Protected Honey Face Templates

Martiri, Edlira; Yang, Bian; Busch, Christoph

doi:10.1109/biosig.2015.7314618

Cited by 4 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, an extra layer of protection is needed with biometric feature schemes, as these have been shown to be flawed. A honey template protection scheme relating to faces has been proposed and evaluated as representing an improvement on existing schemes [12].…”

Section: Related Workmentioning

confidence: 99%

Achieving Flatness: Honeywords Generation Method for Passwords based on user behaviours

Akif¹,

Sabeeh²,

Rodgers³

et al. 2019

ijacsa

View full text Add to dashboard Cite

Honeywords (decoy passwords) have been proposed to detect attacks against hashed password databases. For each user account, the original password is stored with many honeywords in order to thwart any adversary. The honeywords are selected deliberately such that a cyber-attacker who steals a file of hashed passwords cannot be sure, if it is the real password or a honeyword for any account. Moreover, entering with a honeyword to login will trigger an alarm notifying the administrator about a password file breach. At the expense of increasing the storage requirement by 24 times, the authors introduce a simple and effective solution to the detection of password file disclosure events. In this study, we scrutinise the honeyword system and highlight possible weak points. Also, we suggest an alternative approach that selects the honeywords from existing user information, a generic password list, dictionary attack, and by shuffling the characters. Four sets of honeywords are added to the system that resembles the real passwords, thereby achieving an extremely flat honeywords generation method. To measure the human behaviours in relation to trying to crack the password, a testbed engaged with by 820 people was created to determine the appropriate words for the traditional and proposed methods. The results show that under the new method it is harder to obtain any indication of the real password (high flatness) when compared with traditional approaches and the probability of choosing the real password is 1/k, where k = number of honeywords plus the real password.

show abstract

Section: Related Workmentioning

confidence: 99%

Achieving Flatness: Honeywords Generation Method for Passwords based on user behaviours

Akif¹,

Sabeeh²,

Rodgers³

et al. 2019

ijacsa

View full text Add to dashboard Cite

show abstract

“…In the biometric context, in a honey‐based system the use of stolen templates can be detected when the pseudonymous identifier ( PI *) is presented again to the system: if it is a sugar template, the system will detect the leakage and impersonation attempt. A particular case study for facial verification was presented in [10] using irreversible eigenface‐based templates. The performance, security and irreversibility evaluations show the feasibility of such an approach.…”

Section: Related Workmentioning

confidence: 99%

“…It is proposed in [8] for the protection of traditional passwords where several password hashes are stored for each subject: hashes for the real password and for other false passwords or honeywords. More recently, a general framework for the application of the honeywords concept to biometric authentication system, known as Honey Templates , was proposed [9], and a particular case study on face verification based on eigenfaces was applied on a small scale database [10], showing its effectiveness in terms of both irreversibility and recognition performance (see Section 2.1).…”

Section: Introductionmentioning

confidence: 99%

Biometric template protection based on Bloom filters and honey templates

et al. 2016

Self Cite

View full text Add to dashboard Cite

Biometric verification can be considered one of the most reliable approaches to person authentication. However, biometrics are highly sensitive personal data and any information leakage poses severe security and privacy risks. Biometric templates should hence be protected and impersonation with stolen templates must be prevented, while preserving system's performance. In this study, a general biometric template protection scheme based on honey templates and Bloom filters is proposed, in order to grant privacy protection to the enrolled subject and detect the use of stolen templates. The performance and security evaluations show the soundness of the proposed scheme for facial verification. The benchmark is conducted with the publicly available BioSecure Multimodal DB and the free Bob image processing toolbox, so that research is fully reproducible.

show abstract