Pub Date : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032592
Dominik Soukup, Ondřej Hujňák, Simon Štefunko, Radek Krejcí, Erik Gresak
Our environment becomes more and more interconnected. Various devices like refrigerators, doors or light bulbs communicate over different networks and provide information for applications that are supposed to make our lives easier and more comfortable. However, such data provide sensitive information about our presence or habits and become captivating for network attackers. It is very challenging to detect incidents in heterogeneous IoT networks where different devices come in and out or change their network profiles quite frequently. We propose a security framework for IoT and fog computing networks to address these challenges. Our framework is very flexible and designed even for devices with limited computational power. All components can be deployed on one network node or distributed among many, which also allows easy scalability. Part of our solution is software IoT gateway that provides the capability to analyse traffic from non-IP IoT sensors. This project covers full-stack security solution because it contains collectors, detectors and management tools. This framework has only software components with no relation to any specific hardware device. It is developed as an open-source project and it is publicly available for the worldwide community. Currently developed detectors detect identified vulnerabilities for Z-Wave, Long Range Wide Area Network (Lo-RaWAN), BLE and IP based IoT protocols.
{"title":"Security Framework for IoT and Fog Computing Networks","authors":"Dominik Soukup, Ondřej Hujňák, Simon Štefunko, Radek Krejcí, Erik Gresak","doi":"10.1109/I-SMAC47947.2019.9032592","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032592","url":null,"abstract":"Our environment becomes more and more interconnected. Various devices like refrigerators, doors or light bulbs communicate over different networks and provide information for applications that are supposed to make our lives easier and more comfortable. However, such data provide sensitive information about our presence or habits and become captivating for network attackers. It is very challenging to detect incidents in heterogeneous IoT networks where different devices come in and out or change their network profiles quite frequently. We propose a security framework for IoT and fog computing networks to address these challenges. Our framework is very flexible and designed even for devices with limited computational power. All components can be deployed on one network node or distributed among many, which also allows easy scalability. Part of our solution is software IoT gateway that provides the capability to analyse traffic from non-IP IoT sensors. This project covers full-stack security solution because it contains collectors, detectors and management tools. This framework has only software components with no relation to any specific hardware device. It is developed as an open-source project and it is publicly available for the worldwide community. Currently developed detectors detect identified vulnerabilities for Z-Wave, Long Range Wide Area Network (Lo-RaWAN), BLE and IP based IoT protocols.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127733903","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032472
G. Shobana, M. Suguna
Blockchain is decentralized architecture, where data are stored in the form of blocks for processing. The data has to be transferred from one person to another with safety and security and updated with smart contract in the blockchain. But there are some challenges such as data spoofing, integrity, authentication of the data. In the health sector the privacy of the patients' data has to be maintained. The proposed system, “Insurance Management in Healthcare Sector” uses blockchain combined with identity management to access the identity of a person when authorized by the person. After verifying the details, the insured amount will be transferred to the policy holder or the hospital with the help of matching smart contracts in the blockchain of the Ethereum platform. As a result, the insurance claim can reach the policy holder who has initiated the claim process with proof of work. The other use cases such as health care industries, social media networks are also discussed and the analysis of how the blockchain can be used in various fields.
{"title":"Block Chain Technology towards Identity Management in Health Care Application","authors":"G. Shobana, M. Suguna","doi":"10.1109/I-SMAC47947.2019.9032472","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032472","url":null,"abstract":"Blockchain is decentralized architecture, where data are stored in the form of blocks for processing. The data has to be transferred from one person to another with safety and security and updated with smart contract in the blockchain. But there are some challenges such as data spoofing, integrity, authentication of the data. In the health sector the privacy of the patients' data has to be maintained. The proposed system, “Insurance Management in Healthcare Sector” uses blockchain combined with identity management to access the identity of a person when authorized by the person. After verifying the details, the insured amount will be transferred to the policy holder or the hospital with the help of matching smart contracts in the blockchain of the Ethereum platform. As a result, the insurance claim can reach the policy holder who has initiated the claim process with proof of work. The other use cases such as health care industries, social media networks are also discussed and the analysis of how the blockchain can be used in various fields.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131009656","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032445
V. R. Machavaram, B. Nistala
A compact very low loss onchip bandpass filter which suits the 5G radio frequency front end (RFFE) filtering requirements, is reported here. The proposed filter is modeled using $0.18 mumathrm{m}$ CMOS Silicon substrate IPD technology. A series LC resonant onchip BPF structure is designed and simulated by combining a passive multilayer (ML) spiral inductor and a planar spiral capacitor in High Frequency Structural Simulator (HFSS) at component level. The filter showed a quality factor (Q) value of 7.3125 and a fractional bandwidth of 13% (< 20%). It had exhibited very good insertion loss of −0.415 dB and also excellent return loss of −42.9 dB, at a self-resonant (SRF) frequency of 3.5 GHz. The physical dimensions of the Inductor, Capacitor and bandpass filter are $340times 240 mumathrm{m}^{2},quad 280times 240 mumathrm{m}^{2}$ and $480times 240 mumathrm{m}^{2}$ respectively. It had demonstrated with an excellent loss along with a narrow passband characteristics, still occupying very small onchip area. Hence, this compact resonator filter definitely suits the 5G front end filter applications. We simulated this filter by focusing around 3.5 GHz, as this spectral band is used in 4G and also being actively considered for several 5G trials and installations across several countries.
本文报道了一种紧凑型极低损耗片上带通滤波器，适合5G射频前端(RFFE)滤波要求。该滤波器采用$0.18 mu mathm {m}$ CMOS硅衬底IPD技术建模。采用无源多层螺旋电感与平面螺旋电容相结合的方法，在高频结构模拟器(HFSS)中设计并仿真了串联LC谐振片上BPF结构。该滤波器的质量因子(Q)值为7.3125，分数带宽为13%(< 20%)。在自谐振(SRF)频率为3.5 GHz时，其插入损耗为- 0.415 dB，回波损耗为- 42.9 dB。电感器、电容和带通滤波器的物理尺寸分别为$340乘以240 mu mathm {m}^{2}， $ quad 280乘以240 mu mathm {m}^{2}$和$480乘以240 mu mathm {m}^{2}$。实验证明，该芯片具有良好的损耗和窄通带特性，且占用的片上面积很小。因此，这款紧凑型谐振器滤波器绝对适合5G前端滤波器应用。我们通过聚焦3.5 GHz左右来模拟该滤波器，因为该频段用于4G，并且正在积极考虑在几个国家进行几次5G试验和安装。
{"title":"A Compact Low Loss Onchip Bandpass Filter For 5G Radio Front End Using Integrated Passive Device Technology","authors":"V. R. Machavaram, B. Nistala","doi":"10.1109/I-SMAC47947.2019.9032445","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032445","url":null,"abstract":"A compact very low loss onchip bandpass filter which suits the 5G radio frequency front end (RFFE) filtering requirements, is reported here. The proposed filter is modeled using $0.18 mumathrm{m}$ CMOS Silicon substrate IPD technology. A series LC resonant onchip BPF structure is designed and simulated by combining a passive multilayer (ML) spiral inductor and a planar spiral capacitor in High Frequency Structural Simulator (HFSS) at component level. The filter showed a quality factor (Q) value of 7.3125 and a fractional bandwidth of 13% (< 20%). It had exhibited very good insertion loss of −0.415 dB and also excellent return loss of −42.9 dB, at a self-resonant (SRF) frequency of 3.5 GHz. The physical dimensions of the Inductor, Capacitor and bandpass filter are $340times 240 mumathrm{m}^{2},quad 280times 240 mumathrm{m}^{2}$ and $480times 240 mumathrm{m}^{2}$ respectively. It had demonstrated with an excellent loss along with a narrow passband characteristics, still occupying very small onchip area. Hence, this compact resonator filter definitely suits the 5G front end filter applications. We simulated this filter by focusing around 3.5 GHz, as this spectral band is used in 4G and also being actively considered for several 5G trials and installations across several countries.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128994307","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}
Accurate classification and counting of blood components is crucial in detection of illnesses of an individual. The widely used methods to count blood components are manual counting and hematology analyzer. With advancement in the field of image processing and machine learning, new and better methods are available for counting and classifying blood components. Deep leaning is training the computer with labelled data for classification tasks. Such techniques have shown high performance and accuracy. Most Deep learning models uses neural network architecture. One of the most popular type of deep learning model is Convolutional Neural Network. CNN convolves learned features with input data, and uses 2D convolutional layers, making this architecture well suited to processing 2D data, such as images. CNN's extract the features from the image automatically using numerous hidden layers. Most Deep learning models use transfer learning that is fine-tuning a pre-trained model. RCNN stands for Region based CNN. Unlike CNN which is used for image classification, RCNN is used for object detection. Thus in this paper, we have proposed a method to classify various components of blood : RBCs, WBCs (Monocyte, Lymphocytes, Eosinophils, Neutrophils and Basophils) and find their count from a microscopic blood image using Faster R-CNN model. Thus generating a CBC (Complete Blood Count) report which can be used by medical professionals to diagnose, suggest tests and treatments to their patients.
{"title":"Recognizing Presence of Hematological Disease using Deep Learning","authors":"Bhagyeshri Darane, Prathamesh Rajput, Yogesh Sondagar, Reeta Koshy","doi":"10.1109/I-SMAC47947.2019.9032639","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032639","url":null,"abstract":"Accurate classification and counting of blood components is crucial in detection of illnesses of an individual. The widely used methods to count blood components are manual counting and hematology analyzer. With advancement in the field of image processing and machine learning, new and better methods are available for counting and classifying blood components. Deep leaning is training the computer with labelled data for classification tasks. Such techniques have shown high performance and accuracy. Most Deep learning models uses neural network architecture. One of the most popular type of deep learning model is Convolutional Neural Network. CNN convolves learned features with input data, and uses 2D convolutional layers, making this architecture well suited to processing 2D data, such as images. CNN's extract the features from the image automatically using numerous hidden layers. Most Deep learning models use transfer learning that is fine-tuning a pre-trained model. RCNN stands for Region based CNN. Unlike CNN which is used for image classification, RCNN is used for object detection. Thus in this paper, we have proposed a method to classify various components of blood : RBCs, WBCs (Monocyte, Lymphocytes, Eosinophils, Neutrophils and Basophils) and find their count from a microscopic blood image using Faster R-CNN model. Thus generating a CBC (Complete Blood Count) report which can be used by medical professionals to diagnose, suggest tests and treatments to their patients.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131614795","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032656
B. Neethu, S. Jayanthy, J JudesonAntonyKovilpillai.
An embedded system is developed for monitoring and controlling the parameters that affect the growth of plants using STM32F401RE ARM Cortex M4 based Microcontrollers. Parameters such as Light intensity, Soil Moisture, CO2, Temperature, are monitored. The measured values are processed using Modified K Means Clustering Algorithm to find if the values are needed to be optimized to the required level to enhance the plant growth. The results are compared with the Traditional K-Means Clustering algorithm. The results indicate that the proposed algorithm gives better results in terms of accuracy and execution time compared to traditional one. The data that are measured and predicted are viewed using Cool Term.
{"title":"Greenhouse Monitoring and Controlling using Modified K Means Clustering Algorithm","authors":"B. Neethu, S. Jayanthy, J JudesonAntonyKovilpillai.","doi":"10.1109/I-SMAC47947.2019.9032656","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032656","url":null,"abstract":"An embedded system is developed for monitoring and controlling the parameters that affect the growth of plants using STM32F401RE ARM Cortex M4 based Microcontrollers. Parameters such as Light intensity, Soil Moisture, CO2, Temperature, are monitored. The measured values are processed using Modified K Means Clustering Algorithm to find if the values are needed to be optimized to the required level to enhance the plant growth. The results are compared with the Traditional K-Means Clustering algorithm. The results indicate that the proposed algorithm gives better results in terms of accuracy and execution time compared to traditional one. The data that are measured and predicted are viewed using Cool Term.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115389711","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032570
T. Upadhyaya, Riki H. Patel, A. Desai, Upesh Patel, K. Pandya, K. Kaur
A negative refractive index material loaded wideband patch resonator is presented for the wireless applications. The negative refraction has been achieved by creating a semi-circular and linear defect in the antenna ground plane. The antenna demonstrates an electrical tilt. This presents the ability to keep the communication module mechanically vertical. The engineered metallic strip excites the resonance mode. The structure of the metallic strip is a modification of thin wire and split-ring resonator (SRR) which are responsible for negative values of permeability and permittivity respectively. The finite truncated ground plane significantly helps to improve the antenna bandwidth. The antenna has an electrical length of $0.65lambda times 0.65lambda$ where $lambda$ is the wavelength at lowest resonance. The resonating frequencies of antenna are 2.46, 3.5, and 5.5 GigaHertz, respectively. The antenna has impedance bandwidth of 8.94%, 14.57% and 8.72% for the presented center frequencies respectively. The antenna prototype was fabricated where measured and simulated results show good correlation.
{"title":"Electrically Tilted Broadband Antenna using Negative Refractive Index material","authors":"T. Upadhyaya, Riki H. Patel, A. Desai, Upesh Patel, K. Pandya, K. Kaur","doi":"10.1109/I-SMAC47947.2019.9032570","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032570","url":null,"abstract":"A negative refractive index material loaded wideband patch resonator is presented for the wireless applications. The negative refraction has been achieved by creating a semi-circular and linear defect in the antenna ground plane. The antenna demonstrates an electrical tilt. This presents the ability to keep the communication module mechanically vertical. The engineered metallic strip excites the resonance mode. The structure of the metallic strip is a modification of thin wire and split-ring resonator (SRR) which are responsible for negative values of permeability and permittivity respectively. The finite truncated ground plane significantly helps to improve the antenna bandwidth. The antenna has an electrical length of $0.65lambda times 0.65lambda$ where $lambda$ is the wavelength at lowest resonance. The resonating frequencies of antenna are 2.46, 3.5, and 5.5 GigaHertz, respectively. The antenna has impedance bandwidth of 8.94%, 14.57% and 8.72% for the presented center frequencies respectively. The antenna prototype was fabricated where measured and simulated results show good correlation.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127589508","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032618
Sunanda Nalajala, K. Akhil, V. Sai, D. Shekhar, Praveen Tumuluru
Nowadays more and more data is stored and retrieved through Cloud Computing. With advancement there arises a problem in security. This means the data can be decrypted easily and the content being accessed by strangers and the privacy of the data will be lost. We have introduced a new algorithm known as “Cipher Attribute Based Encryption Algorithm” with symmetric key in our newly proposed light weight data sharing scheme for mobile cloud computing. Light weight in the sense, data with a fairly light storage capacity like files, audio clips etc. will be secured based on our proposed concept LDSS. The LDSS structure is modified and used as an access control in Cipher Attribute Based Encryption (CP-ABE). To reduce the user cost, it introduced attribute description fields to implement lazy revocation which is difficult in CP-ABE working systems. Everything in this operation might not be applicable in all mobile devices because the components are small and flexibility is less. The results from this paper show the issues related to data privacy have been solved in most cases for light weight data sharing scheme.
{"title":"Light Weight Secure Data Sharing Scheme for Mobile Cloud Computing","authors":"Sunanda Nalajala, K. Akhil, V. Sai, D. Shekhar, Praveen Tumuluru","doi":"10.1109/I-SMAC47947.2019.9032618","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032618","url":null,"abstract":"Nowadays more and more data is stored and retrieved through Cloud Computing. With advancement there arises a problem in security. This means the data can be decrypted easily and the content being accessed by strangers and the privacy of the data will be lost. We have introduced a new algorithm known as “Cipher Attribute Based Encryption Algorithm” with symmetric key in our newly proposed light weight data sharing scheme for mobile cloud computing. Light weight in the sense, data with a fairly light storage capacity like files, audio clips etc. will be secured based on our proposed concept LDSS. The LDSS structure is modified and used as an access control in Cipher Attribute Based Encryption (CP-ABE). To reduce the user cost, it introduced attribute description fields to implement lazy revocation which is difficult in CP-ABE working systems. Everything in this operation might not be applicable in all mobile devices because the components are small and flexibility is less. The results from this paper show the issues related to data privacy have been solved in most cases for light weight data sharing scheme.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121896416","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032609
Padmaveni Krishnan, D. Aravindhar, D. P. Kumar
The fast and up-to-date communication of disaster and recovery information during crisis plays a very important role in victims' life. Most of the information will reach as text and could be communicated as such. But this needs proper network coverage. In this research paper, a new software is developed to convert the text into vector images ie., syntagms into signagrams, and groups the crisis into categories using adaptive resonance theory. The proposed software can be used for delivering a quick and effective communication during crisis.
{"title":"Text to vector image conversion and Adaptive Resonance Theory applied for Crisis communication","authors":"Padmaveni Krishnan, D. Aravindhar, D. P. Kumar","doi":"10.1109/I-SMAC47947.2019.9032609","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032609","url":null,"abstract":"The fast and up-to-date communication of disaster and recovery information during crisis plays a very important role in victims' life. Most of the information will reach as text and could be communicated as such. But this needs proper network coverage. In this research paper, a new software is developed to convert the text into vector images ie., syntagms into signagrams, and groups the crisis into categories using adaptive resonance theory. The proposed software can be used for delivering a quick and effective communication during crisis.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"275 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123083906","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032580
R. Meena, V. T. Bai
Due to the rapid advancements in social media, it generates voluminous data in almost different areas of applications. Large amount of potential health related data are being available in large scale in various sources of internet. We explored the small use case of social media data for a particular disease, cancer on three different social media platforms such as google trends, twitter and online forums with the sentiment analysis of the mined text. The study shows that people are more relied on social media for their health related queries and the twitter analysis shows that there is a significant raise in the percentage of positive sentiments in the tweets shared by the organizations and individuals on cancer.
{"title":"Study on Machine learning based Social Media and Sentiment analysis for medical data applications","authors":"R. Meena, V. T. Bai","doi":"10.1109/I-SMAC47947.2019.9032580","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032580","url":null,"abstract":"Due to the rapid advancements in social media, it generates voluminous data in almost different areas of applications. Large amount of potential health related data are being available in large scale in various sources of internet. We explored the small use case of social media data for a particular disease, cancer on three different social media platforms such as google trends, twitter and online forums with the sentiment analysis of the mined text. The study shows that people are more relied on social media for their health related queries and the twitter analysis shows that there is a significant raise in the percentage of positive sentiments in the tweets shared by the organizations and individuals on cancer.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121848764","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 : 2019-12-01DOI: 10.1109/I-SMAC47947.2019.9032526
S. Vyshnavi, S. Sree, N. Jayapandian
The modern world technology is civilized, globalized and modernized. The technological development of social networks and e-commerce applications produce larger data. This data communication is major task, because device to device communication need network terminal. This data transmission is not safe because of different types of tools and software available to destroy the existing network. In the field of network security during data transfer from one particular node to other node some security vulnerability is happened this is the one of the critical issue in this sector. The reason for this network security is different types of data attacks are happen in day to day life. It is easy to establish a new network but protecting the entire network is a big issue. This network security is generally two parameter first one is communication and second one is data automation. The network security field is directly or indirectly linked with the concept of data encryption. The development in this network security has taken us to a level that from signature again we came back to thumb print. For example maintain the data secure we use the lock system which is a finger print type. This technology helps us to protect the physical data theft, but logical data theft is still problem for data transmission. This article will brief about the network security it also presents the various network security types. Those types are wired and wireless network security. Apart from the network security the following topics is also discussed in this article. Those are network security protocols and simulation tools in network security. The research problems in network security are privacy and vulnerability of data.
{"title":"Network Security Tools and Applications in Research Perspective","authors":"S. Vyshnavi, S. Sree, N. Jayapandian","doi":"10.1109/I-SMAC47947.2019.9032526","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032526","url":null,"abstract":"The modern world technology is civilized, globalized and modernized. The technological development of social networks and e-commerce applications produce larger data. This data communication is major task, because device to device communication need network terminal. This data transmission is not safe because of different types of tools and software available to destroy the existing network. In the field of network security during data transfer from one particular node to other node some security vulnerability is happened this is the one of the critical issue in this sector. The reason for this network security is different types of data attacks are happen in day to day life. It is easy to establish a new network but protecting the entire network is a big issue. This network security is generally two parameter first one is communication and second one is data automation. The network security field is directly or indirectly linked with the concept of data encryption. The development in this network security has taken us to a level that from signature again we came back to thumb print. For example maintain the data secure we use the lock system which is a finger print type. This technology helps us to protect the physical data theft, but logical data theft is still problem for data transmission. This article will brief about the network security it also presents the various network security types. Those types are wired and wireless network security. Apart from the network security the following topics is also discussed in this article. Those are network security protocols and simulation tools in network security. The research problems in network security are privacy and vulnerability of data.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131334950","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}
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