Pub Date : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039559
Rishabh Bhargava, Russel Lobo, Rushabh Shah, Nishank Shah, S. Nair
The Web has changed significantly in recent years, and websites now carry increasing information which has given rise to websites that can be difficult to navigate because of complex UI. In this work, an approach is presented which will make web navigation easier by incorporating the concepts of data scraping and intent classifiers with a natural language processing model. Our proposed concept is to create a dynamic NLUI (natural language user interface) that makes web navigation easier based on queries that can be text or voice-based. The proposed approach will help the user to obtain answers to their queries which will make web navigation easier. This is done by classifying user queries as intents and the required data is scraped from the website and when integrated with NLP models, helps achieve flexibility in understanding the context to a greater extent. The intent classification model used achieves an accuracy of 99.1 percent on our self-curated dataset. Selenium web drivers and BeautifulSoup have been used for web scraping. The integration of a BERT q/a module was also done, there are endless models and a lot of potential to scale the work and make it more flexible
{"title":"Easier Web Navigation Using Intent Classification, Web Scraping and NLP Approaches","authors":"Rishabh Bhargava, Russel Lobo, Rushabh Shah, Nishank Shah, S. Nair","doi":"10.1109/ICAST55766.2022.10039559","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039559","url":null,"abstract":"The Web has changed significantly in recent years, and websites now carry increasing information which has given rise to websites that can be difficult to navigate because of complex UI. In this work, an approach is presented which will make web navigation easier by incorporating the concepts of data scraping and intent classifiers with a natural language processing model. Our proposed concept is to create a dynamic NLUI (natural language user interface) that makes web navigation easier based on queries that can be text or voice-based. The proposed approach will help the user to obtain answers to their queries which will make web navigation easier. This is done by classifying user queries as intents and the required data is scraped from the website and when integrated with NLP models, helps achieve flexibility in understanding the context to a greater extent. The intent classification model used achieves an accuracy of 99.1 percent on our self-curated dataset. Selenium web drivers and BeautifulSoup have been used for web scraping. The integration of a BERT q/a module was also done, there are endless models and a lot of potential to scale the work and make it more flexible","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131223163","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039604
Dhananjay Dhutraj, M. Nemade, Mayur Dikonda, Shlok Gokhale
The present disclosure relates to a medicine manufacturing device and in particular to an autonomous device for making capsules and filling them with medicines which is used by the doctors (ayurveda and homopathic). Making their work in simpler form with the help of electronics devices such as linear actuator and motor, the manual work is replaced with the automation through the autonomous device and here we have also used the servo motor for opening and closing lid of the funnel. We are using agar agar, Hydroxypropyl methyl cellulose, gellan gum as main ingredients for capsule. Our mainly focus is filling part where we fill the medicinal powder in the bottom part of the capsule and encapsulation of capsule where we joint the two parts i.e top part and bottom part of capsule. Our objective was to implement 5 Capsules at a time (15min Estimated)
{"title":"Autonomous Capsule Maker & Filler","authors":"Dhananjay Dhutraj, M. Nemade, Mayur Dikonda, Shlok Gokhale","doi":"10.1109/ICAST55766.2022.10039604","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039604","url":null,"abstract":"The present disclosure relates to a medicine manufacturing device and in particular to an autonomous device for making capsules and filling them with medicines which is used by the doctors (ayurveda and homopathic). Making their work in simpler form with the help of electronics devices such as linear actuator and motor, the manual work is replaced with the automation through the autonomous device and here we have also used the servo motor for opening and closing lid of the funnel. We are using agar agar, Hydroxypropyl methyl cellulose, gellan gum as main ingredients for capsule. Our mainly focus is filling part where we fill the medicinal powder in the bottom part of the capsule and encapsulation of capsule where we joint the two parts i.e top part and bottom part of capsule. Our objective was to implement 5 Capsules at a time (15min Estimated)","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131655413","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039479
V. Shelake, Vijay Pare
In this digital world, we have gradually shifted to all kinds of digital transactions. Due to the increasing number of various kinds of data formats or languages, it is quite difficult to accurately match data from different databases in a secure manner. Secure record linkage is the most prominent method for matching the data used in most of the industry now for maintaining security and privacy during similarity matching of encrypted records. Among different secure record linkage techniques, Blockchain is the recent technology useful for maintaining data privacy for similarity matching. Also, the demanded Bloom filter technique can be very helpful for storage, encryption and inline combination with Blockchain. However, the similarity matching over encrypted data can be cumbersome and lead to lesser linkage accuracy. In this review, the similarity matching for encrypted data has been discussed and analyzed.
{"title":"A Review of Similarity Matching Over Encrypted Data","authors":"V. Shelake, Vijay Pare","doi":"10.1109/ICAST55766.2022.10039479","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039479","url":null,"abstract":"In this digital world, we have gradually shifted to all kinds of digital transactions. Due to the increasing number of various kinds of data formats or languages, it is quite difficult to accurately match data from different databases in a secure manner. Secure record linkage is the most prominent method for matching the data used in most of the industry now for maintaining security and privacy during similarity matching of encrypted records. Among different secure record linkage techniques, Blockchain is the recent technology useful for maintaining data privacy for similarity matching. Also, the demanded Bloom filter technique can be very helpful for storage, encryption and inline combination with Blockchain. However, the similarity matching over encrypted data can be cumbersome and lead to lesser linkage accuracy. In this review, the similarity matching for encrypted data has been discussed and analyzed.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134325792","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039560
Jaikishan Bagul, Prajwal Warkhade, T. Gangwal, Nikhita Mangaonkar
Machine learning, in contrast to traditional algorithms and models, is a systematic and complete application of computer algorithms and statistical models that has been widely applied in a variety of industries. Machine learning is primarily utilized in finance to examine the future trend of capital market prices. In this research, we used traditional models and machine learning models for forecasting the linear and non-linear problems, respectively, to predict stock time-series data. To begin, stock samples from the National Stock Exchange from 2010 to 2019 are collected. To train and predict stock price and stock price sub correlation, the ARIMA (autoregressive integrated moving average model) and LSTM (long short-term memory) neural network models are used.
{"title":"ARIMA vs LSTM Algorithm – A Comparative Study Based on Stock Market Prediction","authors":"Jaikishan Bagul, Prajwal Warkhade, T. Gangwal, Nikhita Mangaonkar","doi":"10.1109/ICAST55766.2022.10039560","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039560","url":null,"abstract":"Machine learning, in contrast to traditional algorithms and models, is a systematic and complete application of computer algorithms and statistical models that has been widely applied in a variety of industries. Machine learning is primarily utilized in finance to examine the future trend of capital market prices. In this research, we used traditional models and machine learning models for forecasting the linear and non-linear problems, respectively, to predict stock time-series data. To begin, stock samples from the National Stock Exchange from 2010 to 2019 are collected. To train and predict stock price and stock price sub correlation, the ARIMA (autoregressive integrated moving average model) and LSTM (long short-term memory) neural network models are used.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"94 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133821927","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039530
Madhura Phadke, Anirudh Bhattacharya, Mink Shethia, Saumya Shah
In an industry with stiff competition among individual organizations, Churn is an important factor to be considered by the company itself as well as by prospective customers. In the telecommunication industry, churn can be affected by multiple factors: a customer's preference, location, job, and so on. Thus, customer churn in the telecom industry is a widely studied subject. However, churn based on previous rates alone is not enough to predict future churn and there must be additional factors considered. We propose a method to overcome this inadequacy. By using the predictions generated by past data, a rough estimate of the churn rate for a certain time period can be generated, such as a quarter or a year. A Machine Learning algorithm can be used for the same to get the value of the prediction. This value can be further tweaked by incorporating customer feedback which can affect the churn rate. Thus, the value generated by the predictions and the feedback will be more accurate.
{"title":"Feedback Based Telecom Churn Prediction Using Machine Learning","authors":"Madhura Phadke, Anirudh Bhattacharya, Mink Shethia, Saumya Shah","doi":"10.1109/ICAST55766.2022.10039530","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039530","url":null,"abstract":"In an industry with stiff competition among individual organizations, Churn is an important factor to be considered by the company itself as well as by prospective customers. In the telecommunication industry, churn can be affected by multiple factors: a customer's preference, location, job, and so on. Thus, customer churn in the telecom industry is a widely studied subject. However, churn based on previous rates alone is not enough to predict future churn and there must be additional factors considered. We propose a method to overcome this inadequacy. By using the predictions generated by past data, a rough estimate of the churn rate for a certain time period can be generated, such as a quarter or a year. A Machine Learning algorithm can be used for the same to get the value of the prediction. This value can be further tweaked by incorporating customer feedback which can affect the churn rate. Thus, the value generated by the predictions and the feedback will be more accurate.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"157 s321","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132904272","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039526
Piyushi Jain, Surekha Kohle
Transmission of information plays a vital role in the world. Now-a-days, at a given point of time, two people are transmitting messages from one place to another irrespective of the distance between them. But the main concern is that how does it guarantee that the message which is received by the receiver is not tampered or is hundred percent confidential. Therefore, this transmission process always faces some problems such as complex working, integrity issues and attacks, which make us doubt whether the data source is correct or incorrect. For this reason, many authors have come up with different variations of encrypting the data. This paper illustrates a Playfair cipher algorithm integrated with MD5 hashing and seed-based algorithm. It is a variation of Playfair cipher which tries to overcome some of the issues which can be seen in other variations of Playfair cipher. It not only provides great range of characters to work with but also provides integrity and prevents our message from man-in-the-middle and brute-force attacks.
{"title":"Variation of Playfair Cipher","authors":"Piyushi Jain, Surekha Kohle","doi":"10.1109/ICAST55766.2022.10039526","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039526","url":null,"abstract":"Transmission of information plays a vital role in the world. Now-a-days, at a given point of time, two people are transmitting messages from one place to another irrespective of the distance between them. But the main concern is that how does it guarantee that the message which is received by the receiver is not tampered or is hundred percent confidential. Therefore, this transmission process always faces some problems such as complex working, integrity issues and attacks, which make us doubt whether the data source is correct or incorrect. For this reason, many authors have come up with different variations of encrypting the data. This paper illustrates a Playfair cipher algorithm integrated with MD5 hashing and seed-based algorithm. It is a variation of Playfair cipher which tries to overcome some of the issues which can be seen in other variations of Playfair cipher. It not only provides great range of characters to work with but also provides integrity and prevents our message from man-in-the-middle and brute-force attacks.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114956819","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039602
Samrat Pravin Patel, S. S. Deshmukh
Drone, in today's world is considered as the disruptive technology. Drones are being adopted in various scientific and engineering endeavors very quickly. We always perceive drone as object that has capability to fly which one always assumes, as we credit its definition, to the word which is derived from Biology, “a male bee in a colony of social bees, which does no work but can fertilize a queen”. In actual sense drones can not only mean that they can fly but also, they can be capable of functioning on the land or float over the water or may be even underwater and underground. In future this technology will advance into complex network constantly exchanging data and working collaboratively to gather data. Unmanned Aerial Vehicle (UAV) systems as a data acquisition platform and as a measurement instrument are becoming popular means for many surveying. The traditional forest surveying is not cost effective due to the cost of data collection. This paper covers a brief literature review of the UAS, drone's application in forestry and its role in climate change by citing current application use cases along with some of the disadvantages in current UAS LiDAR sensing technology. Confined spaces have always been a challenge for the Wireless Radio Frequency signal propagation which can be a problem for controlling drones, hence this paper proposes a solution to this problem using novel wireless signal propagation techniques using “Leaky Feeder Antenna Cable” and proposing a potential application use case for inspection and surveillance using a Micro IoT(Internet of Things) based UGV for application in confined spaces such as natural gas pipelines which are hazardous to both humans and to the earth's climate. Other proposed application of this concept is in lunar space exploration such as lunar lava tubes.
{"title":"UAV and IoT Based Micro UGV Platform Applications for Forestry Climate Change and Lunar Space Explorations","authors":"Samrat Pravin Patel, S. S. Deshmukh","doi":"10.1109/ICAST55766.2022.10039602","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039602","url":null,"abstract":"Drone, in today's world is considered as the disruptive technology. Drones are being adopted in various scientific and engineering endeavors very quickly. We always perceive drone as object that has capability to fly which one always assumes, as we credit its definition, to the word which is derived from Biology, “a male bee in a colony of social bees, which does no work but can fertilize a queen”. In actual sense drones can not only mean that they can fly but also, they can be capable of functioning on the land or float over the water or may be even underwater and underground. In future this technology will advance into complex network constantly exchanging data and working collaboratively to gather data. Unmanned Aerial Vehicle (UAV) systems as a data acquisition platform and as a measurement instrument are becoming popular means for many surveying. The traditional forest surveying is not cost effective due to the cost of data collection. This paper covers a brief literature review of the UAS, drone's application in forestry and its role in climate change by citing current application use cases along with some of the disadvantages in current UAS LiDAR sensing technology. Confined spaces have always been a challenge for the Wireless Radio Frequency signal propagation which can be a problem for controlling drones, hence this paper proposes a solution to this problem using novel wireless signal propagation techniques using “Leaky Feeder Antenna Cable” and proposing a potential application use case for inspection and surveillance using a Micro IoT(Internet of Things) based UGV for application in confined spaces such as natural gas pipelines which are hazardous to both humans and to the earth's climate. Other proposed application of this concept is in lunar space exploration such as lunar lava tubes.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116937032","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039539
J. Kumar, Prachi Gholap, Vijaya Pinjarkar
According to statistics, tuberculosis kills many people each year; thus, if we create an awareness platform for it, people would be able to act accordingly. If people already have an x-ray report, they can check how much percent of the lungs are affected. The main aim of the following system is to have a handy tool which would be beneficial to people for checking their lungs conditions and whether they might have Tuberculosis or might not, suggestions will be provided to them based on their lung conditions, they can also check the symptoms along with particular information as provided on the proposed system. In this particular system, we use convolution neural networks to determine whether the image is tuberculosis positive or not.
{"title":"TuberculosisXpert - Prediction of Pulmonary Tuberculosis","authors":"J. Kumar, Prachi Gholap, Vijaya Pinjarkar","doi":"10.1109/ICAST55766.2022.10039539","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039539","url":null,"abstract":"According to statistics, tuberculosis kills many people each year; thus, if we create an awareness platform for it, people would be able to act accordingly. If people already have an x-ray report, they can check how much percent of the lungs are affected. The main aim of the following system is to have a handy tool which would be beneficial to people for checking their lungs conditions and whether they might have Tuberculosis or might not, suggestions will be provided to them based on their lung conditions, they can also check the symptoms along with particular information as provided on the proposed system. In this particular system, we use convolution neural networks to determine whether the image is tuberculosis positive or not.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668069","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039548
Anshu Mehta, Sukhada Virkar, Jay Khatri, Rhutuja Thakur, A. Dalvi
The importance of good mental health has been realised in recent times especially after the advent of the pandemic which has further worsened the mental health conditions. An individual facing mental disorders or having a tough time mentally often faces social stigma. Hence Chatbots can potentially prove to be a powerful tool for such people who are afraid of stigmatisation. This paper has been divided into two parts. The first part covers a detailed literature survey of the work that has been carried out in the field of medical chatbots and the algorithms that have been used in the proposed approach. The second part covers the implementation of the proposed system and the results obtained followed by the conclusion and future scope. Bidirectional LSTM model was used for performing sentiment analysis on user's text and an accuracy of 80.88% was obtained. The chatbot functions on the basis of a neural network model that provides a minimal loss.
{"title":"Artificial Intelligence Powered Chatbot for Mental Healthcare based on Sentiment Analysis","authors":"Anshu Mehta, Sukhada Virkar, Jay Khatri, Rhutuja Thakur, A. Dalvi","doi":"10.1109/ICAST55766.2022.10039548","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039548","url":null,"abstract":"The importance of good mental health has been realised in recent times especially after the advent of the pandemic which has further worsened the mental health conditions. An individual facing mental disorders or having a tough time mentally often faces social stigma. Hence Chatbots can potentially prove to be a powerful tool for such people who are afraid of stigmatisation. This paper has been divided into two parts. The first part covers a detailed literature survey of the work that has been carried out in the field of medical chatbots and the algorithms that have been used in the proposed approach. The second part covers the implementation of the proposed system and the results obtained followed by the conclusion and future scope. Bidirectional LSTM model was used for performing sentiment analysis on user's text and an accuracy of 80.88% was obtained. The chatbot functions on the basis of a neural network model that provides a minimal loss.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121642035","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 : 2022-12-02DOI: 10.1109/ICAST55766.2022.10039641
Sujata V. Kadam, Joanne Gomes
Wireless networks get subjected to the different attacks because of it's open nature. Eavesdropping attack, which occurs at the Physical layer of the OSI model, has a great impact on wireless network security. Conventional security in wireless networks depends on the cryptographic techniques. But in wireless sensor networks where a key management infrastructure may not be present and the power resources are also limited, generating a cryptographic key between two mobile entities becomes difficult. Hence Physical layer Security (PLS) has become a novel research solution. In PLS based key generation, a symmetric secret key is obtained at both the ends of the legitimate users using the properties of wireless channel. The key generation process includes four major blocks namely channel measurement, quantization of input samples, error detection and correction and privacy amplification. The output of quantizer has a great effect on the bit mismatch rate (BMR) between the two legitimate users. It also has an impact on key generation rate (KGR). Hence selecting a proper quantizer becomes very essential. In this paper different Quantization schemes are analyzed to achieve effective PLS between the two legitimate users.
{"title":"Comparative Analysis of Quantization Schemes for Physical Layer Key generation","authors":"Sujata V. Kadam, Joanne Gomes","doi":"10.1109/ICAST55766.2022.10039641","DOIUrl":"https://doi.org/10.1109/ICAST55766.2022.10039641","url":null,"abstract":"Wireless networks get subjected to the different attacks because of it's open nature. Eavesdropping attack, which occurs at the Physical layer of the OSI model, has a great impact on wireless network security. Conventional security in wireless networks depends on the cryptographic techniques. But in wireless sensor networks where a key management infrastructure may not be present and the power resources are also limited, generating a cryptographic key between two mobile entities becomes difficult. Hence Physical layer Security (PLS) has become a novel research solution. In PLS based key generation, a symmetric secret key is obtained at both the ends of the legitimate users using the properties of wireless channel. The key generation process includes four major blocks namely channel measurement, quantization of input samples, error detection and correction and privacy amplification. The output of quantizer has a great effect on the bit mismatch rate (BMR) between the two legitimate users. It also has an impact on key generation rate (KGR). Hence selecting a proper quantizer becomes very essential. In this paper different Quantization schemes are analyzed to achieve effective PLS between the two legitimate users.","PeriodicalId":225239,"journal":{"name":"2022 5th International Conference on Advances in Science and Technology (ICAST)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124677324","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：