Evaluating current authentication methods: Prediction of a more suitable authentication approach for public interaction

The trend in information technology is towards achieving ubiquitous service rendering where barriers (geographical, time) in getting information related services will be eliminated. A good example of this is the ATM machines used by banks for public banking services, the likes in other sectors are currently on the way.This paper explores the user’s perception on the current identity authentication (Token-based and Knowledgebased) with a view to predict a more secured authentication for authentication in public places.A survey study is conducted so as to justify the claims of the previous authors on the need to migrate from the conventional knowledge-based and tokenbased authentication methods to a more secured biometric authentication approach which makes impossible user’s impersonation, and thus minimizing fraud, particularly in business transactions.Also, biometrical identification was also reviewed with respect to the all known biometric identifiers where human iris data was revealed to be the best human trait that can be used for identification/authentication purposes in public zone

Strengthening e-banking security using keystroke dynamics

This paper investigates keystroke dynamics and its possible use as a tool to prevent or detect fraud in the banking industry. Given that banks are constantly on the lookout for improved methods to address the menace of fraud, the paper sets out to review keystroke dynamics, its advantages, disadvantages and potential for improving the security of e-banking systems. This paper evaluates keystroke dynamics suitability of use for enhancing security in the banking sector. Results from the literature review found that keystroke dynamics can offer impressive accuracy rates for user identification. Low costs of deployment and minimal change to users modus operandi make this technology an attractive investment for banks. The paper goes on to argue that although this behavioural biometric may not be suitable as a primary method of authentication, it can be used as a secondary or tertiary method to complement existing authentication systems

Iris Recognition Approach for Preserving Privacy in Cloud Computing

Biometric identification systems involve securing biometric traits by encrypting them using an encryption algorithm and storing them in the cloud. In recent decades, iris recognition schemes have been considered one of the most effective biometric models for identifying humans based on iris texture, due to their relevance and distinctiveness. The proposed system focuses on encrypting biometric traits. The user’s iris feature vector is encrypted and stored in the cloud. During the matching process, the user’s iris feature vector is compared with the one stored in the cloud. If it meets the threshold conditions, the user is authenticated. Iris identification in cloud computing involves several steps. First, the iris image is pre-processed to remove noise using the Hough transform. Then, the pixel values are normalized, Gabor filters are applied to extract iris features. The features are then encrypted using the AES 128-bit algorithm. Finally, the features of the test image are matched with the stored features on the cloud to verify authenticity. The process ensures the privacy and security of the iris data in cloud storage by utilizing encryption and efficient image processing techniques. The matching is performed by setting an appropriate threshold for comparison. Overall, the approach offers a significant level of safety, effectiveness, and accuracy