Journal of Discrete Mathematical Sciences & Cryptography最新文献

Embedded security framework for M2M communication using ULBC and Rubik’s Cube encryption algorithm 采用ULBC和魔方加密算法的M2M通信嵌入式安全框架

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1755

M. Salunke, P. Mahalle, G. Shinde

{"title":"Embedded security framework for M2M communication using ULBC and Rubik’s Cube encryption algorithm","authors":"M. Salunke, P. Mahalle, G. Shinde","doi":"10.47974/jdmsc-1755","DOIUrl":"https://doi.org/10.47974/jdmsc-1755","url":null,"abstract":"The potential of a variety of stockholders has increased as a direct result of the development of the Internet of Things and cloud computing. These individuals are now able to communicate and share data in a productive manner. This interaction with devices is regarded as extremely helpful and advantageous by a lot of users. Inadequate configuration of a network system makes it an easy target for potential security breaches. This is why it is important that a security framework is developed for the Internet of Things (IoT) and cloud computing models. This paper talks about the various frameworks that are used in these two technologies. It also explores the various security methods that are used to protect the devices that are connected to the cloud. Numerous studies have shown that there are various ways that people can manipulate the operations of machine-to-machine (M2M) in the digital world. While analyzing the methodology used in this technology, it is also important to keep in mind the security levels of the cloud and IoT ecosystem. The development of a secure connection between the various devices that are connected to the cloud is also important to ensure that the network is protected from security threats. This paper aims to provide a framework that will allow the integration of the Cloud and IoT and the Cloud Framework for Machine-to-Machine communication. The paper aims to develop a secure framework that will allow the integration of the Cloud and IoT with secure framework for Machine-to-Machine communication using (ultra-lightweight block cipher) ULBC and Rubik’s Cube encryption algorithm.","PeriodicalId":408043,"journal":{"name":"Journal of Discrete Mathematical Sciences & Cryptography","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126183770","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

Triple vertex of cycle graph for polyalphabetic encryption scheme 多字母加密方案中循环图的三重顶点

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1565

Manal Hatif Kadhim, R. K. Ajeena

引用次数: 0

A two stage hybrid intrusion detection using genetic algorithm in IoT networks 基于遗传算法的物联网网络两阶段混合入侵检测

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1737

V. Sharma, N. Yadav, Sundar Suhrith Adavi, D. S. D. Reddy, B. Gupta

{"title":"A two stage hybrid intrusion detection using genetic algorithm in IoT networks","authors":"V. Sharma, N. Yadav, Sundar Suhrith Adavi, D. S. D. Reddy, B. Gupta","doi":"10.47974/jdmsc-1737","DOIUrl":"https://doi.org/10.47974/jdmsc-1737","url":null,"abstract":"Today, almost 90% of the technology in usage is linked with IoT (Internet of Things). which brings the question, what is IoT? Internet of things is a system of co-related computers, electronic devices, and objects. IoT essentially controls almost every online service which we avail without human -to-human interaction. An IDS is a hardware or software system that automatically monitors, identifies, and alerts a computer or network against attacks and intrusions. The proposed hybrid model makes use of genetic algorithm with UNSW NB-15 dataset which contains multiple classes of attack to provide a huge variety of attacks which will help to simulate different kinds of attack which will help train the model better. We have used CNN and LSTM model for extracting features. By detecting the attacks quickly, we can identify potential intruders and limit the damage. Feature selection and classification have been performed using Generic algorithm. This hybrid model helps to check whether the alert is an attack or not, if yes what kind of attack is it. the proposed Hybrid model works better than a conventional intrusion detection system, we got 99.38% accuracy from this model.","PeriodicalId":408043,"journal":{"name":"Journal of Discrete Mathematical Sciences & Cryptography","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125429233","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

Impact of computer vision based secure image enrichment techniques on image classification model 基于计算机视觉的安全图像充实技术对图像分类模型的影响

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1777

A. S. Rao, K. Mahantesh

{"title":"Impact of computer vision based secure image enrichment techniques on image classification model","authors":"A. S. Rao, K. Mahantesh","doi":"10.47974/jdmsc-1777","DOIUrl":"https://doi.org/10.47974/jdmsc-1777","url":null,"abstract":"Growing advancement in Artificial Intelligence has led to developing systems which can think, analyze, recognize patterns and are capable enough to convert data into information has turned out to be a major prerequisite. An effort to provide enriched data with Computer Vision based Image Enrichment techniques and its impact on performance of Deep learning algorithms (VIRNet) is analyzed in the research. At first, various image enrichment technique like sharpening, denoising, color enhancement which makes the dominant features more visible which can be easily captured by the classification model. Later, popular computer vision techniques for image segmentation which differentiates the background and foreground area like Deeplabv3, Mask R-CNN and Region based segmentation methods are applied and its impact over Classification model is analyzed. The experimental study was conducted on popular image dataset Caltech 101 and Caltech-256, from the results it is clearly evident the image enrichment based on CLAHE outweighs the popular segmentation methods. Besides image segmentation and enrichment techniques, implementing an AES encryption in the process helps in protecting the sensitive data and ensures the data is kept private and secure. An image classification algorithm using deep learning equipped with AES encryption is implemented, which adds a layer of security to an image processing system.","PeriodicalId":408043,"journal":{"name":"Journal of Discrete Mathematical Sciences & Cryptography","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114825526","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

More secure on the symmetric encryption schemes based on triple vertex path graph 基于三顶点路径图的对称加密方案更安全

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1564

M. K. Shathir, Ghassan. E. Arif, R. K. Ajeena

引用次数: 1

Highly secure intelligent computer data detection of anomalies 高度安全的智能计算机异常数据检测

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1767

Upasana Gupta, Vaishali Singh, Dinesh Goyal

{"title":"Highly secure intelligent computer data detection of anomalies","authors":"Upasana Gupta, Vaishali Singh, Dinesh Goyal","doi":"10.47974/jdmsc-1767","DOIUrl":"https://doi.org/10.47974/jdmsc-1767","url":null,"abstract":"The latest technology is focusing on the detection of different attacks occurring in the cloud and IoT data centers and services. So, there is a need of providing high dimensional security for the data. The appraisal issue prompts the suggestion of a coordinated methodology for sifting the unusual data of interest and perspectives for seeing anticipated exceptions in the new youngster around subspaces of high-layered enormous information. High-layered immense information requires significant computational memory and brings a tremendous computational weight, no matter what the way that continuous figuring sources solid areas are. Thus, the fundamental examination objective of this assessment is to develop an adaptable system for inconsistency recognizing confirmation that arrangements with the issue of the scourge of dimensionality in goliath instructive combinations. The issue of irregularity range has different highlights, and how we depict irregularities, the sort of information, and anticipated surrender can have a critical effect on recognizable confirmation techniques. As a result of these contrasts, issue plans shift enormously, requiring the utilize of different shrewd frameworks to address them.","PeriodicalId":408043,"journal":{"name":"Journal of Discrete Mathematical Sciences & Cryptography","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128878348","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

Neural network based image object detection and tracking for security and surveillance 基于神经网络的安防监控图像目标检测与跟踪

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1780

Nishu Sethi, S. B. Bajaj

引用次数: 0

An IoT-based integrated health monitoring of bulk milk cooler 基于物联网的散装牛奶冷却器整体健康监测

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1764

P. Ajitha, Arun Mozhi Selvi Sundarapandi, M. Soniya, T. Tamilvizhi

引用次数: 0

Foreword of Special Issue on : Current Research Trends in Secure Computer Vision, IoT and Machine Learning 特刊前言:安全计算机视觉、物联网和机器学习的当前研究趋势

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-26-3-foreword

Dinesh Goyal

引用次数: 0

Computer vision, machine learning based monocular biomechanical and security analysis 计算机视觉，基于机器学习的单目生物力学和安全分析

Journal of Discrete Mathematical Sciences & Cryptography Pub Date : 1900-01-01 DOI: 10.47974/jdmsc-1741

Arun Kumar, Himanshu Sharma, S. Mathur, Dimpal Sharma, Girraj Khandelwal, G. Sharma

引用次数: 0

Journal of Discrete Mathematical Sciences &amp; Cryptography最新文献

Journal of Discrete Mathematical Sciences & Cryptography最新文献