Instructions
Prepare a comparison study with various continuous authentication approaches (which supports one factor or more than one factors). You are required to search various papers and websites of these approaches and find out their unique features and write at least eight(8) continuous authentication approach mentioning their features, uniqueness, how the study conducted, what is the accuracy of this approach. Regarding these approaches, please consider recent two/three years publications (2017-2020) only. You are required to write a paragraph mentioning the above criteria. It is possible to choose some adaptive authentication techniques which published recent years that support continuous authentication.
Then based on your research, need to prepare a comparison table with these eight approaches and mention your criteria to compare these approaches and why you choose these criteria. You are required to provide a reference for each of the chosen Continuous authentication approach
Student’s Name:
Institution:
Continuous Authentication Approaches
Continuous authentication involves verification methods directed at providing identity confirmation and cybersecurity protection continuously, thus ensuring improved security and monitoring. The continuous authentication approach constantly measures the probability that individual users are who they claim to be. The user is continuously authenticated through the session, thus assuring that the system and account are used by the right user (Li et al., 2018). Continuous authentication focuses on achieving smart, secure identity verification without interrupting workflow; thus, it incorporates different behavioral patterns, machine learning, or biometric. Consequently, different continuous approaches have their differences or similarities defined by features, uniqueness, and approach accuracy, how the study is conducted. The different continuous authentication approaches include password-based, multi-factor based, certificate-based, biometric, token-based authentication, voice-based machine learning-based, and behavioral pattern-based authentication.
Different continuous authentication approaches
Password-based authentication
Password-based authentication remains the most common authentication that requires the user to key in a string of letters, special characters, and numbers to access a system. In this regard, every user must develop their password that is registered with the system to use it in accessing the system (Ayeswarya and Norman, 2019). The uniqueness of password-based authentication is that the user needs to create strong passwords that incorporate all possible options to increase their safety levels. The approach to accuracy is the verification of the system entered password and password data held in the data center of the system. The conduct of the study, in this case, requires the users to test the system by entering different passwords from the genuine password to evaluate and observe the reaction of the system.
Multi-factor authentication
The multi-factor authentication approach adopts two or more ways to identify and ascertain the user as one of its features. The uniqueness of multi-factor authentication is that a confirmation code is generated from the user’s facial recognition, fingerprint, captcha, or smartphones to ascertain the user’s identity (Ayeswarya and Norman, 2019). The accuracy approach in the authentication approach is achieved through the use of adding multiple layers of security. The authentication approach study takes the Assessment of the link and capability of the two or more independent ways to identify the user.
Certificate-based authentication
The certificate-based authentication approach uses the digital certificates feature to identify the users, devices, and machines. The certificate-based authentication’s uniqueness is based on an electronically generated document as a certificate to enhance the user access to the system (Shahzad and Singh, 2017). The authentication approach to accuracy is that the generated certificate contains a user’s digital identity, including a public key and the digital signature of a certification authority. The server verifies the digital certificate’s identity of the user. The study’s conduct on the authentication approach takes the verification of different digital signature and certificate authority.
Biometric authentication
The features of biometric authentication are that it relies on an individual’s biological traits to allow the user access into a system. The uniqueness of biometric authentication is the use of a person’s unique biological features to identify and certify their identity before they access the system. Different biometric authentication methods include facial recognition, fingerprint scanners, voice identification, and eye scanners (Shahzad and Singh, 2017). The accuracy approaches adopted the user biological characteristics to the authorized features saved in the database. The study’s conduct takes the testing of the different biometric authentication technology to evaluate their effectiveness in accessing a system based on authorized features contained in the database.
Token-based authentication
The token-based authentication approach uses the features of one entering their credentials and receiving a unique encrypted string of random characters to enhance their access to the system. The authentication approach’s uniqueness arises from the generation of a unique encrypted character to access the system (Ashibani, Kauling, and Mahmoud, 2019). The accuracy approach adopted is the use of tokens that proves that one has access permission. Token-based authentication is the testing of tokens or the credentials on multiple frameworks to evaluate their effectiveness.
Machine learning-based authentication
The machine learning-based authentication uses the adaptive authentication feature to identify and certify the user before accessing the system. The authentication approach’s uniqueness is that it selects the right authentication factors to use through the Assessment of the user tendencies and risk profile (Ashibani, Kauling, and Mahmoud, 2019). The accuracy approach on the machine learning authentication approach identifies the associated risk levels and presents the relevant levels of authentication in real-world scenarios. The conduct of the study of the authentication is based on the observation of the changes in the adaptive nature of the authentication approach.
Behavioral pattern-based authentication
Behavioral authentication uses the features of the user’s behavior patterns when they interact with a device such as a smartphone, computer, or tablet. The authentication approach’s uniqueness is that it uses the unique patterns of behavior regularly exhibited by the user in identifying the before they use the system (Chuang et al., 2018). The accuracy approach adopted is the Assessment of the finer details exhibited by the user, such as finger pressure on the keypad. The conduct of the study, in this case, takes the Assessment of the system to identify the behavioral patterns among the people and identify them with such patterns.
Comparison Table
Types of authentications Features Uniqueness Accuracy approach Conduct of study
Pass word based authentication Requires the user to key in a string of letters, special characters and numbers to have an access to a system User needs to create strong passwords that incorporate all possible options to increase their safety levels Verification of the system entered password and password data held in the data center of the system Requires the users testing the system by entering different password from the genuine password to evaluate and observe the reaction of the system
Multi-factor authentication Takes the adoption of two or more ways to identify and ascertain the user Selects the right authentication factors to use in through the Assessment of the user tendencies and risk profile Use of additing multiple layers of security the Assessment of the link and capability of the two or more independent ways to identify the user
Certificate based authentication Digital certificate It has electronically generated certificate Verification of digital identity verification of different digital signature and certificate authority to ascertain the identity
Biometric authentication Uses biological traits to access the system Uses unique biological features on a person to identify and certify their identity comparison of the user biological characteristics to the authorized features saved in the database Testing of the different biometric authentication technology to evaluate their effectiveness in accessing a system based on authorized features contained in the database
Token based authentication Uses credential to initiate the access into the system Generation of unique encrypted string to certify access into the system Use of tokens that proves that one has access permission Testing of tokens or the credentials on multiple frameworks to evaluate their effectiveness
Machine learning based authentication Use of the adaptive authentication Selection of the right authentication factors to use in through the Assessment of the user tendencies and risk profile identification of the associated risk levels and presenting the relevant levels of authentication in real world scenarios Observation of the changes in the adaptive nature of the authentication approach
Behavioral pattern based authentication Uses the feature of behavior pattern exhibited by the user when they interact with a device Uses the unique patterns of behavior regularly exhibited by the user in identifying the before they use the system Assessment of the finer and unique details exhibited by the user Assessment of the system to identify the behavioral patterns among the people and identify them with such patterns
References
Ashibani, Y., Kauling, D., & Mahmoud, Q. H. (2019). Design and implementation of a contextual-based continuous authentication framework for smart homes. Applied System Innovation, 2(1), 4.
Li, Y., Hu, H., & Zhou, G. (2018). Using data augmentation in continuous authentication on smartphones. IEEE Internet of Things Journal, 6(1), 628-640.
Ayeswarya, S., & Norman, J. (2019). A survey on different continuous authentication systems. International Journal of Biometrics, 11(1), 67-99.
Shahzad, M., & Singh, M. P. (2017). Continuous authentication and authorization for the internet of things. IEEE Internet Computing, 21(2), 86-90.
Chuang, Y. H., Lo, N. W., Yang, C. Y., & Tang, S. W. (2018). A lightweight continuous authentication protocol for the Internet of Things. Sensors, 18(4), 1104.
