Pub Date : 2023-03-31DOI: 10.1109/CSCITA55725.2023.10104947
Arpan Dhamelia, Gideon Harpanhalli, Arya Doshi, Ashna Kabsuri, Nitika Rai
The COVID-19 pandemic has led to the creation of vaccination passports as a means of verifying an individual’s vaccination status for travel and access to certain services. The validity of immunization records and supply chain procedures, however, are significant issues. The supply chain for vaccination passports has been called for to be made more secure and transparent using blockchain technology. To ensure safe and effective supply chain management, this article suggests a blockchain-based authentication mechanism for vaccination passports. The issuer, the prover, and the verifier will be the system’s three key actors. The issuer will be in charge of producing inventory tokens and providing immunization certificates. The prover will verify the authenticity of the vaccination supply chain, and the verifier will ensure that the inventory token is legitimate. The proposed system will enhance transparency, security, and efficiency in the supply chain for vaccination passports, thereby improving the trustworthiness of vaccination records and facilitating safe travel during the pandemic.
{"title":"Supply Chain Authentication for Vaccine Passport Using Blockchain","authors":"Arpan Dhamelia, Gideon Harpanhalli, Arya Doshi, Ashna Kabsuri, Nitika Rai","doi":"10.1109/CSCITA55725.2023.10104947","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104947","url":null,"abstract":"The COVID-19 pandemic has led to the creation of vaccination passports as a means of verifying an individual’s vaccination status for travel and access to certain services. The validity of immunization records and supply chain procedures, however, are significant issues. The supply chain for vaccination passports has been called for to be made more secure and transparent using blockchain technology. To ensure safe and effective supply chain management, this article suggests a blockchain-based authentication mechanism for vaccination passports. The issuer, the prover, and the verifier will be the system’s three key actors. The issuer will be in charge of producing inventory tokens and providing immunization certificates. The prover will verify the authenticity of the vaccination supply chain, and the verifier will ensure that the inventory token is legitimate. The proposed system will enhance transparency, security, and efficiency in the supply chain for vaccination passports, thereby improving the trustworthiness of vaccination records and facilitating safe travel during the pandemic.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115528889","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 : 2023-03-31DOI: 10.1109/CSCITA55725.2023.10104935
Yashika N. Mahajan, Deepika Mehta, Joel Miranda, Ron Pinto, Vandana A. Patil
Bees are essential as they are responsible for the pollination of one-third of the world’s food. Without bees, the availability of fresh produce would be significantly less and could also lead to the collapse of several ecosystems. This study proposes a system that uses computer vision to detect Varroa mite infestation levels in a beehive using object detection techniques and a beehive audio analysis system using Mel spectrograms and Mel-frequency cepstral coefficients (MFCCs) as input features to a deep learning model to discriminate between a healthy hive and a weak hive. For this experiment the object detection algorithms YOLOv8, YOLOv7, YOLOv5 and SSD, are compared based on their accuracy, speed, and compute requirements. A dataset consisting of over 10,000 ground-truth images of bees infected with varroa mites and healthy bees was used and the models achieved the highest precision of 0.962 for Varroa mite detection. For audio analysis, a custom dataset with over 2 hours of audio recordings from ‘‘strong’’ and ‘‘weak’’ beehives was used to train and evaluate a neural network that reached a maximum accuracy of 0.998.
{"title":"NeuralBee - A Beehive Health Monitoring System","authors":"Yashika N. Mahajan, Deepika Mehta, Joel Miranda, Ron Pinto, Vandana A. Patil","doi":"10.1109/CSCITA55725.2023.10104935","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104935","url":null,"abstract":"Bees are essential as they are responsible for the pollination of one-third of the world’s food. Without bees, the availability of fresh produce would be significantly less and could also lead to the collapse of several ecosystems. This study proposes a system that uses computer vision to detect Varroa mite infestation levels in a beehive using object detection techniques and a beehive audio analysis system using Mel spectrograms and Mel-frequency cepstral coefficients (MFCCs) as input features to a deep learning model to discriminate between a healthy hive and a weak hive. For this experiment the object detection algorithms YOLOv8, YOLOv7, YOLOv5 and SSD, are compared based on their accuracy, speed, and compute requirements. A dataset consisting of over 10,000 ground-truth images of bees infected with varroa mites and healthy bees was used and the models achieved the highest precision of 0.962 for Varroa mite detection. For audio analysis, a custom dataset with over 2 hours of audio recordings from ‘‘strong’’ and ‘‘weak’’ beehives was used to train and evaluate a neural network that reached a maximum accuracy of 0.998.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115753732","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 : 2023-03-31DOI: 10.1109/CSCITA55725.2023.10104852
Ekta Masrani, Dwarkesh Patel, Medhashakti Khatri, Esha Martis, Nidhi Gaur
In this era of new technologies with the ever growing need for reliable ecological energy supplies, monitoring and reducing the energy consumption of buildings becomes a very crucial concern. Improved healthcare institutions available in the city, more employment opportunities, high standards of living, along with increase in population, has led to rapid urbanization resulting in development of a huge number of buildings. Buildings have become one of the most important contributors to energy consumption, which are responsible for around one-third of energy that is consumed in cities. This makes it very important to monitor and analyze the energy usage by such territories in a meaningful manner to further save energy and even help in cutting down financial costs. The proposed system provides various features as a solution to conserve energy, monitor the power consumption and water usage along with real time monitoring. Smart living allows you to have greater control of your energy usage, all while automating things like adjusting devices based on weather conditions, turning on or off appliances based on occupancy of the room, etc. It provides insights into energy use that can help you become more energy efficient and mindful of ecological factors.
{"title":"Smart Living Solution to Optimize Building Systems for Efficient Energy Usage and Prediction","authors":"Ekta Masrani, Dwarkesh Patel, Medhashakti Khatri, Esha Martis, Nidhi Gaur","doi":"10.1109/CSCITA55725.2023.10104852","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104852","url":null,"abstract":"In this era of new technologies with the ever growing need for reliable ecological energy supplies, monitoring and reducing the energy consumption of buildings becomes a very crucial concern. Improved healthcare institutions available in the city, more employment opportunities, high standards of living, along with increase in population, has led to rapid urbanization resulting in development of a huge number of buildings. Buildings have become one of the most important contributors to energy consumption, which are responsible for around one-third of energy that is consumed in cities. This makes it very important to monitor and analyze the energy usage by such territories in a meaningful manner to further save energy and even help in cutting down financial costs. The proposed system provides various features as a solution to conserve energy, monitor the power consumption and water usage along with real time monitoring. Smart living allows you to have greater control of your energy usage, all while automating things like adjusting devices based on weather conditions, turning on or off appliances based on occupancy of the room, etc. It provides insights into energy use that can help you become more energy efficient and mindful of ecological factors.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124641375","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}
This paper presents the Exploratory Data Analysis on the climate data of the city of Mumbai. The climate variables are closely associated with each other. Exploratory Data Analysis helps to understand the data in a better way so that the predictions of any particular weather phenomenon are done properly. Random forest has been used to for prediction. Standardization and Normalization has been used and the results are shown. The validation techniques used are Mean Square Error, Root Mean Square Error and Mean Absolute Error.
{"title":"Implementation of Exploratory Data Analysis on Weather Data","authors":"Sahil Adivarekar, Shruti Nanwani, Nabanita Mandal, Tanuja Sarode","doi":"10.1109/CSCITA55725.2023.10104864","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104864","url":null,"abstract":"This paper presents the Exploratory Data Analysis on the climate data of the city of Mumbai. The climate variables are closely associated with each other. Exploratory Data Analysis helps to understand the data in a better way so that the predictions of any particular weather phenomenon are done properly. Random forest has been used to for prediction. Standardization and Normalization has been used and the results are shown. The validation techniques used are Mean Square Error, Root Mean Square Error and Mean Absolute Error.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125578271","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 : 2023-03-31DOI: 10.1109/CSCITA55725.2023.10104801
Syed Shadab Nayyer, J. Hozefa, M. Rahul, C. Mandhar
As an integral part of the Smart Grid (SG), transformers’ thermal profile (Accurate Top-oil Temperature (TOT) and Hot-spot Temperature (HST)) predictions are essential for maximizing transformer utilization and deciding on the best remedial action in the case of transformer failures. However, for these predictions and estimates, the classical mathematical models of TOT lead to a mismatch between the estimated and the actual value because of assumptions, simplifications, and lack of sufficient data points. The online monitoring of transformers’ rate of ageing, capability to overload, and diagnosis are restricted by uncertainties in measurements and classical mathematical models. Therefore, a Machine Learning (ML) perspective is explored by using the Gaussian Process Regression (GPR)based TOT model to incorporate these model uncertainty and measurement noise. The transformer LoL (Loss-of-Life) and HST with uncertainties are evaluated using existing thermal (thermal-electrical-based) and GPR models.To authenticate the effectiveness of the proposed approach, MATLAB-based virtual data and data from an in-service transformer are utilized.
{"title":"A Machine Learning Perspective in an Effective Monitoring of Thermal Performance of Transformer","authors":"Syed Shadab Nayyer, J. Hozefa, M. Rahul, C. Mandhar","doi":"10.1109/CSCITA55725.2023.10104801","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104801","url":null,"abstract":"As an integral part of the Smart Grid (SG), transformers’ thermal profile (Accurate Top-oil Temperature (TOT) and Hot-spot Temperature (HST)) predictions are essential for maximizing transformer utilization and deciding on the best remedial action in the case of transformer failures. However, for these predictions and estimates, the classical mathematical models of TOT lead to a mismatch between the estimated and the actual value because of assumptions, simplifications, and lack of sufficient data points. The online monitoring of transformers’ rate of ageing, capability to overload, and diagnosis are restricted by uncertainties in measurements and classical mathematical models. Therefore, a Machine Learning (ML) perspective is explored by using the Gaussian Process Regression (GPR)based TOT model to incorporate these model uncertainty and measurement noise. The transformer LoL (Loss-of-Life) and HST with uncertainties are evaluated using existing thermal (thermal-electrical-based) and GPR models.To authenticate the effectiveness of the proposed approach, MATLAB-based virtual data and data from an in-service transformer are utilized.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116427566","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 : 2023-03-31DOI: 10.1109/CSCITA55725.2023.10104798
Varsha Nagpurkar, Neha Pattankar, Tripti Nayak, Allan D’Souza, Nipun Henriques
The guitar is one of the most popular and widely used instruments. The guitar’s popularity makes it an obvious choice for many who wish to learn an instrument. And due to its popularity, there are many materials available to learn with. Learning guitar can be a fun and exciting experience for a budding musician but unfortunately with the resources available today learning an instrument without the aid of a professional musician can be challenging and tricky. The available systems do not completely help the guitarists to identify the chords. An alternative to taking music classes is to follow online courses or applications to learn the guitar but these methods come with their own set of drawbacks. Hence there is a need for a system that will help the guitarists with the same. This is where the GuitarGuru system comes in. Our main aim is to combine the best elements of various methods of learning the guitar into one ultimate application while leaving out the failures and drawbacks that come with these methods. We want to make it easier for budding musicians as well as experienced guitarists to learn, analyze and track their performance to make faster progress while learning this sophisticated and beautiful instrument. We plan to make, the GuitarGuru system to be a one-stop shop for all budding musicians that want to make quick progress on learning and mastering the guitar most efficiently without the aid of an actual musical instructor or an online course that doesn’t provide any live feedback. When words fail, music speaks.
{"title":"GuitarGuru: A Realtime Guitar Chords Detection System","authors":"Varsha Nagpurkar, Neha Pattankar, Tripti Nayak, Allan D’Souza, Nipun Henriques","doi":"10.1109/CSCITA55725.2023.10104798","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104798","url":null,"abstract":"The guitar is one of the most popular and widely used instruments. The guitar’s popularity makes it an obvious choice for many who wish to learn an instrument. And due to its popularity, there are many materials available to learn with. Learning guitar can be a fun and exciting experience for a budding musician but unfortunately with the resources available today learning an instrument without the aid of a professional musician can be challenging and tricky. The available systems do not completely help the guitarists to identify the chords. An alternative to taking music classes is to follow online courses or applications to learn the guitar but these methods come with their own set of drawbacks. Hence there is a need for a system that will help the guitarists with the same. This is where the GuitarGuru system comes in. Our main aim is to combine the best elements of various methods of learning the guitar into one ultimate application while leaving out the failures and drawbacks that come with these methods. We want to make it easier for budding musicians as well as experienced guitarists to learn, analyze and track their performance to make faster progress while learning this sophisticated and beautiful instrument. We plan to make, the GuitarGuru system to be a one-stop shop for all budding musicians that want to make quick progress on learning and mastering the guitar most efficiently without the aid of an actual musical instructor or an online course that doesn’t provide any live feedback. When words fail, music speaks.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127392620","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}
The growing deployment of computer vision in industrial processes significantly contributes to strengthening the manufacturing sector in terms of productivity and safety of the workers. Manufacturing workers are often working in hazardous environments handling different dangerous equipment putting their life on the line every day. Work accidents are reminders for which companies must make efforts to reduce its occurrence and their adverse impact on the lives of workers. In case of an active accident, the computer vision system can send an alert to managers and staff about location and the intensity of the accident so the production process can be halted in that specific area and proactively ensure the safety of employees. The deployment of computer vision-powered systems operating 24/7 accelerates manufacturing cycles increasing productivity. Computer vision applications have a major role in product and component assembly in the manufacturing space. They also aid in defect detection with increased accuracy and precision. Manufacturers conduct constant monitoring of equipment used for production manually. To improve the safety and working conditions for the workers and increase productivity in the manufacturing sector, this project aims to implement computer vision as a monitoring method to assure the security measures are followed and analyze the productivity in the organization. The object recognition algorithm, YOLOv3, is trained and tested using data that is gathered from industrial facilities in the form of images.
{"title":"Computer Vision for Industrial Safety and Productivity","authors":"Shreya Shetye, Srishti Shetty, Srushti Shinde, Chaithanya Madhu, Amrita Mathur","doi":"10.1109/CSCITA55725.2023.10104764","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104764","url":null,"abstract":"The growing deployment of computer vision in industrial processes significantly contributes to strengthening the manufacturing sector in terms of productivity and safety of the workers. Manufacturing workers are often working in hazardous environments handling different dangerous equipment putting their life on the line every day. Work accidents are reminders for which companies must make efforts to reduce its occurrence and their adverse impact on the lives of workers. In case of an active accident, the computer vision system can send an alert to managers and staff about location and the intensity of the accident so the production process can be halted in that specific area and proactively ensure the safety of employees. The deployment of computer vision-powered systems operating 24/7 accelerates manufacturing cycles increasing productivity. Computer vision applications have a major role in product and component assembly in the manufacturing space. They also aid in defect detection with increased accuracy and precision. Manufacturers conduct constant monitoring of equipment used for production manually. To improve the safety and working conditions for the workers and increase productivity in the manufacturing sector, this project aims to implement computer vision as a monitoring method to assure the security measures are followed and analyze the productivity in the organization. The object recognition algorithm, YOLOv3, is trained and tested using data that is gathered from industrial facilities in the form of images.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134569691","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}
A digital transformation is being undergone by the music industry, with key drivers of change such as streaming services and blockchain technology emerging. The potential of web3 and blockchain technology to disrupt the traditional music industry business model and create new opportunities for artists and creators is examined in this study. A case study of a web3-based music player and marketplace that allows audio content to be shared and monetized in the form of non-fungible tokens (NFTs) is presented. The potential of NFTs to revolutionize the way music is distributed, consumed, and valued is explored through analysis of the platform’s features and user feedback. The findings suggest that artists can be empowered and given greater control over their creative works, while also providing consumers with a more immersive and personalized listening experience through web3 and blockchain technology. The growing body of research on the intersection of music and blockchain is contributed to by this study, and has implications for the future of the music industry.
{"title":"Web-3 Music Player on Blockchain","authors":"Akshay Agrawal, Aakash Mahesh Gujar, Ayush Chovatiya, Het Gopal Sheth, Tarun Singh","doi":"10.1109/CSCITA55725.2023.10105088","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10105088","url":null,"abstract":"A digital transformation is being undergone by the music industry, with key drivers of change such as streaming services and blockchain technology emerging. The potential of web3 and blockchain technology to disrupt the traditional music industry business model and create new opportunities for artists and creators is examined in this study. A case study of a web3-based music player and marketplace that allows audio content to be shared and monetized in the form of non-fungible tokens (NFTs) is presented. The potential of NFTs to revolutionize the way music is distributed, consumed, and valued is explored through analysis of the platform’s features and user feedback. The findings suggest that artists can be empowered and given greater control over their creative works, while also providing consumers with a more immersive and personalized listening experience through web3 and blockchain technology. The growing body of research on the intersection of music and blockchain is contributed to by this study, and has implications for the future of the music industry.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132736532","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 : 2023-03-31DOI: 10.1109/CSCITA55725.2023.10104807
S. Thakur, S. Chaudhari, Bharti Joshi
Malicious users can steal user credentials by launching various attacks. In most of such scenarios, honeywords are proven to be the best way to detect failure and unauthorized access. However, there are some flaws in honeyword based malicious user detection systems such as lack of integrity handling and robust confidentiality mechanism. We have proposed hybrid approach for honeyword generation using chaffing by tweaking digit and take a tail method. We also proposed modified BLAST algorithm to detect malicious users. If a fraudulent user is detected, an email is sent to the administrator. Additionally, QR Code is being used to strengthen overall security of login process. The proposed approach reduces risk of data theft from users. The hybrid model is performing better compared with all other honeyword generation techniques. In addition, user password hashes are stored in the database, reducing the risk of password cracking.
{"title":"Malicious User Detection using Honeywords","authors":"S. Thakur, S. Chaudhari, Bharti Joshi","doi":"10.1109/CSCITA55725.2023.10104807","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104807","url":null,"abstract":"Malicious users can steal user credentials by launching various attacks. In most of such scenarios, honeywords are proven to be the best way to detect failure and unauthorized access. However, there are some flaws in honeyword based malicious user detection systems such as lack of integrity handling and robust confidentiality mechanism. We have proposed hybrid approach for honeyword generation using chaffing by tweaking digit and take a tail method. We also proposed modified BLAST algorithm to detect malicious users. If a fraudulent user is detected, an email is sent to the administrator. Additionally, QR Code is being used to strengthen overall security of login process. The proposed approach reduces risk of data theft from users. The hybrid model is performing better compared with all other honeyword generation techniques. In addition, user password hashes are stored in the database, reducing the risk of password cracking.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122672941","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 : 2023-03-31DOI: 10.1109/CSCITA55725.2023.10104824
Asit Shigwan, Alden Aguiar, Derrick D’Abreo, Shree Jaswal
The act of bargaining between two parties over the allocation of a resource whose supply is constrained by the laws of nature is known as negotiation. One goal of the digital revolution as we move closer to the digital era has been to replicate, simulate, and automate processes that need higher level human cognition, such as negotiation. The introduction of e-negotiation is the main force behind the automation of negotiation. Our goal is to present a P2P negotiating framework in this study that may be broadly applied in a range of scenarios and domains. Our proposed, domain-specific solution is primarily driven by fuzzy controllers.
{"title":"P2P Negotiation Framework for trading Carbon Credits","authors":"Asit Shigwan, Alden Aguiar, Derrick D’Abreo, Shree Jaswal","doi":"10.1109/CSCITA55725.2023.10104824","DOIUrl":"https://doi.org/10.1109/CSCITA55725.2023.10104824","url":null,"abstract":"The act of bargaining between two parties over the allocation of a resource whose supply is constrained by the laws of nature is known as negotiation. One goal of the digital revolution as we move closer to the digital era has been to replicate, simulate, and automate processes that need higher level human cognition, such as negotiation. The introduction of e-negotiation is the main force behind the automation of negotiation. Our goal is to present a P2P negotiating framework in this study that may be broadly applied in a range of scenarios and domains. Our proposed, domain-specific solution is primarily driven by fuzzy controllers.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125662761","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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