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1. Iris Print Attack Detection using Eye Movement Signals

   https://doi.org/10.1145/3517031.3532521  

   Raju, Mehedi Hasan; Lohr, Dillon J; Komogortsev, Oleg (January 2022, 2022 Symposium on Eye Tracking Research and Applications)

   Iris-based biometric authentication is a wide-spread biometric modality due to its accuracy, among other benefits. Improving the resistance of iris biometrics to spoofing attacks is an important research topic. Eye tracking and iris recognition devices have similar hardware that consists of a source of infra-red light and an image sensor. This similarity potentially enables eye tracking algorithms to run on iris-driven biometrics systems. The present work advances the state-of-the-art of detecting iris print attacks, wherein an imposter presents a printout of an authentic user’s iris to a biometrics system. The detection of iris print attacks is accomplished via analysis of the captured eye movement signal with a deep learning model. Results indicate better performance of the selected approach than the previous state-of-the-art. 

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2. Increasing Security of WebIDs Through Biometrics

   https://doi.org/10.1109/southeastcon44009.2020.9368274  

   Gwyn, Tony; Martin, Taylor; Esterline, Albert (March 2020, 2020 IEEE SoutheastCon)

   null (Ed.)

   We are creating a streamlined way to adapt WebIDs [1], and biometrics [2] to the cyber world. This involves building a user authentication system that enables quick, fast and secure access. It is understood that compared to traditional username and password user authentication, WebIDs are designed to provide such services. Nevertheless, if an intruder either has direct access to the user's computer or somehow gets the unique certificate of the user, important information can be stolen with solely the use of WebIDs. Since biometric data (e.g. fingerprints, iris scanning, etc.) is unique and not easily duplicated, this possibility can be avoided by including biometrics in the authentication process. We also include an enrollment protocol that checks whether a user has a WebID while trying to access a server. If they do, we allow the user access to the server, and if they do not, by accessing their own server, we register the user for a WebID with their permission. Implementing these features in the WebID protocol will greatly enhance user authentication safety. 

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3. Evaluation of Local Binary Pattern Algorithm for User Authentication with Face Biometric

   https://doi.org/10.1109/icmla51294.2020.00170  

   Gwyn, Tony; Atay, Mustafa; Kaushik, Roy; Esterline, Albert (December 2020, 19th IEEE International Conference on Machine Learning and Applications (ICMLA))

   null (Ed.)

   In the ever-changing world of computer security and user authentication, the username/password standard is becoming increasingly outdated. Using the same username and password across multiple accounts and websites leaves a user open to vulnerabilities, and the need to remember multiple usernames and passwords feels very unnecessary in the current digital age. Authentication methods of the future need to be reliable and fast, while maintaining the ability to provide secure access. Augmenting traditional username-password standard with face biometric is proposed in the literature to enhance the user authentication. However, this technique still needs an extensive evaluation study to show how reliable and effective it will be under different settings. Local Binary Pattern (LBP) is a discrete yet powerful texture classification scheme, which works particularly well with image classification for facial recognition. The system proposed here strives to examine and test various LBP configurations to determine their image classification accuracy. The most favorable configurations of LBP should be examined as a potential way to augment the current username and password standard by increasing their security with facial biometrics. 

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4. A Systematic Survey of Multi-Factor Authentication for Cloud Infrastructure

   https://doi.org/10.3390/fi15040146  

   Otta, Soumya Prakash; Panda, Subhrakanta; Gupta, Maanak; Hota, Chittaranjan (April 2023, Future Internet)

   The unauthorized usage of various services and resources in cloud computing is something that must be protected against. Authentication and access control are the most significant concerns in cloud computing. Several researchers in this field suggest numerous approaches to enhance cloud authentication towards robustness. User names and associated passwords have been a common practice for long as Single Factor Authentication. However, advancements in the speed of computing and the usage of simple methods, starting from the Brute Force technique to the implementation of advanced and efficient crytographic algorithms, have posed several threats and vulnerabilities for authentication systems, leading to the degradation of their effectiveness. Multi-factor authentication has emerged as a robust means of securing the cloud using simultaneous and multiple means of authentication factors. This employs multiple levels of cascaded authentication checks. This paper covers an extensive and systematic survey of various factors towards their adoption and suitability for authentication for multi-factor authentication mechanisms. The inference drawn from the survey is in terms of arriving at a unique authentication factor that does not require any additional, specialized hardware or software for multi-factor authentication. Such authentication also uses the distinct biometric characteristics of the concerned user in the process. This arrangement augments the secured and robust user authentication process. The mechanism is also assessed as an effective means against impersonation attacks. 

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5. Mouse Dynamics Behavioral Biometrics: A Survey

   https://doi.org/10.1145/3640311  

   Khan, Simon; Devlen, Charles; Manno, Michael; Hou, Daqing (June 2024, ACM Computing Surveys)

   Utilization of the Internet in our everyday lives has made us vulnerable in terms of privacy and security of our data and systems. Therefore, there is a pressing need to protect our data and systems by improving authentication mechanisms, which are expected to be low cost, unobtrusive, and ideally ubiquitous in nature. Behavioral biometric modalities such as mouse dynamics (mouse behaviors on a graphical user interface (GUI)) and widget interactions (another modality closely related to mouse dynamics that also considers the target (widget) of a GUI interaction, such as links, buttons, and combo-boxes) can bolster the security of existing authentication systems because of their ability to distinguish individuals based on their unique features. As a result, it can be difficult for an imposter to impersonate these behavioral biometrics, making them suitable for authentication. In this article, we survey the literature on mouse dynamics and widget interactions dated from 1897 to 2023. We begin our survey with an account of the psychological perspectives on behavioral biometrics. We then analyze the literature along the following dimensions: tasks and experimental settings for data collection, taxonomy of raw attributes, feature extractions and mathematical definitions, publicly available datasets, algorithms (statistical, machine learning, and deep learning), data fusion, performance, and limitations. We end the paper with presenting challenges and promising research opportunities. 

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