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-SMAC47947.2019.9032431
B. Siddartha, G. Ravikumar
Increased use of modern advanced electronic devices rapidly increased the data collection rate, most of the advanced healthcare industries today are using updated healthcare facilities with the advanced healthcare technologies to collect and process the data. Healthcare data generated by the most of the industries are in the digital format. Provisioning protection and security to the PHI is the major concern but it is very difficult to safeguard the generated data from unauthorized users or breaches. There are many advanced techniques are in use today to protect the individuals sensitive data. Data masking approach is the advanced technique that enables security provisioning of personnel health records. This paper presented the in-depth study on current healthcare security techniques and summarized the gaps in security provisioning. Conclusion part of the paper highlights the some of the acts and policies adopted by the countries to safeguard the citizens' healthcare data.
{"title":"Analysis of Masking Techniques to Find out Security and other Efficiency Issues in Healthcare Domain","authors":"B. Siddartha, G. Ravikumar","doi":"10.1109/I-SMAC47947.2019.9032431","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032431","url":null,"abstract":"Increased use of modern advanced electronic devices rapidly increased the data collection rate, most of the advanced healthcare industries today are using updated healthcare facilities with the advanced healthcare technologies to collect and process the data. Healthcare data generated by the most of the industries are in the digital format. Provisioning protection and security to the PHI is the major concern but it is very difficult to safeguard the generated data from unauthorized users or breaches. There are many advanced techniques are in use today to protect the individuals sensitive data. Data masking approach is the advanced technique that enables security provisioning of personnel health records. This paper presented the in-depth study on current healthcare security techniques and summarized the gaps in security provisioning. Conclusion part of the paper highlights the some of the acts and policies adopted by the countries to safeguard the citizens' healthcare data.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"13 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":"114515483","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-SMAC47947.2019.9032492
V. M. Yazhmozhi, B. Janet
Because of the colossal growth of internet, most of the users have changed their preference from traditional shopping, banking etc. to online mode. This paved the way for a lot of cybercrimes including phishing into existence. The attackers try to extract sensitive/personal details such as user ID, passwords and debit card/credit card information by disguising themselves as reliable websites. Identifying whether the Uniform Resource Locator (URL) of a website is legitimate or phishing is a difficult task because it exploits the user's vulnerabilities. Although many products are available for detecting phishing websites, they are just making use of heuristic approach and black lists and hence they can't prevent phishing in a more effective way. A system that detects phishing websites in real time has been proposed in this paper. It uses five different classification algorithms with two different feature sets using natural language processing and word vectors to identify which performs better. After analyzing the accuracy of different machine learning classification algorithms like naive bayes, logistic regression, support vector machine, decision tree and random forest using different features, it has been found that random Forest algorithm with features based on natural language processing has performed better with an accuracy of 97.99.
{"title":"Natural language processing and Machine learning based phishing website detection system","authors":"V. M. Yazhmozhi, B. Janet","doi":"10.1109/I-SMAC47947.2019.9032492","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032492","url":null,"abstract":"Because of the colossal growth of internet, most of the users have changed their preference from traditional shopping, banking etc. to online mode. This paved the way for a lot of cybercrimes including phishing into existence. The attackers try to extract sensitive/personal details such as user ID, passwords and debit card/credit card information by disguising themselves as reliable websites. Identifying whether the Uniform Resource Locator (URL) of a website is legitimate or phishing is a difficult task because it exploits the user's vulnerabilities. Although many products are available for detecting phishing websites, they are just making use of heuristic approach and black lists and hence they can't prevent phishing in a more effective way. A system that detects phishing websites in real time has been proposed in this paper. It uses five different classification algorithms with two different feature sets using natural language processing and word vectors to identify which performs better. After analyzing the accuracy of different machine learning classification algorithms like naive bayes, logistic regression, support vector machine, decision tree and random forest using different features, it has been found that random Forest algorithm with features based on natural language processing has performed better with an accuracy of 97.99.","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"85 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":"114290526","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-SMAC47947.2019.9032666
Sachin Kumar, S. V., Vijayalaxmi
Indirect Immunfluorsece method (IFA) is one of the important laboratory procedures for the diagnosis of the autoimmune disease, but it suffers from low throughput and subjectivity due to manual interpretation. The Human Epithelial type-2 (HEp-2) pattern, such as homogeneous, speckled, centromere, Nucleolar pattern images, gives the diagnosis of different autoimmune diseases. For the current study, different patterns are obtained from the publicly available datasets A.I.D.A ((Auto- Immunity Diagnosis by Computer) project of 1000 images. The images pre-processed and features such as statistical and textural features extracted and explored to find the appropriate one for the detection and the classification of ANA HEp2 cells pattern. The paper uses the Analysis of Variance (ANOVA) for the identification of appropriate features and Artifical Neural network (ANN) for classification. The result obtained indicates that textural features are the better features in comparison with other extracted features, with the results obtained average accuracy around 92% using ANN as the classifier. The outcome thus produced is useful for the further design of cost-effective image analysis in the autoimmune diagnosis
{"title":"Automatic classification of ANA HEp-2 Immunofluorescence images based on the texture features using artificial neural network","authors":"Sachin Kumar, S. V., Vijayalaxmi","doi":"10.1109/I-SMAC47947.2019.9032666","DOIUrl":"https://doi.org/10.1109/I-SMAC47947.2019.9032666","url":null,"abstract":"Indirect Immunfluorsece method (IFA) is one of the important laboratory procedures for the diagnosis of the autoimmune disease, but it suffers from low throughput and subjectivity due to manual interpretation. The Human Epithelial type-2 (HEp-2) pattern, such as homogeneous, speckled, centromere, Nucleolar pattern images, gives the diagnosis of different autoimmune diseases. For the current study, different patterns are obtained from the publicly available datasets A.I.D.A ((Auto- Immunity Diagnosis by Computer) project of 1000 images. The images pre-processed and features such as statistical and textural features extracted and explored to find the appropriate one for the detection and the classification of ANA HEp2 cells pattern. The paper uses the Analysis of Variance (ANOVA) for the identification of appropriate features and Artifical Neural network (ANN) for classification. The result obtained indicates that textural features are the better features in comparison with other extracted features, with the results obtained average accuracy around 92% using ANN as the classifier. The outcome thus produced is useful for the further design of cost-effective image analysis in the autoimmune diagnosis","PeriodicalId":275791,"journal":{"name":"2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"3 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":"121109031","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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