Biometrics in Cyber Security

Computers play an important role in our daily lives and its usage has grown manifolds today. With ever increasing demand of security regulations all over the world and large number of services provided using the internet in day to day life, the assurance of security associated with such services has become a crucial issue. Biometrics is a key to the future of data/cyber security. This paper presents a biometric recognition system which can be embedded in any system involving access control, e-commerce, online banking, computer login etc. to enhance the security. Fingerprint is an old and mature technology which has been used in this work as biometric trait. In this paper a fingerprint recognition system based on no minutiae features: Fuzzy features and Invariant moment features has been developed. Fingerprint images from FVC2002 are used for experimentation. The images are enhanced for improving the quality and a region of interest (ROI) is cropped around the core point. Two sets of features are extracted from ROI and support vector machine (SVM) is used for verification. An accuracy of 95 per cent is achieved with the invariant moment features using RBF kernel in SVM

Features for Cross Spectral Image Matching: A Survey

In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching

Recent Application in Biometrics

In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book

An Overview on Privacy Preserving Biometrics

The Internet has consolidated itself as a very powerful platform that has changed the communication and business way. Nowadays, the number of users navigating through Internet is about 1,552 millions according to Internet World Stats. This large audience demands online commerce, e-government, knowledge sharing, social networks, online gaming . . . which grew exponentially over the past few years. The security of these transactions is very important considering the number of information that could be intercepted by an attacker. Within this context, authentication is one of the most important challenges in computer security. Indeed, the authentication step is often considered as the weakest link in the security of electronic transactions. In general, the protection of the message content is achieved by using cryptographic protocols that are well known and established. The well-known ID/password is far the most used authentication method, it is widely spread despite its obvious lack of security. This is mainly due to its implementation ease and to its ergonomic feature: the users are used to this system, which enhances its acceptance and deployment. Many more sophisticated solutions exist in the state of the art to secure logical access control (one time passwords tokens, certificates . . . ) but none of them are used by a large community of users for a lack of simplicity usage (O'Gorman, 2003)..

Analysis of the image moments sensitivity for the application in pattern recognition problems

Momenti slike su numerički deskriptori koji sadrže informaciju o svojstvima invarijantnim na translaciju, rotaciju, promjenu skale i neke oblike distorzije, a njihova analiza je jedna od metoda koje se često koriste pri analizi slika i raspoznavanju uzoraka. U okviru ove radnje razvijeni su algoritmi za računanje geometrijskih, Legendreovih, Zernikeovih, Fourier – Mellinovih te tri tipa Fourier – Jacobijevih momenata, kao i iz njih definiranih invarijanti slike u programskom jeziku MatLab uz rješavanje inverznog problema rekonstrukcije početnog ulaza. Za sve tipove momenata osim najjednostavnijih geometrijskih definirani su vektori osjetljivosti na rotaciju i promjenu skale čije su komponente oni članovi skupa koji nose značajnije informacije o ulaznoj slici. Primjenom novih deskriptora na klasifikaciju rukom pisanih slova i identifikacijskih fotografija osoba pokazano je da je relevantna informacija o ulazu na taj način sačuvana, a njihov je izračun znatno brži i jednostavniji uz zadržanu sposobnost jednoznačnog raspoznavanja uzoraka. Korištenjem momenata slike i vektora osjetljivosti analizirani su znakovi s dvaju glagoljskih spomenika te utvrđeno postojanje mješavine znakova trokutastog i okruglog modela glagoljice. Metoda je primijenjena i na klasifikaciju tragova puzanja ličinki mutanata vinske mušice za potrebe proučavanja odgovora živčanog sustava na različite podražaje.Image moments are numerical descriptors invariant to translation, rotation, change of scale and some types of image distortion and their analysis is one of the most often used methods in image processing and pattern recognition. In this work, algorithms for calculation of geometric, Legendre, Zernike, Fourier – Mellin and three types of Fourier – Jacobi moments were implemented in MatLab. Hu's, affine and blur invariants were also obtained as well as inverse problem of input image reconstruction solved. For each type of image moments exept geometric ones the set of sensitivity vectors for rotation and scale were defined. Their components are those image moments which describe more important features of the input image. These new descriptors were applied for classification of handwritten letters and identifying personal photos. It was shown that the process of such descriptor calculation is much faster and simpler while preserving all the relevant information about input image. Using this method, the signs carved in two glagolitic inscriptions were analyzed and the mixture of triangular and round glagolitic letters found. The method was also applied to classification of the mutant fruit fly larvae crawling trails which is needed in studying responses of the nervous system to different stimuli

Analysis of the image moments sensitivity for the application in pattern recognition problems

Momenti slike su numerički deskriptori koji sadrže informaciju o svojstvima invarijantnim na translaciju, rotaciju, promjenu skale i neke oblike distorzije, a njihova analiza je jedna od metoda koje se često koriste pri analizi slika i raspoznavanju uzoraka. U okviru ove radnje razvijeni su algoritmi za računanje geometrijskih, Legendreovih, Zernikeovih, Fourier – Mellinovih te tri tipa Fourier – Jacobijevih momenata, kao i iz njih definiranih invarijanti slike u programskom jeziku MatLab uz rješavanje inverznog problema rekonstrukcije početnog ulaza. Za sve tipove momenata osim najjednostavnijih geometrijskih definirani su vektori osjetljivosti na rotaciju i promjenu skale čije su komponente oni članovi skupa koji nose značajnije informacije o ulaznoj slici. Primjenom novih deskriptora na klasifikaciju rukom pisanih slova i identifikacijskih fotografija osoba pokazano je da je relevantna informacija o ulazu na taj način sačuvana, a njihov je izračun znatno brži i jednostavniji uz zadržanu sposobnost jednoznačnog raspoznavanja uzoraka. Korištenjem momenata slike i vektora osjetljivosti analizirani su znakovi s dvaju glagoljskih spomenika te utvrđeno postojanje mješavine znakova trokutastog i okruglog modela glagoljice. Metoda je primijenjena i na klasifikaciju tragova puzanja ličinki mutanata vinske mušice za potrebe proučavanja odgovora živčanog sustava na različite podražaje.Image moments are numerical descriptors invariant to translation, rotation, change of scale and some types of image distortion and their analysis is one of the most often used methods in image processing and pattern recognition. In this work, algorithms for calculation of geometric, Legendre, Zernike, Fourier – Mellin and three types of Fourier – Jacobi moments were implemented in MatLab. Hu's, affine and blur invariants were also obtained as well as inverse problem of input image reconstruction solved. For each type of image moments exept geometric ones the set of sensitivity vectors for rotation and scale were defined. Their components are those image moments which describe more important features of the input image. These new descriptors were applied for classification of handwritten letters and identifying personal photos. It was shown that the process of such descriptor calculation is much faster and simpler while preserving all the relevant information about input image. Using this method, the signs carved in two glagolitic inscriptions were analyzed and the mixture of triangular and round glagolitic letters found. The method was also applied to classification of the mutant fruit fly larvae crawling trails which is needed in studying responses of the nervous system to different stimuli