Physical Layer Authentication via Fingerprint Embedding: Min-Entropy Analysis : Invited Presentation

Perazzone, Jake; Yu, Paul; Sadler, Brian M.; Blum, Rick S.

doi:10.1109/ciss.2019.8693051

Cited by 8 publications

(5 citation statements)

References 14 publications

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“…In the conventional strategy, the tag power is fixed as 0.015 and only φ varies, which is adopted in [12], [15]. First of all, we can observe that the authentication probability (P D ) is the same by the proposed fixed ψ strategy in Fig.…”

Section: Numerical Resultsmentioning

confidence: 91%

“…the mean in both hypotheses only depends on the length of sequence L t , and L t is constant in the power allocation strategy. The second term and third term in parentheses in (15) can be regarded as zero, since multi-user precoder eliminates the effect of other users' channel and AN precoder is null to users' channel. Then, the variance in (15) can be approximated as…”

Section: A Analysis Of Authentication Probabilitymentioning

confidence: 99%

“…The second term and third term in parentheses in (15) can be regarded as zero, since multi-user precoder eliminates the effect of other users' channel and AN precoder is null to users' channel. Then, the variance in (15) can be approximated as…”

Section: A Analysis Of Authentication Probabilitymentioning

confidence: 99%

See 2 more Smart Citations

Power Allocation for Fingerprint-Based PHY-Layer Authentication with mmWave UAV Networks

Maeng

Yapıcı

Güvenç

et al. 2021

ICC 2021 - IEEE International Conference on Communications

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Physical layer security (PLS) techniques can help to protect wireless networks from eavesdropper attacks. In this paper, we consider the authentication technique that uses fingerprint embedding to defend 5G cellular networks with unmanned aerial vehicle (UAV) systems from eavesdroppers and intruders. Since the millimeter wave (mmWave) cellular networks use narrow and directional beams, PLS can take further advantage of the 3D spatial dimension for improving the authentication of UAV users. Considering a multi-user mmWave cellular network, we propose a power allocation technique that jointly takes into account splitting of the transmit power between the precoder and the authentication tag, which manages both the secrecy as well as the achievable rate. Our results show that we can obtain optimal achievable rate with expected secrecy.

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Section: Numerical Resultsmentioning

confidence: 91%

Section: A Analysis Of Authentication Probabilitymentioning

confidence: 99%

See 1 more Smart Citation

Power Allocation for Fingerprint-Based PHY-Layer Authentication with mmWave UAV Networks

Maeng

Yapıcı

Güvenç

et al. 2021

ICC 2021 - IEEE International Conference on Communications

View full text Add to dashboard Cite

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“…Suppose the adversary can eavesdrop some information O about the key K. The conditional min-entropy, H ∞ (K|O), is adopted to indicate the remaining uncertainty. Given an observation o, the probability of adversaries successfully obtaining the key using the maximum likelihood decoder on the first try is [46]:…”

Section: Security Evaluation For the Probing Phase Of The Key Generat...mentioning

confidence: 99%

Dynamic Bayesian Network Based Security Analysis for Physical Layer Key Extraction

Huang

Ansari

Huang

et al. 2022

IEEE Open J. Commun. Soc.

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Internet of Things (IoT) is envisioned to expand Internet connectivity of the physical world, and the mobile edge cloud can be leveraged to enhance the resource-constrained IoT devices. The performance of the cloud-enhanced IoT applications depends on various system-wide information, such as the wireless channel states between IoT devices and their corresponding serving edge cloud nodes. However, with the semi-trusted edge resources and the public nature of wireless channels, public sharing of system information should be avoided to better balance the tradeoff between performance and security. In this paper, the benefits of local information exchange is investigated, where the privately-owned physical layer channel information is leveraged to extract lightweight keys. For the point-to-point wireless communications links with multiple passive eavesdroppers, the security metric in terms of conditional min-entropy is evaluated via the proposed Dynamic Bayesian Model. The proposed model can flexibly incorporate various dynamic information flows in the system and quantify the information leakage caused by wireless broadcasting. The rigorously defined and derived security metrics for such a key generation pipeline has been verified via the real-world collected time-varying wireless channel data. The designed model can achieve previously inconceivable security properties.

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“…Min entropy has been used in studies related to cryptographic primitives, such as hash functions [ 19 , 20 ], in developing cryptographic hardware such as PUFs (physically unclonable functions) [ 21 ], and in authentication [ 22 , 23 ] and secret sharing [ 24 ].…”

Section: Entropy Measures and Related Conceptsmentioning

confidence: 99%

The Odyssey of Entropy: Cryptography

Zolfaghari

Bibak

Koshiba

2022

Entropy

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After being introduced by Shannon as a measure of disorder and unavailable information, the notion of entropy has found its applications in a broad range of scientific disciplines. In this paper, we present a systematic review on the applications of entropy and related information-theoretical concepts in the design, implementation and evaluation of cryptographic schemes, algorithms, devices and systems. Moreover, we study existing trends, and establish a roadmap for future research in these areas.

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Physical Layer Authentication via Fingerprint Embedding: Min-Entropy Analysis : Invited Presentation

Cited by 8 publications

References 14 publications

Power Allocation for Fingerprint-Based PHY-Layer Authentication with mmWave UAV Networks

Power Allocation for Fingerprint-Based PHY-Layer Authentication with mmWave UAV Networks

Dynamic Bayesian Network Based Security Analysis for Physical Layer Key Extraction

The Odyssey of Entropy: Cryptography

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