Motivations and Topics:
Biometric systems consist in acquiring key physiological and/or behavioural features of humans, and use them for the automatic identification or verification of identity claims for physical protection. The urge for protection of sensitive infrastructure is calling for robust and secure biometric systems. In the first case, robustness is achieved by tolerating and dealing with the noise in the feature acquisition without affecting the correct outcome. This is achieved by investigating the number of false positive and false negative that noised feature acquisition causes and by proposing proper tolerance method to reduce such numbers. In the second case, a series of attacks can be directed towards a biometric system in order to bring it in error and alter the obtained result, by augmenting the number of false positive or the one of false negative. Moreover, a biometric system holds a number of data upon which the identification is performed, which may be considered sensitive and should keep private by the system. Currently, a series of proposal are being investigated in order to rise the offered level of robustness and security within such systems by using innovative pattern recognition systems and/or using multiple classifiers paving the way to multi-modal or multi-criteria biometrics.
This is to respond to the more demanding market needs with respect to security and robustness by retaining high accuracy, scalability and usability. Last, recently a novel research topic is meeting greater attention and interest: when designing and deploying biometric systems it is important to consider the cultural, social and legal contexts of these systems. There is an increasing awareness of the social and legal aspects related to biometric systems, due to the fact that they are firmly tied to our physical bodies. There are considerable privacy concerns related to biometric systems: the legal status of biometric data, the storage of biometric data, compulsory and voluntary issues and the necessity of using biometric technology. Those concerns are calling out for legal regulations to discipline the use and design of biometric systems.
The aim of the special issue is to solicit novel contributions to the current debate of improving robustness, security and privacy of biometric systems, by also seeking manuscripts on the legal and societal aspect and regulations for those systems. The list of possible topics includes, but not limited to:
Robustness of the Biometric Systems and Its improvement
Regulatory and Legal Framework of Biometric Systems
Security and Trustworthiness of Biometric Systems
Biometric Systems for Security and Privacy
Pattern Recognition Innovations in Biometry
Novel biometric acquisition and storage
De-identification and Privacy in Soft Biometrics
Anti-Spoofing and Template Security
The proposed schedule is given below:
Submission period: September 1- 30, 2017
Author notification: November 30, 2017
Revised papers due: December 31, 2017
Final notification: January 31, 2018
Publication: April, 2018 (Tentative)
Prospective authors are invited to upload their manuscripts during the submission period. Papers should be prepared by adhering to the PRLetters guidelines at https://www.elsevier.com/journals/pattern-recognition-letters/0167-8655/guide-for-authors/. All the papers will be peer-reviewed following the Pattern Recognition Letters reviewing procedures.
When submitting their papers through the online system, Authors should select the acronym “SI: RSRA-BS” to make it clear that they are submitting to this SI.
Contributors will be informed that their papers should not have been published previously, nor be under consideration for publication elsewhere. If the submissions are extended works of previously published papers, the original works should be included and a description of the changes that have been made should be provided.
Guest editors will make an initial determination of the suitability and scope of all submissions.
Managing Guest Editor:
Andrea F. Abate, University of Salerno, Italy (email@example.com)
Gian Luca Marcialis, University of Cagliari, Italy (firstname.lastname@example.org)
Norman Poh, University of Surrey, United Kingdom (email@example.com)
Carlo Sansone, University of Naples “Federico II”, Italy (firstname.lastname@example.org)