A Study on Fingerprint Hash Code Generation Using Euclidean Distance for Identifying a User
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| Název: | A Study on Fingerprint Hash Code Generation Using Euclidean Distance for Identifying a User |
|---|---|
| Autoři: | Sreeramana Aithal P., orcid:0000-0002-4691-, Krishna Prasad, K. |
| Informace o vydavateli: | Zenodo |
| Rok vydání: | 2017 |
| Sbírka: | Zenodo |
| Témata: | Fingerprint image, Fingerprint hashcode, Authentication, Multifactor authentication model, Euclidean distance |
| Popis: | Biometrics innovation has ended up being a precise and proficient response to the security issue. Biometrics is a developing field of research as of late and has been dedicated to the distinguishing proof or authentication of people utilizing one or multiple inherent physical or behavioural characteristics. The unique fingerprint traits of a man are exceptionally exact and are special to a person. Authentication frameworks in light of unique fingerprints have demonstrated to create low false acceptance rate and false rejection rate, alongside other favourable circumstances like simple and easy usage strategy. But the modern study reveals that fingerprint is not so secured like secured passwords which consist of alphanumeric characters, number and special characters. Fingerprints are left at crime places, on materials or at the door which is usually class of latent fingerprints. We cannot keep fingerprint as secure like rigid passwords. In this paper, we discuss fingerprint image Hash code generation based on the Euclidean distance calculated on the binary image. Euclidean distance on a binary image is the distance from every pixel to the nearest neighbour pixel which is having bit value one. Hashcode alone not sufficient for Verification or Authentication purpose, but can work along with Multifactor security model or it is half secured. To implement Hash code generation we use MATLAB2015a. This study shows how fingerprints Hash code uniquely identifies a user or acts as index-key or identity-key. |
| Druh dokumentu: | article in journal/newspaper |
| Jazyk: | unknown |
| Relation: | https://zenodo.org/records/1133545; oai:zenodo.org:1133545; https://doi.org/10.5281/zenodo.1133545 |
| DOI: | 10.5281/zenodo.1133545 |
| Dostupnost: | https://doi.org/10.5281/zenodo.1133545 https://zenodo.org/records/1133545 |
| Rights: | Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode |
| Přístupové číslo: | edsbas.5A47FE5A |
| Databáze: | BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: A Study on Fingerprint Hash Code Generation Using Euclidean Distance for Identifying a User – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sreeramana+Aithal+P%2E%22">Sreeramana Aithal P.</searchLink><br /><searchLink fieldCode="AR" term="%22orcid%3A0000-0002-4691-%22">orcid:0000-0002-4691-</searchLink><br /><searchLink fieldCode="AR" term="%22Krishna+Prasad%2C+K%2E%22">Krishna Prasad, K.</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: Zenodo – Name: DatePubCY Label: Publication Year Group: Date Data: 2017 – Name: Subset Label: Collection Group: HoldingsInfo Data: Zenodo – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Fingerprint+image%22">Fingerprint image</searchLink><br /><searchLink fieldCode="DE" term="%22Fingerprint+hashcode%22">Fingerprint hashcode</searchLink><br /><searchLink fieldCode="DE" term="%22Authentication%22">Authentication</searchLink><br /><searchLink fieldCode="DE" term="%22Multifactor+authentication+model%22">Multifactor authentication model</searchLink><br /><searchLink fieldCode="DE" term="%22Euclidean+distance%22">Euclidean distance</searchLink> – Name: Abstract Label: Description Group: Ab Data: Biometrics innovation has ended up being a precise and proficient response to the security issue. Biometrics is a developing field of research as of late and has been dedicated to the distinguishing proof or authentication of people utilizing one or multiple inherent physical or behavioural characteristics. The unique fingerprint traits of a man are exceptionally exact and are special to a person. Authentication frameworks in light of unique fingerprints have demonstrated to create low false acceptance rate and false rejection rate, alongside other favourable circumstances like simple and easy usage strategy. But the modern study reveals that fingerprint is not so secured like secured passwords which consist of alphanumeric characters, number and special characters. Fingerprints are left at crime places, on materials or at the door which is usually class of latent fingerprints. We cannot keep fingerprint as secure like rigid passwords. In this paper, we discuss fingerprint image Hash code generation based on the Euclidean distance calculated on the binary image. Euclidean distance on a binary image is the distance from every pixel to the nearest neighbour pixel which is having bit value one. Hashcode alone not sufficient for Verification or Authentication purpose, but can work along with Multifactor security model or it is half secured. To implement Hash code generation we use MATLAB2015a. This study shows how fingerprints Hash code uniquely identifies a user or acts as index-key or identity-key. – Name: TypeDocument Label: Document Type Group: TypDoc Data: article in journal/newspaper – Name: Language Label: Language Group: Lang Data: unknown – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://zenodo.org/records/1133545; oai:zenodo.org:1133545; https://doi.org/10.5281/zenodo.1133545 – Name: DOI Label: DOI Group: ID Data: 10.5281/zenodo.1133545 – Name: URL Label: Availability Group: URL Data: https://doi.org/10.5281/zenodo.1133545<br />https://zenodo.org/records/1133545 – Name: Copyright Label: Rights Group: Cpyrght Data: Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode – Name: AN Label: Accession Number Group: ID Data: edsbas.5A47FE5A |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5281/zenodo.1133545 Languages: – Text: unknown Subjects: – SubjectFull: Fingerprint image Type: general – SubjectFull: Fingerprint hashcode Type: general – SubjectFull: Authentication Type: general – SubjectFull: Multifactor authentication model Type: general – SubjectFull: Euclidean distance Type: general Titles: – TitleFull: A Study on Fingerprint Hash Code Generation Using Euclidean Distance for Identifying a User Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sreeramana Aithal P. – PersonEntity: Name: NameFull: orcid:0000-0002-4691- – PersonEntity: Name: NameFull: Krishna Prasad, K. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2017 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
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