A Study on Biometric Template Protection Techniques

Poongodi, P.; Betty, Paul

doi:10.14445/22315381/ijett-v7p244

Cited by 11 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The template that is kept in the database may be exposed to eavesdropping which makes the protecting of it a challenging task in the biometric system. Because of these reasons, many researches used cryptography, stenography and watermarking for biometric data and template protection in the system [6]. Despite the biometrics advantages as an approach of identity verification, some concerns are raised because of the high sensitivity of biometric data: Information leakage poses a serious privacy threat.…”

Section: Introductionmentioning

confidence: 99%

Biometric iris templates security based on secret image sharing and chaotic maps

Jassim

Hamzah²,

Shimal³

2022

IJECE

View full text Add to dashboard Cite

Biometric technique includes of uniquely identifying person based on their physical or behavioural characteristics. It is mainly used for authentication. Storing the template in the database is not a safe approach, because it can be stolen or be tampered with. Due to its importance the template needs to be protected. To treat this safety issue, the suggested system employed a method for securely storing the iris template in the database which is a merging approach for secret image sharing and hiding to enhance security and protect the privacy by decomposing the template into two independent host (public) iris images. The original template can be reconstructed only when both host images are available. Either host image does not expose the identity of the original biometric image. The security and privacy in biometrics-based authentication system is augmented by storing the data in the form of shadows at separated places instead of whole data at one. The proposed biometric recognition system includes iris segmentation algorithms, feature extraction algorithms, a (2, 2) secret sharing and hiding. The experimental results are conducted on standard colour UBIRIS v1 data set. The results indicate that the biometric template protection methods are capable of offering a solution for vulnerability that threatens the biometric template.

show abstract

Section: Introductionmentioning

confidence: 99%

Biometric iris templates security based on secret image sharing and chaotic maps

Jassim

Hamzah²,

Shimal³

2022

IJECE

View full text Add to dashboard Cite

show abstract

“…The invader marks the storage record straightaway via a visibly conceded application to mount denial-of-service (Arjunwadkar et al, 2012;Habibu & Sam, 2018;Poongodi & Betty, 2014). Figure 3 characterized point eight attack.…”

Section: Attack On Database Templatementioning

confidence: 99%

Development of secured algorithm to enhance the privacy and security template of biometric technology

Habibu¹

View full text Add to dashboard Cite

The security of information and personal privacy are the growing concerns in today’s human life worldwide. The storage of biometric data in the database has raised the prospect of compromising the database leading to grave risks and misuse of the person’s privacy such as growth in terrorism and identity fraud. When a person’s biometric data stored is revealed, their security and privacy are being compromised. This research described a detailed evaluation on several outbreaks and threats associated with the biometric technology. It analyzed the user’s fear and intimidations to the biometric technology alongside the protection steps for securing the biometric data template in the database. It is known that, when somebody’s biometric data template is compromised from the database that consequently might indicate proof of identity robbery of that person. Mixed method to compute and articulate the results as well as a new tactic of encryption-decryption algorithm with a design pattern of Model View Template (MVT) are used for securing the biometric data template in the database. The model managed information logically, the view indicated the visualization of the data, and the template directed the data migration into pattern object. Factors influencing fear of biometric technology such as an exposer of personal information, improper data transfer, and data misuse are found. Strong knowledge of the ideal technology like the private skills of the biometric technology, data secrecy and perceived helpfulness are established. The fears and attacks along the technology like a counterfeit of documents and brute-force attack are known. The designed algorithm based on the cryptographic module of the Fernet keys instance are utilized. The Fernet keys are combined to generate a multiFernet key, integrated with biometric data to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and firmly stored in the database. The storage database has security measures that guard against an impostor’s attack. The database system can block the attacker from unauthorized access. Thus, significantly increased individual data privacy and integrity.

show abstract

3T‐FASDM: Linear discriminant analysis‐based three‐tier face anti‐spoofing detection model using support vector machine

Bakshi

Gupta

et al. 2020

Int J Communication

View full text Add to dashboard Cite

SummaryIn recent years, to solve the problem of face spoofing, momentous work has been done in this field, but still, there is a need for establishing counter measures to the biometric spoofing attacks. Although trained and evaluated on different databases, impressive results have been achieved in existing face anti‐spoofing techniques, but biometric authentication is a very significant problem as imposters are using lots of reconstructed samples or fake synthetic material or structure that can be used for various attack purposes. For the first time, to the best of our knowledge, this paper explains the security for face anti‐spoofing detection using linear discriminant analysis and validates the results by calculating HTER and accuracy on different databases (i.e., REPLAY ATTACK and CASIA). The proposed model, that is, three‐tier face anti‐spoofing detection model (3T‐FASDM), is used for the detection of the fake biometric user and works well for real‐time applications. The proposed methods tested on a set of state‐of‐the‐art anti‐spoofing features for the face mode gives a very low degree of complexity as 26 general image quality measures are applied to differentiate among legitimate and imposter samples. The outcomes obtained from publically available data show that this technique has improved performance and accuracy by analyzing the HTER and machine learning classifiers that are helpful to differentiate among real and fake traits.

show abstract

A Study on Biometric Template Protection Techniques

Cited by 11 publications

References 0 publications

Biometric iris templates security based on secret image sharing and chaotic maps

Biometric iris templates security based on secret image sharing and chaotic maps

Development of secured algorithm to enhance the privacy and security template of biometric technology

3T‐FASDM: Linear discriminant analysis‐based three‐tier face anti‐spoofing detection model using support vector machine

Contact Info

Product

Resources

About