Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877443
R. Gedela, H. Nemade, R. Bhattacharjee
Orthogonal frequency coding is often used for surface acoustic wave (SAW) based systems. This paper presents the theoretical analysis of orthogonal frequency coding technique used with on-off keying in communications systems. The interference encountered in multiuser environment is formulated and a code selection criterion for minimizing the interference is proposed. The analytical expression for bit error rate (BER) is derived for an additive white Gaussian noise channel considering multiple access interference. BER performance for different lengths of orthogonal frequency code (OFC) has been studied through simulations and the results are in good agreement with the theory.
{"title":"BER analysis of communication systems employing orthogonal frequency coding in surface acoustic wave (SAW) correlators","authors":"R. Gedela, H. Nemade, R. Bhattacharjee","doi":"10.1109/NGCT.2016.7877443","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877443","url":null,"abstract":"Orthogonal frequency coding is often used for surface acoustic wave (SAW) based systems. This paper presents the theoretical analysis of orthogonal frequency coding technique used with on-off keying in communications systems. The interference encountered in multiuser environment is formulated and a code selection criterion for minimizing the interference is proposed. The analytical expression for bit error rate (BER) is derived for an additive white Gaussian noise channel considering multiple access interference. BER performance for different lengths of orthogonal frequency code (OFC) has been studied through simulations and the results are in good agreement with the theory.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121288488","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877383
D. Majumder, M. Das
Leukemia is routinely diagnosed by light microscopic images. However, pathologists' criteria for a disease diagnosis from images are mostly qualitative and empirical in nature. Reports suggest that though leukemia is a cancer of leukocytes; however, there are morphological alterations of red blood cells (RBCs) under the condition of leukemia. This has been evident by in observation of ultra-structural images of RBCs. Recently computational analysis of those ultra-structural images helps in revealing the quantitative understanding of the changes under the condition of leukemia. Light microscopic image analysis may further propel this approach towards clinical feasibility. Hence, development of computational analytical method for light microscopic images would the most suited way for direct application in clinics as the dragged quantitative information may help in an understanding of grading of the disease. Moreover wider application of the method may provide a hint towards the pre-leukemic state and the residual disease in future.
{"title":"An analytical approach for leukemia diagnosis from light microscopic images of Rbcs (Computational approach for leukemia diagnosis)","authors":"D. Majumder, M. Das","doi":"10.1109/NGCT.2016.7877383","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877383","url":null,"abstract":"Leukemia is routinely diagnosed by light microscopic images. However, pathologists' criteria for a disease diagnosis from images are mostly qualitative and empirical in nature. Reports suggest that though leukemia is a cancer of leukocytes; however, there are morphological alterations of red blood cells (RBCs) under the condition of leukemia. This has been evident by in observation of ultra-structural images of RBCs. Recently computational analysis of those ultra-structural images helps in revealing the quantitative understanding of the changes under the condition of leukemia. Light microscopic image analysis may further propel this approach towards clinical feasibility. Hence, development of computational analytical method for light microscopic images would the most suited way for direct application in clinics as the dragged quantitative information may help in an understanding of grading of the disease. Moreover wider application of the method may provide a hint towards the pre-leukemic state and the residual disease in future.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122791110","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877526
A. Sarkar, S. Shome, Fareha Hareem, P. Das
In the present day scenario security of people is a big issue. Moreover natural disasters occur very often nowadays. In this respect there should be some mechanism by which any person falling into a crisis, can inform about the emergency situation to other person(s) of her choice to seek help. This paper presents a system which deals with the issue of emergency and crisis situations. The system enables a fully automated location tracking mechanism by which a user's present location can be tracked. The system allows dynamic switching between different location tracking strategies of the Android platform depending upon the prevailing conditions. The tracked locations are periodically updated to server or sent to emergency contact numbers as and when required. We present an algorithm to minimize the energy consumption of the system for location tracking and show significant reduction of power consumption by as much as 93.4% (approx).
{"title":"SHAKTI — Secured and highly adaptive knowledge base tracking information system using android platform","authors":"A. Sarkar, S. Shome, Fareha Hareem, P. Das","doi":"10.1109/NGCT.2016.7877526","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877526","url":null,"abstract":"In the present day scenario security of people is a big issue. Moreover natural disasters occur very often nowadays. In this respect there should be some mechanism by which any person falling into a crisis, can inform about the emergency situation to other person(s) of her choice to seek help. This paper presents a system which deals with the issue of emergency and crisis situations. The system enables a fully automated location tracking mechanism by which a user's present location can be tracked. The system allows dynamic switching between different location tracking strategies of the Android platform depending upon the prevailing conditions. The tracked locations are periodically updated to server or sent to emergency contact numbers as and when required. We present an algorithm to minimize the energy consumption of the system for location tracking and show significant reduction of power consumption by as much as 93.4% (approx).","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123424368","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877434
Chandrakala Arya, S. Dwivedi
The incentive for this work originates from the need of retrieving useful web news pages from the Indian news websites corpus. News web pages contrast from other web pages; it is mainly vital to recognize web news accurately for precise classification. We will likely locate a simple yet efficient technique to mine news articles from web corpus. To accomplish this task, the automatic recognition method has been recommended for news web page classification that uses classification rules based on a combination of content, structure and uniform resource locator (URL) attributes. We gathered news web documents from 10 different news websites. We use Naïve Bayes algorithm to distinguish news articles from non-news articles examples advertisements, not related links.
{"title":"News web page classification using url content and structure attributes","authors":"Chandrakala Arya, S. Dwivedi","doi":"10.1109/NGCT.2016.7877434","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877434","url":null,"abstract":"The incentive for this work originates from the need of retrieving useful web news pages from the Indian news websites corpus. News web pages contrast from other web pages; it is mainly vital to recognize web news accurately for precise classification. We will likely locate a simple yet efficient technique to mine news articles from web corpus. To accomplish this task, the automatic recognition method has been recommended for news web page classification that uses classification rules based on a combination of content, structure and uniform resource locator (URL) attributes. We gathered news web documents from 10 different news websites. We use Naïve Bayes algorithm to distinguish news articles from non-news articles examples advertisements, not related links.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115701015","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877486
Kanwarpreet Kaur, Amardeep Kaur
Cloud computing allows hosting of multiple services on different datacenters where resources are allocated to users on demand. It uses virtualized environment for functioning services, because without virtualization computing is inefficient and not flexible. Load balancing assure that all the processors in the system does generally the equal load of work at any instant of time. The various traditional load balancing algorithms not performed well and they does not consider SLA parameters while selecting virtual machine for migration. Some another issues are also involved in migration process like number of migrations, consumption of cost, time and memory. So there is need to develop new approach for load balancing in data centers using VM algorithm that overcome the problems in traditional approaches and improve their performance. So the hybrid approach using various methods like ACO, Min-Max Ant System as well as GA algorithm is proposed in this paper. This paper overcome the problem of stagnation in ACO-VMM technique. The results are simulated in cloud sim environment.
{"title":"A hybrid approach of load balancing through VMs using ACO, MinMax and genetic algorithm","authors":"Kanwarpreet Kaur, Amardeep Kaur","doi":"10.1109/NGCT.2016.7877486","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877486","url":null,"abstract":"Cloud computing allows hosting of multiple services on different datacenters where resources are allocated to users on demand. It uses virtualized environment for functioning services, because without virtualization computing is inefficient and not flexible. Load balancing assure that all the processors in the system does generally the equal load of work at any instant of time. The various traditional load balancing algorithms not performed well and they does not consider SLA parameters while selecting virtual machine for migration. Some another issues are also involved in migration process like number of migrations, consumption of cost, time and memory. So there is need to develop new approach for load balancing in data centers using VM algorithm that overcome the problems in traditional approaches and improve their performance. So the hybrid approach using various methods like ACO, Min-Max Ant System as well as GA algorithm is proposed in this paper. This paper overcome the problem of stagnation in ACO-VMM technique. The results are simulated in cloud sim environment.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"146 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131577310","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877478
Shobha Aswal, N. J. Ahuja, Ritika
Data classification in medical field is distinct from that in other fields, because the medical data are heterogeneous, skewed and complex in nature and medical data classification involves multi class classification. In this paper we present the experimental analysis of well-known traditional classification algorithms on bio-medical datasets in order to observe their performance. This experimental analysis will provide deeper insight in designing the efficient classification algorithm for bio medical data.
{"title":"Experimental analysis of traditional classification algorithms on bio medical dtatasets","authors":"Shobha Aswal, N. J. Ahuja, Ritika","doi":"10.1109/NGCT.2016.7877478","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877478","url":null,"abstract":"Data classification in medical field is distinct from that in other fields, because the medical data are heterogeneous, skewed and complex in nature and medical data classification involves multi class classification. In this paper we present the experimental analysis of well-known traditional classification algorithms on bio-medical datasets in order to observe their performance. This experimental analysis will provide deeper insight in designing the efficient classification algorithm for bio medical data.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130925136","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877409
Rishabh Gupta, Niharika Singh, Bhagwant Singh
Air pollution has become health hazard. With the growth of industries, the air quality has now become an issue both for the environment as well to the society over the last few years. Due to the rising degradation of air quality, the need for control has risen. Artificial neural network have been applied to many environmental engineering problems and have demonstrated good degree of success in processing and interpretation of results. The purpose of this study is to develop an Artificial Neural Network based Geographical Information System (GIS) for the visualization of air quality hot spots. In this study, a mapping method is developed using feed-forward neural network algorithm. The mapping will be done by hit and trial approach which will help to define the parameters to be taken. Parameters such as temperature, relative humidity, precipitation and air velocity are taken as input for the neural network model which leads us to develop an output in terms of Oxides of Nitrogen (NOX) and Oxides of Sulphur (SOX). The performance of the developed model is assessed through a non-linear sigmoid function. From the constructed model, the best performance based on hit and trial approach will be considered and then will be displayed in the GIS referenced map.
空气污染已成为健康危害。随着工业的发展，在过去的几年里，空气质量已经成为环境和社会的一个问题。由于空气质量日益恶化，控制空气质量的需求也增加了。人工神经网络已应用于许多环境工程问题，并在结果的处理和解释方面取得了良好的成功。本研究的目的是开发一个基于人工神经网络的地理信息系统(GIS)，用于空气质量热点的可视化。本文提出了一种利用前馈神经网络算法的映射方法。映射将采用hit and trial方法，这将有助于确定要采取的参数。将温度、相对湿度、降水和风速等参数作为神经网络模型的输入，使我们开发出以氮氧化物(NOX)和硫氧化物(SOX)为形式的输出。该模型的性能通过非线性s型函数进行评估。从构建的模型中，考虑基于命中和试验方法的最佳性能，然后将其显示在GIS参考图中。
{"title":"Neural network based GIS application for air quality visualization","authors":"Rishabh Gupta, Niharika Singh, Bhagwant Singh","doi":"10.1109/NGCT.2016.7877409","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877409","url":null,"abstract":"Air pollution has become health hazard. With the growth of industries, the air quality has now become an issue both for the environment as well to the society over the last few years. Due to the rising degradation of air quality, the need for control has risen. Artificial neural network have been applied to many environmental engineering problems and have demonstrated good degree of success in processing and interpretation of results. The purpose of this study is to develop an Artificial Neural Network based Geographical Information System (GIS) for the visualization of air quality hot spots. In this study, a mapping method is developed using feed-forward neural network algorithm. The mapping will be done by hit and trial approach which will help to define the parameters to be taken. Parameters such as temperature, relative humidity, precipitation and air velocity are taken as input for the neural network model which leads us to develop an output in terms of Oxides of Nitrogen (NOX) and Oxides of Sulphur (SOX). The performance of the developed model is assessed through a non-linear sigmoid function. From the constructed model, the best performance based on hit and trial approach will be considered and then will be displayed in the GIS referenced map.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127547710","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877387
Abhirup Khanna, Ravi Tomar
Internet of Things aims at integrating networked information systems to real world entities. It connects objects such as smart phones, sensors, LED(Light Emitting Diodes) displays and even clothes through the internet allowing them to interact and exchange information among themselves. In today's times IoT has found its application in practically every walk of life and inventory management is no exception. At present, inventory management is becoming increasingly complex, where there is an exponential rise in the diversity and number of both products and customers. The biggest problem faced by store owners is to optimize the experience of inventory management along with increased sales and reduced operational costs. With such enormous product lines it becomes extremely difficult for store owners to track and monitor the performance of a product in terms of its sales, shelf life, cost and customer response. IoT acts as a solution to this problem as it facilitates the use of Wireless Sensor Networks (WSN) in order to interconnect all the various actors in a logistic system. This humongous network of interconnected devices generate massive amounts of data which is difficult to store and process. Cloud computing here plays a role of a facilitator and provides great help in addressing challenges related to storage and processing capabilities. In this paper, we present an Interactive Shopping Model along with an Automated Inventory Intelligent Management System (AIMS) that benefits from the amalgamation of IoT and Cloud and provides real time monitoring, tracking and management of products. We also propose an algorithm that depicts the working of our system. The proposed system along with the algorithm are simulated using the iFogSim simulator. To this end, we illustrate the working of our proposed system along with the simulated results.
{"title":"IoT based interactive shopping ecosystem","authors":"Abhirup Khanna, Ravi Tomar","doi":"10.1109/NGCT.2016.7877387","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877387","url":null,"abstract":"Internet of Things aims at integrating networked information systems to real world entities. It connects objects such as smart phones, sensors, LED(Light Emitting Diodes) displays and even clothes through the internet allowing them to interact and exchange information among themselves. In today's times IoT has found its application in practically every walk of life and inventory management is no exception. At present, inventory management is becoming increasingly complex, where there is an exponential rise in the diversity and number of both products and customers. The biggest problem faced by store owners is to optimize the experience of inventory management along with increased sales and reduced operational costs. With such enormous product lines it becomes extremely difficult for store owners to track and monitor the performance of a product in terms of its sales, shelf life, cost and customer response. IoT acts as a solution to this problem as it facilitates the use of Wireless Sensor Networks (WSN) in order to interconnect all the various actors in a logistic system. This humongous network of interconnected devices generate massive amounts of data which is difficult to store and process. Cloud computing here plays a role of a facilitator and provides great help in addressing challenges related to storage and processing capabilities. In this paper, we present an Interactive Shopping Model along with an Automated Inventory Intelligent Management System (AIMS) that benefits from the amalgamation of IoT and Cloud and provides real time monitoring, tracking and management of products. We also propose an algorithm that depicts the working of our system. The proposed system along with the algorithm are simulated using the iFogSim simulator. To this end, we illustrate the working of our proposed system along with the simulated results.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127550377","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877477
Ramandeep Kaur, M. Bansal
In the wide growth of information technology, security has one challenging phase for computer and networks. Attacks on the web are increasing day-by-day. Intrusion detection system is used to detect several types of malicious attacks that can compromise the security of a computer system. Data mining techniques are used to monitor and analyze large amount of network data & classify these network data into abnormal and normal data. Various data mining techniques like classification and clustering are applied to build Intrusion detection system. An effective Intrusion detection system needs high detection rate, low false alarm rate and high accuracy. This presents IDS uses the KDD Cup 99 dataset and completely different Data mining techniques are used on IDS for the effective detection of the abnormal and normal activities in network, that helps to develop secure information system. The multidimensional feature representation method is an important pattern classifier that facilitates correct classifications. Then, this new and multidimensional feature descriptor is used to represent each data sample for intrusion detection and SVM(Support Vector Machine) classifier are used for correct classification of normal data and attacks. It also provides the bad data filtering from a given dataset.
在信息技术的广泛发展中，计算机和网络的安全是一个具有挑战性的阶段。对网络的攻击日益增多。入侵检测系统用于检测几种可能危及计算机系统安全的恶意攻击。数据挖掘技术用于对大量的网络数据进行监控和分析，并将这些网络数据分为异常数据和正常数据。入侵检测系统采用了分类、聚类等多种数据挖掘技术。一个有效的入侵检测系统需要高检测率、低虚警率和高准确率。本文介绍了基于KDD Cup 99数据集的入侵检测系统，在入侵检测系统上采用了完全不同的数据挖掘技术，有效地检测出网络中的异常和正常活动，有助于开发安全的信息系统。多维特征表示方法是一种重要的模式分类器，有助于正确分类。然后，利用这个新的多维特征描述符来表示入侵检测的每个数据样本，并使用支持向量机分类器对正常数据和攻击进行正确分类。它还提供来自给定数据集的坏数据过滤。
{"title":"Multidimensional attacks classification based on genetic algorithm and SVM","authors":"Ramandeep Kaur, M. Bansal","doi":"10.1109/NGCT.2016.7877477","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877477","url":null,"abstract":"In the wide growth of information technology, security has one challenging phase for computer and networks. Attacks on the web are increasing day-by-day. Intrusion detection system is used to detect several types of malicious attacks that can compromise the security of a computer system. Data mining techniques are used to monitor and analyze large amount of network data & classify these network data into abnormal and normal data. Various data mining techniques like classification and clustering are applied to build Intrusion detection system. An effective Intrusion detection system needs high detection rate, low false alarm rate and high accuracy. This presents IDS uses the KDD Cup 99 dataset and completely different Data mining techniques are used on IDS for the effective detection of the abnormal and normal activities in network, that helps to develop secure information system. The multidimensional feature representation method is an important pattern classifier that facilitates correct classifications. Then, this new and multidimensional feature descriptor is used to represent each data sample for intrusion detection and SVM(Support Vector Machine) classifier are used for correct classification of normal data and attacks. It also provides the bad data filtering from a given dataset.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128138184","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}
Pub Date : 2016-10-01DOI: 10.1109/NGCT.2016.7877525
Narendra Panwar, M. Rauthan, Amit Agarwal
Online healthcare system provides healthcare services remotely to the patient which include telecare medicine system, patient monitoring system, patient healthcare system etc. Authentication schemes plays a significant and crucial role in providing legitimacy of patient and protection to medical resources/services. New trends in cryptography make the online healthcare services feasible solution to the patient and healthcare sector. It aims to help the medical physician and healthcare workers to make fast and accurate clinical decision. This paper discusses the security vulnerabilities of Das et al scheme and demonstrates various security attack. Our cryptanalysis proves the weakness of their scheme against the login phase and authentication phase.
{"title":"Cryptanalysis of smart card and biometric-hash based authentication scheme","authors":"Narendra Panwar, M. Rauthan, Amit Agarwal","doi":"10.1109/NGCT.2016.7877525","DOIUrl":"https://doi.org/10.1109/NGCT.2016.7877525","url":null,"abstract":"Online healthcare system provides healthcare services remotely to the patient which include telecare medicine system, patient monitoring system, patient healthcare system etc. Authentication schemes plays a significant and crucial role in providing legitimacy of patient and protection to medical resources/services. New trends in cryptography make the online healthcare services feasible solution to the patient and healthcare sector. It aims to help the medical physician and healthcare workers to make fast and accurate clinical decision. This paper discusses the security vulnerabilities of Das et al scheme and demonstrates various security attack. Our cryptanalysis proves the weakness of their scheme against the login phase and authentication phase.","PeriodicalId":326018,"journal":{"name":"2016 2nd International Conference on Next Generation Computing Technologies (NGCT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114505342","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：