Secret Key-Based Identification and Authentication With a Privacy Constraint

Kittichokechai, Kittipong; Caire, Giuseppe

doi:10.1109/tit.2016.2609401

Cited by 20 publications

(25 citation statements)

References 31 publications

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“…where > 0 is a fixed number, and δ → 0 as → 0; (a) follows from the union bound; (b) follows from Claim 2 and Claim 3. Since R C + R J > R I + I(U ; X) − I(U ; Y ) + δ due to (16), we obtain that Pr(E 51 |A) → 0 as N → ∞.…”

Section: Proof: the Proof Is Given In Appendixmentioning

confidence: 82%

“…By taking both the privacy and secrecy into account, the privacy-secrecy trade-off in biometric authentication systems is characterized in [6], [14], [15]. The privacy and secrecy aspects in biometric identification systems that allow authentication are investigated in [7], [16], [17]. In [18], [19], the authors additionally considered noisy enrollment in a privacy-preserving biometric identification system.…”

Section: Introductionmentioning

confidence: 99%

“…In [7], [16], the biometric identification system is characterized by a privacy constraint on the privacy leakage rate, which is not necessarily negligible. In this work, we study biometric identification systems that allow authentication with a more stringent privacy constraint than that in [7], [16]. Namely, the privacy leakage rate in our case is required to be sufficiently small, whereas the ones in [9] and [10] are not.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Two-Stage Biometric Identification Systems Without Privacy Leakage

Zhou

Oechtering

et al. 2021

IEEE J. Sel. Areas Inf. Theory

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We study two-stage biometric identification systems that allow authentication without privacy leakage. In the enrollment phase, secret keys and two layers of the helper data for each user are generated. Additional to the helper data and secret keys, we also introduce private keys in the systems. In the identification phase, an unknown but previously enrolled user is observed, and the user's private key is also presented to the system. The system firstly compares the user with the first layer helper database, outputs a list, and obtains a set of user indices. Then the system compares the observed user with the users in the set. Therefore, the identification procedure avoids an exhaustive search and only has to do a comparison with some part of the users in the system, which leads to a systematic reduction of the search complexity. Fundamental trade-offs among the identification rate, the secret key rate, the private key rate, the helper data rate, and the list size rate are derived in the imposed two-stage biometric identification systems without privacy leakage. Moreover, the obtained results show that a private key can boost the identification rate and the secret key rate, as well as preserve privacy.

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Section: Proof: the Proof Is Given In Appendixmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Two-Stage Biometric Identification Systems Without Privacy Leakage

Zhou

Oechtering

et al. 2021

IEEE J. Sel. Areas Inf. Theory

View full text Add to dashboard Cite

show abstract

“…In [13], key-based authentication is solved from the perspective of privacy-limited registration data. It is assumed that the user's measurement during the authentication phase is controlled through a cost-limited "action" sequence.…”

Section: A Conventional Security Methodsmentioning

confidence: 99%

Securing Health Monitoring via Body-Centric Time-Frequency Signature Authorization

Zhao

Zhang

Yang

et al. 2021

IEEE Internet Things J.

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Identity-based attacks serve as the basis of an intruder's attempt to launch security infringements in mobile health monitoring scenarios. Wireless channel perturbations due to the presence of human body are a relative phenomenon depending heavily on the subject's dielectric properties. A new Body-Centric Signature Authorization (B-CSAI) approach based on time-frequency domain characteristics was proposed. This method utilizes multiple millimeter wave bands of 27-28 GHz, 29-30 GHz, and 31-32 GHz, thereby enhancing the security in body-centric communications exploiting benefits of subject specific channel signature. The proposed bornprint method is based on the intrinsic identity related time-frequency domain information, which generated by the user's natural hand motion signature and resulting creeping waves and space waves. It can meet the unconditional keyless authorization requirements. A detailed measurement campaign considering radiation efficiency ((). ,. ,. 25 8 24 7 26 4 dB η = − − −), pathloss exponent, and shadowing factor in three millimeter wave bands, using six human subjects confirm the usability and efficiency of the proposed approach. This also shows that there is a wide space for realizing security from physical mechanisms.

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“…The trade-off between the identification capacity and the storage is studied in [4]. By considering the privacy and secrecy aspects, biometric identification systems that allow authentication are studied in [2], [5], where the identification-secrecy-privacy tradeoff is studied. Multiple-use of biometric information in biometric authentication systems is considered in [6] to improve secrecy and efficiency.…”

Section: Introductionmentioning

confidence: 99%