Chen
{"title":"A feature extraction algorithm for missing trajectory data clustering","authors":"Xintai He, Qing Li, Runze Wang, Kung-Hao Chen","doi":"10.1117/12.2653456","DOIUrl":"https://doi.org/10.1117/12.2653456","url":null,"abstract":"Feature extraction is one of the critical technologies in trajectory data clustering. Extracting useful features for trajectory clustering is a difficult problem when there are missing segments in trajectories. This paper proposes a feature extraction algorithm for missing trajectories clustering. The algorithm converts trajectories into images, a multi-layer image preprocessing method is proposed to reduce the information loss during image processing. Then build an autoencoder to extract image features. The loss function is designed according to the attention mechanism to highlight the effective information in the trajectory image. The autoencoder’s ability to handle missing trajectory segments is trained by adding artificial image masking. The effect of feature extraction is verified by clustering. Compared with the unimproved autoencoding and interpolation methods, the clustering effect of the features extracted by this algorithm is improved. At missing rate 50%, this is an increase of eight and six percentage points, respectively. It is proved that the algorithm in this paper is more suitable for missing trajectory feature extraction.","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":"81923563","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}
引用次数: 0
Roaming design of the virtual village system 虚拟村庄系统的漫游设计
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653688
Haopeng Guo, Xin Pu, Xiaolu Wang, Xin Guo, Yaotian Fei, Yifan Cao, Chi Chen, Lili Wang
{"title":"Roaming design of the virtual village system","authors":"Haopeng Guo, Xin Pu, Xiaolu Wang, Xin Guo, Yaotian Fei, Yifan Cao, Chi Chen, Lili Wang","doi":"10.1117/12.2653688","DOIUrl":"https://doi.org/10.1117/12.2653688","url":null,"abstract":"According to the national policy of rural revitalization, combined with the new technology of the current era, it has comprehensively opened a new pattern of rural construction, effectively combined with the strategic deployment of the Party Central Committee, and improved the deficiencies of some problems in Rural Revitalization. Through field investigation, we use virtual reality technology to highly simulate and restore the rural cultural heritage and its local characteristics. \"VR add rural tourism\" will be an important part of the Rural Revitalization Strategy. We should fully stimulate the field of rural culture, create tourism culture with Chinese characteristics, and make the countryside show its unique style and simple folk customs.","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":"89125819","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}
引用次数: 0
3D neuronal image segmentation of the mouse brain 小鼠大脑三维神经元图像分割
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2654099
Peng Wang, Mengya Chen
{"title":"3D neuronal image segmentation of the mouse brain","authors":"Peng Wang, Mengya Chen","doi":"10.1117/12.2654099","DOIUrl":"https://doi.org/10.1117/12.2654099","url":null,"abstract":"Neurons are highly morphologically complex, the whole brain image is huge, and strong noise, discontinuous signals, and mutual interference of signals often appear in neural images. The above problems have greatly increased the difficulty of neuron morphological calculation and analysis, so neuron morphology computation and analysis is widely regarded as one of the most challenging computational tasks in computational neuroscience. This paper introduces 3D-segmentation-net, an end-to-end learning method that can automatically segment 3D neuron images from sparse annotations. In automated segmentation validation experiments, we achieved an average IoU of 0.86. The network was trained from scratch and has not been optimized for this application. It is suitable for any mouse brain image segmentation task, and realizes automatic segmentation, tracking, fusion and real-time manual revision of a series of tracking schemes for massive neural images.","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":"87993734","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}
引用次数: 0
Backdoor attack based on feature in federated learning 基于联邦学习特征的后门攻击
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653697
Laicheng Cao, F. Li
{"title":"Backdoor attack based on feature in federated learning","authors":"Laicheng Cao, F. Li","doi":"10.1117/12.2653697","DOIUrl":"https://doi.org/10.1117/12.2653697","url":null,"abstract":"Federated learning enables participants to construct a better model without sharing their private local data with each other. In the context of the continuous introduction of laws and regulations aimed at protecting data and privacy security, such as the \"Data Security Law\", federated learning has been more valued and more widely used. However, federated learning is vulnerable to attacks, one is backdoor attack. Here, we propose a backdoor attack method based on feature, used the CIFAR-10 data set and the ResNet18 model to research in the two different scenarios which one used the data that malicious participant participate in normal training as a backdoor and another used the data that implanting during the training as a backdoor. Especially, when we used the data that malicious participant participate in normal training as a backdoor, the attack success rate is about 50% while the attack does not affect the training process.","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":"85410770","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}
引用次数: 0
Indoor positioning system based on UWB 基于超宽带的室内定位系统
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653679
Z. Zhou, Fangjin Sun, Yiliang Zhao
{"title":"Indoor positioning system based on UWB","authors":"Z. Zhou, Fangjin Sun, Yiliang Zhao","doi":"10.1117/12.2653679","DOIUrl":"https://doi.org/10.1117/12.2653679","url":null,"abstract":"At present, navigation and positioning system based on location service plays an extremely important role in all aspects of people's production and life. GPS or Beidou navigation system performs well in outdoor positioning, however, satellite signals are difficult to meet the requirements of higher accuracy of indoor positioning. This paper designs a set of simple, low cost, high-positioning- accuracy indoor positioning system based on UWB, using DS-TWR ranging algorithm. Experimental results show that the system can achieve high precision positioning effect, the error is less than 10cm. The hardware design is completed, and the upper computer software is developed to draw real-time positioning map.","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":"75883874","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}
引用次数: 4
Research on the application of digital technology in ink animation 数字技术在水墨动画中的应用研究
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2654132
Yuhong Shi
{"title":"Research on the application of digital technology in ink animation","authors":"Yuhong Shi","doi":"10.1117/12.2654132","DOIUrl":"https://doi.org/10.1117/12.2654132","url":null,"abstract":"Ink and wash animation is a key component of animation art in China. China's ink and wash animation once fell into a stagnant stage due to the limitations of its production technology. However, with the rapid development of digital technology and the significant improvement of its manufacturing level, the development of ink and wash animation has ushered in new opportunities. The organic integration of ink and wash animation technology and art endows ink and wash animation with new appeal and vitality. More and more ink and wash animation creators began to use digital technology to create, such as using Adobe's Flash and After Effects joint drawing tools, Illustrator, and Photoshop to simulate various painting techniques of ink and wash painting, which improved the painting efficiency and quality. Based on this, this paper introduces the main expression ways of ink-wash animation and the bottleneck of traditional ink-wash animation development technology and analyzes the innovative significance and value of digital ink-wash animation technology. Taking the ink-wash animation of \"Singing Goose\" as an example, this paper discusses how to apply digital technology in ink-wash animation production, in order to provide reference and help for Chinese ink-wash animation producers.","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":"73855397","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}
引用次数: 0
Research on family classification based on graph similarity 基于图相似度的族分类研究
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653827
Zemin Guo, Xiaojian Liu
{"title":"Research on family classification based on graph similarity","authors":"Zemin Guo, Xiaojian Liu","doi":"10.1117/12.2653827","DOIUrl":"https://doi.org/10.1117/12.2653827","url":null,"abstract":"With the continuous development of mobile devices, the rapid increase in the number of Android malware poses a huge threat to malware detection systems. By classifying malware samples into families, the features shared by malware in the same family can be utilized in the malware detection method, to achieve the effect of improving the detection rate of malware. In this paper, a family classification method based on graph similarity is proposed, which constructs a family matrix and a weight matrix for malicious families and performs family classification by calculating the similarity between the software and each family. Experiments show that the classification accuracy rate of this method for the Kmin family, Inconosys family, Ginimi family, and DroidKungFu family in the Drebin dataset is over 90%.","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":"86174159","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}
引用次数: 0
Application practice of 500 kV OPGW transmission line environmental monitoring technology 500kv OPGW输电线路环境监测技术的应用实践
JITeCS Journal of Information Technology and Computer Science Pub Date : 2022-12-08 DOI: 10.1117/12.2653798
Yan Li, Lishuai He, C. Xu, Bin Li, N. Fan, Lei Gao, Yunkun Huang
{"title":"Application practice of 500 kV OPGW transmission line environmental monitoring technology","authors":"Yan Li, Lishuai He, C. Xu, Bin Li, N. Fan, Lei Gao, Yunkun Huang","doi":"10.1117/12.2653798","DOIUrl":"https://doi.org/10.1117/12.2653798","url":null,"abstract":"This paper takes the optical fiber sensing technology as the research object. Firstly, according to the requirements of the sensing layer of the power Internet of things, starting from the multi risk monitoring of cable (overhead line), such as external breakage, fire, icing and galloping, an on-line monitoring system for transmission line environment is proposed, and the composition and deployment mode of the monitoring system are introduced. Secondly, through the research on the distribution of optical fiber temperature field and stress field, combined with big data and artificial intelligence, the monitoring of important environmental parameters of the line is realized. Finally, taking different monitoring scenarios as examples, this paper expounds the different monitoring functions of the transmission line Internet of things environmental monitoring system, which provides a useful reference for the transmission line environmental monitoring.","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":"78807140","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}
引用次数: 3
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