Journal of Computer Science and Cybernetics最新文献

PROVING THE SECURITY OF AES BLOCK CIPHER BASED ON MODIFIED MIXCOLUMN 证明基于修正混合列的 AES 区块密码的安全性

Journal of Computer Science and Cybernetics Pub Date : 2024-06-10 DOI: 10.15625/1813-9663/18058

Luong Tran Thi

{"title":"PROVING THE SECURITY OF AES BLOCK CIPHER BASED ON MODIFIED MIXCOLUMN","authors":"Luong Tran Thi","doi":"10.15625/1813-9663/18058","DOIUrl":"https://doi.org/10.15625/1813-9663/18058","url":null,"abstract":"Block ciphers in general, Substitution-Permutation Network (SPN) block ciphers in particular are cryptographic fields widely applied today. AES is an SPN block cipher used in many security applications. However, there are many strong attacks on block ciphers as linear attacks, differential attacks, and algebraic attacks which are challenging for cryptographers. Therefore, the research to improve the security of block ciphers in general and AES, in particular, is a topic of great interest today. Along with security, the issue of the execution cost of block ciphers is also crucial in practice. In this paper, we clarify the role of the MDS matrix in increasing the branch number of the diffusion layer of the block ciphers, thereby improving the security of the block ciphers. We propose a method improving the security of the AES block cipher by changing the Mixcolumn transformation of AES using execution-efficient MDS matrices of size 4, 8, or 16. We present a method to find a new diffusion matrix of modified AES block ciphers from which to evaluate the number of fixed points and coefficient of fixed points of the modified AES diffusion layers. In addition, we prove the branch number of the modified AES diffusion layers with MDS matrices of sizes 8, and 16. Then we also analyze the security, statistical standards and execution speed of modified AES block ciphers generated from those MDS matrices. The results show that our proposed method can significantly improve the security of the AES block cipher.","PeriodicalId":15444,"journal":{"name":"Journal of Computer Science and Cybernetics","volume":" 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141365079","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

AN IMPROVED INDEXING METHOD FOR QUERYING BIG XML FILES 一种用于查询大型 XML 文件的改进索引方法

Journal of Computer Science and Cybernetics Pub Date : 2023-12-25 DOI: 10.15625/1813-9663/19018

Dinh Duc Luong, Vuong Quang Phuong, Hoang Do Thanh Tung

{"title":"AN IMPROVED INDEXING METHOD FOR QUERYING BIG XML FILES","authors":"Dinh Duc Luong, Vuong Quang Phuong, Hoang Do Thanh Tung","doi":"10.15625/1813-9663/19018","DOIUrl":"https://doi.org/10.15625/1813-9663/19018","url":null,"abstract":"The exponential growth of bioinformatics in the healthcare domain has revolutionized our understanding of DNA, proteins, and other biomolecular entities. This remarkable progress has generated an overwhelming volume of data, necessitating big data technologies for efficient storage and indexing. While big data technologies like Hadoop offer substantial support for big XML file storage, the challenges of indexing data sizes and XPath query performance persist. To enhance the efficiency of XPath queries and address the data size problem, a novel approach that is derived from the spatial indexing method of the R-tre family. The proposed method is to modify the structure of leaf nodes in the indexing tree to preserve XML-sibling connections. Then, new algorithms for constructing the new tree structure and processing sibling queries better are introduced. Experimental results demonstrate the superior efficiency of sibling XPath queries with reduced data sizes for indexing, while other XPath queries exhibit notable performance improvements. This research contributes to the development of more effective indexing methods for managing and querying large XML datasets in bioinformatics applications, ultimately advancing biomedical research and healthcare initiatives.","PeriodicalId":15444,"journal":{"name":"Journal of Computer Science and Cybernetics","volume":"1 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139157596","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

OHYEAH AT VLSP2022-EVJVQA CHALLENGE: A JOINTLY LANGUAGE-IMAGE MODEL FOR MULTILINGUAL VISUAL QUESTION ANSWERING ohyeah at vlsp2022-evjvqa challenge: a jointly language-image model for multilingual visual question answering（用于多语言视觉问题解答的语言-图像联合模型）...

Journal of Computer Science and Cybernetics Pub Date : 2023-12-25 DOI: 10.15625/1813-9663/18122

Luan Ngo Dinh, Hiếu Lê Ngọc, Long Quoc Phan

引用次数: 0

A NOVEL ALGORITHM FOR FINDING ALL REDUCTS IN THE INCOMPLETE DECISION TABLE 寻找不完整判定表中所有还原的新算法

Journal of Computer Science and Cybernetics Pub Date : 2023-11-21 DOI: 10.15625/1813-9663/18680

Pham Viet Anh, Vu Duc Thi, Nguyen Ngoc Cuong

引用次数: 0

THE VNPT-IT EMOTION TRANSPLANTATION APPROACH FOR VLSP 2022 针对 VLSP 2022 的 VNPT-IT 情感移植方法

Journal of Computer Science and Cybernetics Pub Date : 2023-11-21 DOI: 10.15625/1813-9663/18236

Van Thang Nguyen, Thanh Long Luong, Huan Vu

引用次数: 0

TAEKWONDO POSE ESTIMATION WITH DEEP LEARNING ARCHITECTURES ON ONE-DIMENSIONAL AND TWO-DIMENSIONAL DATA 在一维和二维数据上利用深度学习架构进行跆拳道姿势估计

Journal of Computer Science and Cybernetics Pub Date : 2023-11-21 DOI: 10.15625/1813-9663/18043

Dat Tien Nguyen, Chau Ngoc Ha, Ha Thanh Thi Hoang, Truong Nhat Nguyen, Tuyet Ngoc Huynh, Hai Thanh Nguyen

{"title":"TAEKWONDO POSE ESTIMATION WITH DEEP LEARNING ARCHITECTURES ON ONE-DIMENSIONAL AND TWO-DIMENSIONAL DATA","authors":"Dat Tien Nguyen, Chau Ngoc Ha, Ha Thanh Thi Hoang, Truong Nhat Nguyen, Tuyet Ngoc Huynh, Hai Thanh Nguyen","doi":"10.15625/1813-9663/18043","DOIUrl":"https://doi.org/10.15625/1813-9663/18043","url":null,"abstract":"Practicing sports is an activity that helps people maintain and improve their health, enhance memory and concentration, reduce anxiety and stress, and train teamwork and leadership ability. With the development of science and technology, artificial intelligence in sports has become increasingly popular with the public and brings many benefits. In particular, many applications help people track and evaluate athletes' achievements in competitions. This study extracts images from Taekwondo videos and generates skeleton data from frames using the Fast Forward Moving Picture Experts Group (FFMPEG) technique using MoveNet. After that, we use deep learning architectures such as Long Short-Term Memory Networks, Convolutional Long Short-Term Memory, and Long-term Recurrent Convolutional Networks to perform the poses classification tasks in Taegeuk in Jang lessons. This work presents two approaches. The first approach uses a sequence skeleton extracted from the image by Movenet. Second, we use sequence images to train using video classification architecture. Finally, we recognize poses in sports lessons using skeleton data to remove noise in the image, such as background and extraneous objects behind the exerciser. As a result, our proposed method has achieved promising performance in pose classification tasks in an introductory Taekwondo lesson.","PeriodicalId":15444,"journal":{"name":"Journal of Computer Science and Cybernetics","volume":"59 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139253167","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

A PLANT RECOGNITION APPROACH USING HIGH RESOLUTION NETWORK 一种基于高分辨率网络的植物识别方法

Journal of Computer Science and Cybernetics Pub Date : 2023-10-06 DOI: 10.15625/1813-9663/18144

Dang Ngan Ha, Hieu Trung Huynh

引用次数: 0

EVJVQA CHALLENGE: MULTILINGUAL VISUAL QUESTION ANSWERING Evjvqa挑战:多语言视觉问答

Journal of Computer Science and Cybernetics Pub Date : 2023-09-26 DOI: 10.15625/1813-9663/18157

Nguyen, Ngan Luu-Thuy, Nguyen, Nghia Hieu, Vo, Duong T. D, Tran, Khanh Quoc, Van Nguyen, Kiet

{"title":"EVJVQA CHALLENGE: MULTILINGUAL VISUAL QUESTION ANSWERING","authors":"Nguyen, Ngan Luu-Thuy, Nguyen, Nghia Hieu, Vo, Duong T. D, Tran, Khanh Quoc, Van Nguyen, Kiet","doi":"10.15625/1813-9663/18157","DOIUrl":"https://doi.org/10.15625/1813-9663/18157","url":null,"abstract":"Visual Question Answering (VQA) is a challenging task of natural language processing (NLP) and computer vision (CV), attracting significant attention from researchers. English is a resource-rich language that has witnessed various developments in datasets and models for visual question answering. Visual question answering in other languages also would be developed for resources and models. In addition, there is no multilingual dataset targeting the visual content of a particular country with its own objects and cultural characteristics. To address the weakness, we provide the research community with a benchmark dataset named EVJVQA, including 33,000+ pairs of question-answer over three languages: Vietnamese, English, and Japanese, on approximately 5,000 images taken from Vietnam for evaluating multilingual VQA systems or models. EVJVQA is used as a benchmark dataset for the challenge of multilingual visual question answering at the 9th Workshop on Vietnamese Language and Speech Processing (VLSP 2022). This task attracted 62 participant teams from various universities and organizations. In this article, we present details of the organization of the challenge, an overview of the methods employed by shared-task participants, and the results. The highest performances are 0.4392 in F1-score and 0.4009 in BLUE on the private test set. The multilingual QA systems proposed by the top 2 teams use ViT for the pre-trained vision model and mT5 for the pre-trained language model, a powerful pre-trained language model based on the transformer architecture. EVJVQA is a challenging dataset that motivates NLP and CV researchers to further explore the multilingual models or systems for visual question answering systems.","PeriodicalId":15444,"journal":{"name":"Journal of Computer Science and Cybernetics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134903242","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

DATA AUGMENTATION ANALYSIS OF VEHICLE DETECTION IN AERIAL IMAGES 航拍图像中车辆检测的数据增强分析

Journal of Computer Science and Cybernetics Pub Date : 2023-09-22 DOI: 10.15625/1813-9663/18259

Khang Nguyen

引用次数: 0

A NOVEL APPROACH TO MODELLING A DIAGNOSIS AND TREATMENT OF TRADITIONAL VIETNAMESE MEDICINE 越南传统医学诊断和治疗建模的新方法

Journal of Computer Science and Cybernetics Pub Date : 2023-09-22 DOI: 10.15625/1813-9663/18015

Truong Thi Hong Thuy, Nguyen Hoang Phuong

{"title":"A NOVEL APPROACH TO MODELLING A DIAGNOSIS AND TREATMENT OF TRADITIONAL VIETNAMESE MEDICINE","authors":"Truong Thi Hong Thuy, Nguyen Hoang Phuong","doi":"10.15625/1813-9663/18015","DOIUrl":"https://doi.org/10.15625/1813-9663/18015","url":null,"abstract":"Traditional Vietnamese Medicine (TVM) is based on the experiences of thousands of years of Vietnamese people in the struggle against diseases; therefore, TVM is very important in the medical system of Vietnam. In this paper, we propose a novel model of an expert system for diagnosing disease syndromes and treating traditional Vietnamese medicine. In this model, the knowledge base consists of IF-THEN rules, in which the antecedent of a rule is an elementary conjunction of propositions and negated propositions. The inference mechanism for the diagnosis of disease syndromes and treatment of traditional Vietnamese medicine applies Abelian group operations. A comparison of the inference of our model with the fuzzy max-min inferences shows that our model can have very similar rules whose contributions sum up to high weight. On the other hand, in our model, a rule with a negative weight may diminish an effect of a rule with a good weight. This feature is absent in the systems with fuzzy max-min inferences. We have built rule patterns for the diagnosis of about 50 disease syndromes and their treatment by Herbs and Acupuncture with the cooperation of practitioners of Oriental Traditional Medicine in Vietnam. Some examples of databases and the rules for disease syndrome differentiation and treatment by herbal medicine and Acupuncture are shown. Finally, some conclusions and future works are given.","PeriodicalId":15444,"journal":{"name":"Journal of Computer Science and Cybernetics","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136100798","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