Pub Date : 1900-01-01DOI: 10.4018/978-1-5225-7724-9.CH001
G. Jagadamaba, B. Babu
In the internet era, the online examination has become an integral component of online processing and online learning. Student assessment in the online education system is submitted remotely without any face-to-face recognition and interaction. However, student authentication is the significant challenge in online education and examination. This chapter aims to examine various authentication systems, potential threats, and solutions to student authentication in the online examinations and learning. In this chapter, a keystroke-based authentication system is discussed for online examinations. Keystroke-based authentication does not require any additional investments as compared to the other existing authentication approaches such as face recognition, iris recognition, fingerprint, and so on.
{"title":"Keystroke Dynamics in E-Learning and Online Exams","authors":"G. Jagadamaba, B. Babu","doi":"10.4018/978-1-5225-7724-9.CH001","DOIUrl":"https://doi.org/10.4018/978-1-5225-7724-9.CH001","url":null,"abstract":"In the internet era, the online examination has become an integral component of online processing and online learning. Student assessment in the online education system is submitted remotely without any face-to-face recognition and interaction. However, student authentication is the significant challenge in online education and examination. This chapter aims to examine various authentication systems, potential threats, and solutions to student authentication in the online examinations and learning. In this chapter, a keystroke-based authentication system is discussed for online examinations. Keystroke-based authentication does not require any additional investments as compared to the other existing authentication approaches such as face recognition, iris recognition, fingerprint, and so on.","PeriodicalId":369109,"journal":{"name":"Biometric Authentication in Online Learning Environments","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133804885","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 : 1900-01-01DOI: 10.4018/978-1-5225-7724-9.CH003
Aparna Vegendla, G. Sindre
E-exams have different cheating opportunities and mitigations than paper exams, and remote exams also have different cheating risks that on-site exams. It is important to understand these differences in risk and possible mitigations against them. Authenticating the candidate may be a bigger challenge for remote exams, and biometric authentication has emerged as a key solution. This chapter delivers a categorization of different types of high-stakes assessments, different ways of cheating, and what types of cheating are most relevant for what types of assessments. It further presents an analysis of which threats biometric authentication can be effective against and what types of threats biometric authentication is less effective against. Insecure aspects of various biometric authentication approaches also indicate that biometric authentication and surveillance should be combined with other types of approaches (e.g., how questions are asked, timing of the exam) to mitigate cheating.
{"title":"Mitigation of Cheating in Online Exams","authors":"Aparna Vegendla, G. Sindre","doi":"10.4018/978-1-5225-7724-9.CH003","DOIUrl":"https://doi.org/10.4018/978-1-5225-7724-9.CH003","url":null,"abstract":"E-exams have different cheating opportunities and mitigations than paper exams, and remote exams also have different cheating risks that on-site exams. It is important to understand these differences in risk and possible mitigations against them. Authenticating the candidate may be a bigger challenge for remote exams, and biometric authentication has emerged as a key solution. This chapter delivers a categorization of different types of high-stakes assessments, different ways of cheating, and what types of cheating are most relevant for what types of assessments. It further presents an analysis of which threats biometric authentication can be effective against and what types of threats biometric authentication is less effective against. Insecure aspects of various biometric authentication approaches also indicate that biometric authentication and surveillance should be combined with other types of approaches (e.g., how questions are asked, timing of the exam) to mitigate cheating.","PeriodicalId":369109,"journal":{"name":"Biometric Authentication in Online Learning Environments","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114777279","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 : 1900-01-01DOI: 10.4018/978-1-5225-7724-9.CH010
R. Kashyap
The primary goal of this chapter is to answer online exam frameworks by utilizing face acknowledgment to verify students for going to an online exam. A strategy in light of the utilization of neural systems to validate individuals' computerized unique mark framework for e-learning is present. This chapter centers around breaking down and contrasting the distinctive facial verification frameworks to confirm the understudies when they utilize e-learning stages, itemizing the expenses and the highlights of each structure recorded. Biometrics is a sensible verification used as a type of distinguishing proof and access control. It is additionally used to distinguish people in bunches that are under observation. Biometric identifiers are then particular quantifiable qualities used to mark and portray people. Biometric authenticators are as often as possible named as conduct and additionally physiological attributes. Physiological qualities are identified with the state of the body. In this chapter, the essential focus is on the distinctive biometrics and their applications.
{"title":"Biometric Authentication Techniques and E-Learning","authors":"R. Kashyap","doi":"10.4018/978-1-5225-7724-9.CH010","DOIUrl":"https://doi.org/10.4018/978-1-5225-7724-9.CH010","url":null,"abstract":"The primary goal of this chapter is to answer online exam frameworks by utilizing face acknowledgment to verify students for going to an online exam. A strategy in light of the utilization of neural systems to validate individuals' computerized unique mark framework for e-learning is present. This chapter centers around breaking down and contrasting the distinctive facial verification frameworks to confirm the understudies when they utilize e-learning stages, itemizing the expenses and the highlights of each structure recorded. Biometrics is a sensible verification used as a type of distinguishing proof and access control. It is additionally used to distinguish people in bunches that are under observation. Biometric identifiers are then particular quantifiable qualities used to mark and portray people. Biometric authenticators are as often as possible named as conduct and additionally physiological attributes. Physiological qualities are identified with the state of the body. In this chapter, the essential focus is on the distinctive biometrics and their applications.","PeriodicalId":369109,"journal":{"name":"Biometric Authentication in Online Learning Environments","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123268059","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 : 1900-01-01DOI: 10.4018/978-1-5225-7724-9.CH008
A. V. S. Kumar, Menal Rathi
Online learning has entirely transformed the way of learning by the students. Online tests and quizzes play an important role in online learning, which provides accurate results to the instructor. But, the learners use different methods to cheat during online exams such as opening a browser to search for the answer or a document in the local drive, etc. They are not authenticated once they login and progress to attend the online exams. Different techniques are used in authenticating the students taking up the online exams such as audio or video surveillance systems, fingerprint, or iris recognition, etc. Keystroke dynamics-based authentication (KDA) method, a behavioral biometric-based authentication model has gained focus in authenticating the users. This chapter proposes the usage of KDA as a solution to user authentication in online exams and presents a detailed review on the processes of KDA, the factors that affect the performance of KDA, their applications in different domains, and a few keystroke dynamics-based datasets to authenticate the users during online exams.
{"title":"Keystroke Dynamics","authors":"A. V. S. Kumar, Menal Rathi","doi":"10.4018/978-1-5225-7724-9.CH008","DOIUrl":"https://doi.org/10.4018/978-1-5225-7724-9.CH008","url":null,"abstract":"Online learning has entirely transformed the way of learning by the students. Online tests and quizzes play an important role in online learning, which provides accurate results to the instructor. But, the learners use different methods to cheat during online exams such as opening a browser to search for the answer or a document in the local drive, etc. They are not authenticated once they login and progress to attend the online exams. Different techniques are used in authenticating the students taking up the online exams such as audio or video surveillance systems, fingerprint, or iris recognition, etc. Keystroke dynamics-based authentication (KDA) method, a behavioral biometric-based authentication model has gained focus in authenticating the users. This chapter proposes the usage of KDA as a solution to user authentication in online exams and presents a detailed review on the processes of KDA, the factors that affect the performance of KDA, their applications in different domains, and a few keystroke dynamics-based datasets to authenticate the users during online exams.","PeriodicalId":369109,"journal":{"name":"Biometric Authentication in Online Learning Environments","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130379647","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 : 1900-01-01DOI: 10.4018/978-1-5225-7724-9.CH004
M. Goyal, R. Krishnamurthi
This chapter explores a novel learning content management system. This chapter presents a novel system based on integration of voice authentication, face recognition technique, and signature of a person to recognize in e-learning system. Voice-based authentication, face recognition, and signature of a person is most widely used to authenticate human identity. The main concern in an e-learning system is to demotivate unknown users from taking the examination in place of the learner. Different techniques have been introduced to stop this fraud if any unknown person wants to imitate person's identity. In order to avoid the fraudulent handling of e-learning systems, the authentication based on voice recognition is discussed as one of the efficient techniques in literature.
{"title":"An Enhanced Integration of Voice-, Face-, and Signature-Based Authentication System for Learning Content Management System","authors":"M. Goyal, R. Krishnamurthi","doi":"10.4018/978-1-5225-7724-9.CH004","DOIUrl":"https://doi.org/10.4018/978-1-5225-7724-9.CH004","url":null,"abstract":"This chapter explores a novel learning content management system. This chapter presents a novel system based on integration of voice authentication, face recognition technique, and signature of a person to recognize in e-learning system. Voice-based authentication, face recognition, and signature of a person is most widely used to authenticate human identity. The main concern in an e-learning system is to demotivate unknown users from taking the examination in place of the learner. Different techniques have been introduced to stop this fraud if any unknown person wants to imitate person's identity. In order to avoid the fraudulent handling of e-learning systems, the authentication based on voice recognition is discussed as one of the efficient techniques in literature.","PeriodicalId":369109,"journal":{"name":"Biometric Authentication in Online Learning Environments","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132842232","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 : 1900-01-01DOI: 10.4018/978-1-5225-7724-9.CH006
S. Sivakumar
The number of users using the internet has drastically increased. Due to the large number of online users, demand has increased in various fields like social networks, knowledge sharing, commerce, etc. to protect the user's private data as well as control access. Unfortunately, the need for security and authentication for individual data also increased. In an attempt to confront the new risks unveiled by the networking revolution over the recent years, we need an efficient means for automatically recognizing the identity of individuals. Biometric authentication provides an improved level of security and paves the way to the future. Further, biometric authentication systems are classified as physiological biometric and behavioral biometric technologies. Further, the author provides ideas on research challenges and the future of authentication systems.
{"title":"Biometric Authentication Techniques and Its Future","authors":"S. Sivakumar","doi":"10.4018/978-1-5225-7724-9.CH006","DOIUrl":"https://doi.org/10.4018/978-1-5225-7724-9.CH006","url":null,"abstract":"The number of users using the internet has drastically increased. Due to the large number of online users, demand has increased in various fields like social networks, knowledge sharing, commerce, etc. to protect the user's private data as well as control access. Unfortunately, the need for security and authentication for individual data also increased. In an attempt to confront the new risks unveiled by the networking revolution over the recent years, we need an efficient means for automatically recognizing the identity of individuals. Biometric authentication provides an improved level of security and paves the way to the future. Further, biometric authentication systems are classified as physiological biometric and behavioral biometric technologies. Further, the author provides ideas on research challenges and the future of authentication systems.","PeriodicalId":369109,"journal":{"name":"Biometric Authentication in Online Learning Environments","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123390083","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 : 1900-01-01DOI: 10.4018/978-1-5225-7724-9.CH002
R. Sundararajan
Enhanced authentication is the need of the hour in today's technology. Commonly used login and password are not enough as they may be guessed by imposters. Most of the websites adopt the traditional authentication as login and password. But they don't verify whether the same person is accessing their information continuously in the current session. This is of great concern in distance-based e-learning systems. The institutes offering the e-courses must verify whether it is the same student who enrolled, is accessing their materials, doing the assignments themselves, and completing the examination without any cheating. In this case, one of the techniques, behavioral biometrics-keystroke dynamics, plays a very important role. Along with other authentication methods, keystroke dynamics can be combined to provide a more secured system for the students in e-learning environments. In this chapter, the basics of keystroke dynamics and some of the applications that use them are discussed.
{"title":"Keystroke Dynamics in E-Learning","authors":"R. Sundararajan","doi":"10.4018/978-1-5225-7724-9.CH002","DOIUrl":"https://doi.org/10.4018/978-1-5225-7724-9.CH002","url":null,"abstract":"Enhanced authentication is the need of the hour in today's technology. Commonly used login and password are not enough as they may be guessed by imposters. Most of the websites adopt the traditional authentication as login and password. But they don't verify whether the same person is accessing their information continuously in the current session. This is of great concern in distance-based e-learning systems. The institutes offering the e-courses must verify whether it is the same student who enrolled, is accessing their materials, doing the assignments themselves, and completing the examination without any cheating. In this case, one of the techniques, behavioral biometrics-keystroke dynamics, plays a very important role. Along with other authentication methods, keystroke dynamics can be combined to provide a more secured system for the students in e-learning environments. In this chapter, the basics of keystroke dynamics and some of the applications that use them are discussed.","PeriodicalId":369109,"journal":{"name":"Biometric Authentication in Online Learning Environments","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132001044","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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