Journal of Discrete Mathematical Sciences and Cryptography最新文献

{"title":"Double awareness mechanism based deep learning framework for image captioning","authors":"","doi":"10.47974/jdmsc-1728","DOIUrl":"https://doi.org/10.47974/jdmsc-1728","url":null,"abstract":"Understanding the qualities of an image and converting them into a phrase or sentence that makes sense is the process of image captioning. Neuroscience research has only recently made clear the connection between human vision and language formation. Although there have been many methods for captioning images, including content retrieval and template filling, the current trend is toward deep learning-based methods. Using an image encoder, feature vectors are created from an image through the deep learning process, and a language decoder converts these feature vectors into a string of words. Using encoder-decoder approach or simple attention based has not provided so much efficient results. In the proposed model, double awareness-based mechanism has been used. The primary goal of this study is to extract visual properties from the region of interest (RoI) of an image as well as text features using the glove embedding technique. Inception ResNet version of Convolutional neural network (CNN) is used as an encoder. As a decoder, a gated recurrent unit is employed. The proposed model is tested on Flickr8k dataset and it can be seen that the results achieved through double awareness mechanism are highly effective.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844171","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}

{"title":"Generalized k–step Jacobsthal numbers coding and decoding method ","authors":"Arun Kumar Yadav, Manju Pruthi","doi":"10.47974/jdmsc-1726","DOIUrl":"https://doi.org/10.47974/jdmsc-1726","url":null,"abstract":"In this article, we create a coding/decoding method utilizing the generalized k-step Jacobsthal numbers and the relation between the components of the code matrix and error detection and correction have been established for all value of k. The method’s accuracy is 93.33 percent for k = 2, the method’s accuracy is 99.80 percent for k = 3 and the method accuracy is 99.998 percent for n = 4. In general, the accuracy of the approach improves with each successively higher value of n. We give two examples of generalized k – step jacobsthal sequences via blocking algorithm and solve these illustrations using python.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844178","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}

{"title":"Elliptic curve matrices over group ring to improve elliptic curve–discrete logarithm cryptosystems","authors":"Qasim Mohsin Luhaib, Ruma Kareem K. Ajeena","doi":"10.47974/jdmsc-1616","DOIUrl":"https://doi.org/10.47974/jdmsc-1616","url":null,"abstract":"An elliptic curve matrix (ECM) is created randomly based on an elliptic curve group to modify the elliptic curve-discrete logarithm (EC-DL) cryptosystems, which are elliptic Diffie-Hellman key exchange (DHKE) and elliptic ElGamal public key cryptosystem (EEPKC), and to increase the security level in comparison with the original EC-DL schemes. In proposed schemes, the keys and ciphertext are computed using the ECMs. The security of trust schemes depended on the difficulty of solving the elliptic curve discrete logarithm problem (ECM-DLP). New experimental results on proposed schemes are discussed. The ECM-DL schemes consider new insights for more secure communications.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135845168","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}

{"title":"Image retrieval evaluation on smart phone using variant of histogram of gradient","authors":"Lalit B. Damahe, Nileshsingh V. Thakur, Sachin R. Jain, Shailesh D. Kamble","doi":"10.47974/jdmsc-1738","DOIUrl":"https://doi.org/10.47974/jdmsc-1738","url":null,"abstract":"The retrieval of similar type of data is performed by requesting the query, generally through personal computer. As the smart mobile devices are available at the general user, retrieval of visually similar data is now performed on these devices such as smart phones, PDA etc. A wireless medium is the key component of mobile devices and visually similar image retrieval with minimum latency is the typical issue.Hence the main objective of our proposed work is to develop the efficient mechanism for image retrieval on mobile devices. The image representation scheme V-HOG captures the useful information from the image with the help of gradient vector and the gradients are calculated by using various block size. The size of block, cell and bins are the main components which are varied and developed the V-HOG with feature values 1296, 1176, 672. The experimentation are conceded on the standard Holidays Dataset. The proposed V-HOG approach having a feature value 1296, 1176 and 672 perform better with existing HOG. In comparison with HOG, the precision and recall rate for V-HOG is improved by 27% to 90% and 7% to 32% respectively. The retrieval time is also reduced to 3% to 9%. The proposed V-HOG with 1176 feature perform well and having a good precision and recall rate.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135355371","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}

{"title":"Generalized (a, b)-reverse derivations in semi prime near rings","authors":"Abdul Rauf Khan, Rabia Naz, Muhammad Kashif Maqbool, Zaheer Ahmad, Kar Ping Shum","doi":"10.47974/jdmsc-1571","DOIUrl":"https://doi.org/10.47974/jdmsc-1571","url":null,"abstract":"In this paper, our aim is to study the right generalized (a, b)-reverse derivations on semi-prime near-ring and generalized dependent element of right generalized (a, b)-reverse derivation and right generalized b-reverse derivation on semi-prime near-ring. We generalize some useful results by using these notions.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844146","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}

{"title":"Image steganography using Fresnelet transformations, stated coefficients and a pre-processed message","authors":"Munthir Bahir Tuieb, Hind Jumaa Serteep, Doaa Muhsin Abed Ali","doi":"10.47974/jdmsc-1614","DOIUrl":"https://doi.org/10.47974/jdmsc-1614","url":null,"abstract":"The method of concealing confidential information inside an image is known as image steganography. In this work, the image steganography technique is developed. The framework is made up of three components: preprocessing of secret messages, selecting coefficients for the hiding process, and the hiring process. The secret message is organized as a two dimentional array, then processed via mathematical equations, which provide more security because the result is an encrypted message. The paper suggests a set of steps to hide the message efficiently. The experimental results show that the suggested method provides a high steganographic quality of the cover image and a high capacity for embedding information, which are two characteristics of a successful steganography technique.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"400 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844173","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}

{"title":"Special Issue on: Advances in Secure, Smart and Intelligent Technology based systems","authors":"Dinesh Goyal","doi":"10.47974/jdmsc-26-5-foreword","DOIUrl":"https://doi.org/10.47974/jdmsc-26-5-foreword","url":null,"abstract":"In today’s fast-paced technological landscape, the fields of Artificial Intelligence (AI), Smart Technologies, and Data Science are experiencing unprecedented growth. With the rise of Computer Vision, Internet of Things (IoT), and Machine Learning (ML), these domains are reshaping human life and society on a global scale. However, with such advancements, the importance of security in these areas has become more relevant than ever before. As these technologies rely heavily on data analytics, AI, and ML, new security requirements have emerged, urging researchers to focus on developing secure models and architectures.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135355904","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}

{"title":"A blockchain based private framework for facilitating digital forensics using IoT","authors":"Bhawna Suri, Shweta Taneja, Siddharth Sharma, Vishwajeet Verma, Divyanshi Parashar, Parth Sikka, Monika Arora, Sayed Sayeed Ahmad","doi":"10.47974/jdmsc-1733","DOIUrl":"https://doi.org/10.47974/jdmsc-1733","url":null,"abstract":"Introduction: Images play an essential role as evidence in any forensic analysis of a police investigation. They are a crucial part of the analysis and store important and nuanced information required to guide the analysis in the right direction and then finally lead the investigation to a just conclusion. However, these images are often subject to tampering. Malicious elements of society external or internal entities involved in conducting the investigation, try to tamper with, mend, and destroy pieces of evidence. This change can mislead the direction of the evidence and can benefit the accused. Research Problem: Through the scope of this paper, we will try to tackle this problem and find a solution for it. Methods: The approach proposed to tackle this problem is to implement a blockchain-based, distributed virtual private network (VPN) system. The network consists of devices spread across the internet, connected via a VPN. Only authorized devices are a part of the network and each device has a particular role and key. The image is captured from the IoT device at the crime scene, it is then encrypted using a Mixed Alphabet Cipher substitution algorithm that converts the RGB values to a string at the camera node and then transferred to the main server. It is further decrypted and again encrypted using the key of the main server. Upon encryption, the string is converted to a hash key which is then added to the blockchain. Results: The performance of the proposed network is tested on two different parameters- operating system and image size. It was found that the encryption time of images varies linearly with image size, operating system and image size. The different operating systems are Ubuntu and two variants of MAC OS. The images being tested vary from 200x200 px to 3840x2160px. The encryption and decryption time of different images is recorded, and it was found that the encryption time of images varies linearly with image size. Conclusion: The proposed solution was successfully developed and tested on different sets of images and operating systems. As our solution uses an in-house developed blockchain network, it has a better working cost than using an Ethereum-based blockchain.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135355940","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}

{"title":"Transfer learning based novel intelligent classification for Alzheimer’s Dementia using duplex convolutional neural network","authors":"Bali Devi, Sumit Srivastava, Vivek Kumar Verma, Gaurav Aggarwal","doi":"10.47974/jdmsc-1758","DOIUrl":"https://doi.org/10.47974/jdmsc-1758","url":null,"abstract":"Goal: This work focuses on neuroimaging studies, including MRI analysis via machine learning and deep learning, which has led to an increase in computer vision research and the early detection of neural disorders. Methods: An adaptive implementation of transfer learning (TL) with a top-level VGG16 architecture is set up with pretrained weights for large MRI images dataset. Convolutional neural networks (CNN) are a bespoke version of a multi-layer view. Through experimentation on the ADNI dataset, the algorithm was trained and tested in binary and multiclass classification using the MRI scanning of individuals. Results: The machine was trained on the CNN model of binary classification and the CNN model for multiclass classification and was trained using TL (using the VGG16 model) with CNN; 25 epochs of batch size of 32 were considered. To validate the contributions of this study, we demonstrated that the proposed model used for binary classification gave an accuracy of 96.89% and an F1 score of 96.90%, and for multiclass classification, we obtained an accuracy of 99.89% and an F1 score of 94.82%. Conclusion: The suggested approach is highly generic, as it is simple and parameter invariant, and therefore applicable to any MRI dataset.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135355951","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}

{"title":"A study of e-learning security system and its impact on educators","authors":"Tanya Garg, Ruchi Goyal, Dinesh Goyal","doi":"10.47974/jdmsc-1775","DOIUrl":"https://doi.org/10.47974/jdmsc-1775","url":null,"abstract":"E-Learning is the process of learning which includes interaction between teachers and learners, with comparison to traditional method of education. Plus, it is dependent on the web applications and internet technology. But, the environment of network is considered as a honey pot as it attracts many hackers; also, it is prone to many security risks like, malicious attacks, hackings, etc. Network security is one of the major concerns of the teachers, learners, instructors, etc., as they are not able to foresee risks and do not know the prevention as well. The aim of this study is to investigate the security issues associated with e-learning and effective countermeasures to prevent or mitigate these risks.","PeriodicalId":193977,"journal":{"name":"Journal of Discrete Mathematical Sciences and Cryptography","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135356593","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}