A novel biometric system based on palm vein image

Lee, Jen-Chun

doi:10.1016/j.patrec.2012.04.007

Cited by 143 publications

(106 citation statements)

References 20 publications

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“…Jen-Chun Lee in (Lee, 2012) has examined the encoding of palm vein features into bit string representation, during the template construction needed for the identification task. The system has decreased the size required for palm vein features to 2520 bits.…”

Section: Hand Featuresmentioning

confidence: 99%

Authentication systems: principles and threats

Abdulkader¹,

Atia²,

Mostafa³

2015

CIS

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Identity manipulation is considered a serious security issue that has been enlarged with the spread of automated systems that could be accessed either locally or remotely. Availability, integrity, and confidentiality represent the basic requirements that should be granted for successful authentication systems. Personality verification has taken multiple forms depending on different possession types. They are divided into knowledge based, token based, and biometric based authentication. The permanent ownership to the human being has increased the chances of deploying biometrics based authentication in highly secure systems. It includes capturing the biological traits, which are physiological or behavioral, extracting the important features and comparing them to the previously stored features that belong to the claimed user. Various kinds of attacks aim to take down the basic requirements at multiple points. This paper describes different types of authentication along with their vulnerable points and threatening attacks. Then it provides more details about the biometric system structure as well as examples of distinguishing biological characteristics, organized by their locations. It shows the performance results of various biometric systems along with the deployed algorithms for different components.

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Section: Hand Featuresmentioning

confidence: 99%

Authentication systems: principles and threats

Abdulkader¹,

Atia²,

Mostafa³

2015

CIS

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“…Physiological biometric relies on something the users are. It performs authentication base on physical characteristics such as facial features [18][19][20], palm prints [23,24,26], retina patterns [39,13], finger print [13,25], iris pattern [20], as well as hand geometry [13,27]. In other words, physiological biometrics is based on measurements and data derived from direct measurement of a part of the human body.…”

Section: Literature Reviewmentioning

confidence: 99%

Keystroke Dynamic Authentication in Mobile Cloud Computing

Babaeizadeh¹,

Bakhtiari²,

Maarof³

2014

IJCA

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One of the important challenges in Mobile Cloud Computing (MCC) is related to the authentication of users. There is increasing demand for suitable authentication method for accessing to the shared information via the Internet through Cloud Service Provider (CSP). Personal identification number is the most common mechanism for authentication in mobile devices; however it is not secure way for authenticating users. This work presents a method of authentication which able to identify users based on Keystroke Dynamic Authentication (KDA). Furthermore, keystrokes duration is considered as an attribute for measuring keystrokes of mobile's users. This paper proposed strong method of authentication in the password authentication scheme by combining it with keystroke authentication, which is a type of behavioral biometric mechanism. Experimental results show, the proposed method can work 97.014% correctly, due to the keystroke duration of each user depends on their behavioral characteristic and it can be measured up to milliseconds. On the other hand, if unauthorized person knows the username and password of legal user can not gain access rights because of difference between their keystroke duration. Therefore, it is hard for an attacker to pretend as an owner, and this method enhances the security of authentication in MCC

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“…Geometry-based methods are those that directly use the vein pattern structure information -this approach often has poor discriminatory ability and is highly sensitive to rotation, translation and scales changes [4]. As an example of a geometry-based system, Lee [5] used a two-dimensional Gabor filter with feature matching using Hamming distances for the vein extraction stage. Statistical-based methods calculate characteristics of the vein patterns which are then used in the matching process, but the statistical approach is often sensitive to changes in translation, rotation and scale, making it unsuitable for contactless vein recognition since careful alignment of the capturing equipment would be needed [6].…”

Section: Introductionmentioning

confidence: 99%