2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)最新文献

Generation of Pseudo Random Sequences based on Chaotic Cubic Map and Cyclic Elliptic Curves over GF (28) for Cryptographic Applications 基于GF(28)上混沌三次映射和循环椭圆曲线的伪随机序列的生成

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350495

S. Sheela, S. Sathyanarayana

{"title":"Generation of Pseudo Random Sequences based on Chaotic Cubic Map and Cyclic Elliptic Curves over GF (28) for Cryptographic Applications","authors":"S. Sheela, S. Sathyanarayana","doi":"10.1109/MPCIT51588.2020.9350495","DOIUrl":"https://doi.org/10.1109/MPCIT51588.2020.9350495","url":null,"abstract":"Cyclic elliptic curves (CEC) and chaotic sequences are used for cryptographic application from many decades. In this paper, authors propose a hybrid model to generate pseudo random key sequences for symmetric ciphers. Hybrid model is developed using CEC points over GF (28) and a one-dimensional cubic map. In the proposed system first, binary chaotic sequence and CEC points are given to AES SBOX to get two random sequences separately. Byte wise parity is computed for both the sequences. Based on the parity the sequences are either left or right circular shifted by a byte and two sequences are combined using the XOR operation to get the random binary sequence. The randomness of the generated sequences is analysed using various randomness test suites like NIST SP 800-22 Rev.1a and Correlation. It has been observed that all the sequences pass the randomness tests. These sequences are used to encrypt an image using additive stream cipher algorithm. The security analysis of the cipher image is conducted. The results obtained for the proposed system indicates that it is secure against cryptographic attacks.","PeriodicalId":136514,"journal":{"name":"2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116759128","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

Key Management Using Elliptic Curve Diffie Hellman Curve 25519 利用椭圆曲线Diffie Hellman曲线进行密钥管理

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350454

R. Naik, S. Sathyanarayana, T. Sowmya

{"title":"Key Management Using Elliptic Curve Diffie Hellman Curve 25519","authors":"R. Naik, S. Sathyanarayana, T. Sowmya","doi":"10.1109/MPCIT51588.2020.9350454","DOIUrl":"https://doi.org/10.1109/MPCIT51588.2020.9350454","url":null,"abstract":"Key management shows an important role in the information transmissions. This paper analyzes the more improved and cost-effective key management scheme with respect to transmission overhead, computation cost. A key management policy is effectually employed for the purpose of generating a distinctive convention key for ample members to promise the security of their prospect communications, and this agreement can be allied in cloud computing for the purpose of assisting protected and skilled data distribution. The Key exchange protocols provides the two or more members to decide on a shared secret key and later be able to used for encrypting a long message. The complexity of Discrete Logarithm Problem (DLP) as basic problem considered in Diffie-Hellman Key Exchange Protocol. The Elliptic curve Diffie-Helman (ECDH) is considered as an expansion to the standard Diffie-Hellman. The ECDH function is ideal for a wide range of cryptographic functions. Key management based on ECDH provides much security on key meanwhile having more amount of storage cost and execution time involving in this. The ECDH Curve 25519 makes much faster in execution and lesser storage cost due its structure which uses much higher prime group of the order 2252.","PeriodicalId":136514,"journal":{"name":"2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128300546","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

Analyzing Big Data Originated from Data Communication Networks using K-Means Algorithm to Understand the Nature of Incoming Malicious Connections 利用K-Means算法分析数据通信网络产生的大数据，了解传入恶意连接的性质

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350510

L. B. Shyamasundar, V. A. Kumar, Jhansi Rani Prathuri

引用次数: 0

Simulation of Maximum Efficiency Point Tracking in Wireless Power Transfer Systems using Pulse Density Modulation 脉冲密度调制无线电力传输系统中最大效率点跟踪的仿真

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350475

Urmila Mathure, R. Ramkrishna

{"title":"Simulation of Maximum Efficiency Point Tracking in Wireless Power Transfer Systems using Pulse Density Modulation","authors":"Urmila Mathure, R. Ramkrishna","doi":"10.1109/MPCIT51588.2020.9350475","DOIUrl":"https://doi.org/10.1109/MPCIT51588.2020.9350475","url":null,"abstract":"This paper presents a method of control known as maximum efficiency point tracking (MEPT). This method of control is used for wireless power transfer (WPT) systems to provide maximum value of efficiency against load variations and coupling with achieving power demands of the system. In traditional MEPT systems, on both transmitting and receiving sides dc/dc converters are used in order to achieve maximum efficiency and for the regulation of output voltage. But this arrangement increases the complexity of network with increasing power loss. Some implementations lead to new problems like hard switching, large dc voltage ripples and low average efficiency. An implementation of MEPT based on pulse density modulation is explained in this paper which removes all the drawbacks in existing implementation. A PDM circuit is used in both transmitting and receiving side to achieve maximum efficiency. A simulation circuit is built in matlab in this paper to get maximum efficiency. By varying load resistances and pulse densities in the matlab Simulink circuit an efficiency and output voltage is checked By comparing the results of existing MEPT implementation with this simulation circuit of WPT using PDM it achieved efficiency upto 83% for various load resistances and pulse densities.","PeriodicalId":136514,"journal":{"name":"2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124586534","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

Microscopic Blood Smear RBC Classification using PCA and SVM based Machine Learning 基于PCA和SVM的显微血液涂片红细胞分类

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350389

Prashanth Kannadaguli

{"title":"Microscopic Blood Smear RBC Classification using PCA and SVM based Machine Learning","authors":"Prashanth Kannadaguli","doi":"10.1109/MPCIT51588.2020.9350389","DOIUrl":"https://doi.org/10.1109/MPCIT51588.2020.9350389","url":null,"abstract":"The therapeutic analysis f microscopic blood smear begins with recognizing blood cells f various categories as well as estimating cell count in blood sample. The distinctive blood cell grading and counting furnish priceless knowledge to the pathologist about sundry infections. This exercise can be easily concluded if the shapes f blood cells are pinpointed first and using the shapes, we classify the blood cells. In this research work we build and test an automatic microscopic blood smear red blood cell (RBC) classification by using Principal Component Analysis (PCA) and Support Vector Machine (SVM) based machine learning. We train and test the statistical data models based n probabilistic pattern recognition to classify the blood smear RBC into Normal Cells, Echinocytes, Elliptocytes and Sickle cells. The H-minimum Transform (HmT) and Watershed Transform (WT) are used in pre-processing f images to increase the accuracy if segmentation shape extraction f the blood cells. Then the Bag f Features (BoF) created considering the 500 strongest features f each type f blood cell after K-Means clustering. Training takes place through Image Category Classifier (ICC) whose performance measured by using Mean Average Precision (mAP) justifies that SVM based classifiers provide audacious results.","PeriodicalId":136514,"journal":{"name":"2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124008964","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: 2

Smart Parking System (S-Park) – A Novel Application to Provide Real-Time Parking Solution 智能停车系统(S-Park)——一种提供实时停车解决方案的新应用

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350429

Abhijeet Anand, Abhinav Kumar, A. Rao, Anupam Ankesh, Ankur Raj

{"title":"Smart Parking System (S-Park) – A Novel Application to Provide Real-Time Parking Solution","authors":"Abhijeet Anand, Abhinav Kumar, A. Rao, Anupam Ankesh, Ankur Raj","doi":"10.1109/MPCIT51588.2020.9350429","DOIUrl":"https://doi.org/10.1109/MPCIT51588.2020.9350429","url":null,"abstract":"Due to daily acceleration in the quantity of vehicles out and about, traffic issues will undoubtedly exist. The current transportation framework and vehicle parking space are unable to meet with the quantity of vehicles. Looking for a parking space in central city zones, particularly during top hours, is very strenuous for drivers. To avoid such a situation the project, Smart Parking System (S-Park) is envisioned. In this project, a real time system is developed and implemented, that allows the drivers to successfully locate and restrain the unoccupied parking areas remotely through website and Android App. The system developed, also allows the driver to navigate to their respective parking spot using Google maps. The driver needs to first register himself to avail the facility. The details of driver and vehicle are stored in database. This helps in tracking the in-out time and other details of every individual driver. S-Park provides hassle free operations in and around parking location. It also helps in attenuating the traffic congestion at a very rich scale.","PeriodicalId":136514,"journal":{"name":"2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114001882","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: 5

A Novel Fuzzy Logic Based Controller for Measuring the Effectiveness of Training for Placement 一种新的基于模糊逻辑的定位训练有效性测量控制器

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350470

S. S. Navalgund

引用次数: 0

MPCIT 2020 Table of Contents MPCIT 2020目录

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/mpcit51588.2020.9350424

引用次数: 0

Smart Safety and Security Solution for Women using kNN Algorithm and IoT 使用kNN算法和物联网的女性智能安全和安保解决方案

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350431

B. Yaswanth, R. Darshan, H. Pavan, D. Srinivasa, B. T. V. Murthy

引用次数: 3

Scientific Discovery and Rigor with ML 科学发现和ML的严谨性

2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) Pub Date : 2020-12-11 DOI: 10.1109/MPCIT51588.2020.9350455

Abdul-Gafoor Mohamed, P. Mahanta

{"title":"Scientific Discovery and Rigor with ML","authors":"Abdul-Gafoor Mohamed, P. Mahanta","doi":"10.1109/MPCIT51588.2020.9350455","DOIUrl":"https://doi.org/10.1109/MPCIT51588.2020.9350455","url":null,"abstract":"The evolution of Data Management Scenarios augmented by scientific discovery and rigor is apparent in the industry, judging by the sheer focus on it by analysts and others over the past couple of years. Machine Learning helps immensely playing its part in simplifying enterprise data landscapes, contributing to many aspects of Data Management. We see value in focusing on the Data Discovery and Data Quality aspects in this context, as enterprises these days have complex landscapes, with the average enterprise using more than 5 Cloud storages in addition to their on-prem data sources.A greater affinity for enterprise grade Machine Learning has created a significant pull for system design. This leads platforms towards capabilities like standard APIs for scaled-database queries and integration scenarios. This paper explores the integration of Machine Learning tools and customized libraries with any Cloud Platform for enhancing the stakeholders’ experience with Analytics. As far as concepts are concerned, we propose a hypothesis for scaling an existent platform to a community-based approach, which helps enable sharing of experimental iterations, ideally translating into industry specific solutions that should stay extremely reusable. The intent is to offer a data model flexible enough to handle diverse data scenarios, evaluating confidence scores for each of these. It should enable reproducible shared experiments with consistent evaluated scores, thereby easing the integration process through automated guidance. This paper will touch upon the good practices and architectural recommendations that need to be considered for general Machine Learning applications.","PeriodicalId":136514,"journal":{"name":"2020 Third International Conference on Multimedia Processing, Communication & Information Technology (MPCIT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116100424","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