Biometric authentication has garnered significant attention as a secure and efficient method of identity verification. Among the various modalities, hand vein biometrics, including finger vein, palm vein, and dorsal hand vein recognition, offer unique advantages due to their high accuracy, low susceptibility to forgery, and non-intrusiveness. The vein patterns within the hand are highly complex and distinct for each individual, making them an ideal biometric identifier. Additionally, hand vein recognition is contactless, enhancing user convenience and hygiene compared to other modalities such as fingerprint or iris recognition. Furthermore, the veins are internally located, rendering them less susceptible to damage or alteration, thus enhancing the security and reliability of the biometric system. The combination of these factors makes hand vein biometrics a highly effective and secure method for identity verification. This review paper delves into the latest advancements in deep learning techniques applied to finger vein, palm vein, and dorsal hand vein recognition. It encompasses all essential fundamentals of hand vein biometrics, summarizes publicly available datasets, and discusses state-of-the-art metrics used for evaluating the three modes. Moreover, it provides a comprehensive overview of suggested approaches for finger, palm, dorsal, and multimodal vein techniques, offering insights into the best performance achieved, data augmentation techniques, and effective transfer learning methods, along with associated pretrained deep learning models. Additionally, the review addresses research challenges faced and outlines future directions and perspectives, encouraging researchers to enhance existing methods and propose innovative techniques.

At the end of September, amidst its usual flurry of fall hardware announcements, Amazon debuted two especially futuristic products within five days of each other. The first is a small autonomous surveillance drone, Ring Always Home Cam, that waits patiently inside a charging dock to eventually rise up and fly around your house, checking whether you left the stove on or investigating potential burglaries. The second is a palm recognition scanner, Amazon One, that the company is piloting at two of its grocery stores in Seattle as a mechanism for faster entry and checkout. Both products aim to make security and authentication more convenient--but for privacy-conscious consumers, they also raise red flags. Amazon's latest data-hungry innovations are not launching in a vacuum.

A new biometric technology that literally waves goodbye to passwords is due to be announced by Hitachi Europe Ltd. on September 10. This first-of-a-kind technology couples Hitachi's proven secure finger vein technology with any device that has a camera. So, could this be the beginning of the end for not only passwords but fingerprint scanning and facial recognition systems? I've been taking an exclusive first look at the new hand gesture biometric authentication technology. Hitachi has been a leading player in the biometric authentication business for many years, with its finger vein biometrics used by banks to replace passwords for authorizing transactions.

Two hackers managed to trick a vein scanning system just by using a simple wax hand. As the name suggests, vein authentication systems use a computer to scan and verify a user's veins by studying their shape, size and position underneath a hand. But it seems the system isn't totally foolproof, as security researchers Jan Krissler and Julian Albrecht revealed the sensors could be duped by creating a fake hand out of wax. Security researchers Jan Krissler and Julian Albrecht discovered a vein authentication system could be fooled. Vein authentication is a increasingly popular form of biometric security.