BAN-GZKP: Optimal Zero Knowledge Proof based Scheme for Wireless Body Area Networks

Bu, Gewu; Potop-Butucaru, Maria

doi:10.1016/j.adhoc.2018.04.006

Cited by 16 publications

(14 citation statements)

References 13 publications

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“…In what follows, we perform a formal security analysis of our scheme using the formalization in [14]. Let us define a sensor node (SN ) which holds a known information Y as…”

Section: A Security Analysismentioning

confidence: 99%

“…With the zero knowledge proof, sensors prove to each other having a secret without revealing it in the process. Unfortunately, Bu and Potop-Butucaru [14] pointed out that [13] could not resist data replay, redundancy information, and denialof-service (DoS) attacks. To fix the weaknesses in [13], the authors in [14] proposed random key for each session and hop-by-hop authentication.…”

Section: Introductionmentioning

confidence: 99%

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Mutual Authentication in Body Area Networks Using Signal Propagation Characteristics

Umar

Liao

2020

IEEE Access

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Developments in wireless communications and wearable devices have facilitated the emergence of a network of tiny sensors embedded in, on or around human body called Wireless Body Area Network (WBAN). Over the last decade, WBAN has increasingly been playing a vital role in modern medical systems because of its potential to revolutionize healthcare delivery. The data collected by the sensors contain sensitive information and are transmitted via wireless channels. However, the openness of these channels makes WBAN vulnerable to attacks by unauthorized users. Therefore, secure authentication and data encryption schemes in WBAN are essential. The resource constraint nature of the sensors makes traditional cryptographic schemes unsuitable. Consequently, authentication schemes based on channel characteristics are proposed, which are more suitable with fewer requirements. However, existing approaches do not consider mutual authentication as well as passive/active attacks. Motivated by these limitations, we propose in this paper, a mutual authentication and data encryption scheme based on signal propagation characteristics and enhanced butterfly algorithm. To validate the effectiveness of our scheme, we conducted an extensive real-world experiment involving 5 volunteers in indoor and outdoor areas, under distinct scenarios. We further conducted security and performance analyses to validate the effectiveness of our scheme in terms of resources and its resilience to various attacks. The results of the experiments and the analyses show that our scheme could mutually identify legitimate users and protect user data against active/passive eavesdropping attacks with minimal overhead.INDEX TERMS Authentication, active attack, passive attack, signal propagation characteristic, wireless body area network (WBAN).

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“…In what follows, we perform a formal security analysis of our scheme using the formalization in [14]. Let us define a sensor node (SN ) which holds a known information Y as…”

Section: A Security Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mutual Authentication in Body Area Networks Using Signal Propagation Characteristics

Umar

Liao

2020

IEEE Access

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“…In this section, we define a family of networks, Level-Separable Network, issued from WBAN area (e.g. [3], [5], [6], [4] and [7]). We say an arbitrary network is a Level-Separable Network if the underlay communication graph G = (V, E) of the network verifies the Level-Separable propriety defined below.…”

Section: B Level-separable Networkmentioning

confidence: 99%

“…We first introduce a new family of networks, called level-separable networks issued from in Wireless Body Area Networks (e.g. [3], [5], [6], [4] and [7]). We then propose an acknowledgement-free broadcast strategy using 1-bit labels and a broadcast scheme with acknowledgement using 2-bits labels.…”

Section: Introductionmentioning

confidence: 99%

Wireless Broadcast with short labelling

Bu¹,

Potop-Butucaru²,

Rabie³

2019

Preprint

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In this paper we study the broadcast problem in wireless networks when the broadcast is helped by a labelling scheme. We focus on two variants of broadcast: broadcast without acknowledgement (i.e. the initiator of the broadcast is not notified at the end of broadcast) and broadcast with acknowledgement. Our contribution is twofold. First, we propose label optimal broadcast algorithms in a class of networks issued from recent studies in Wireless Body Area Networks then we extend our solutions to arbitrary networks. We propose an acknowledgement-free broadcast strategy using 1-bit labels and broadcast with acknowledgement using 2-bits labels. In the class of level-separable networks our algorithms finish within 2D rounds for both broadcast with and without acknowledgement, where D is the eccentricity of the broadcast initiator. Second, we improve a recent [11] labelling-based broadcast scheme with acknowledgement designed for arbitrary networks in terms of memory complexity.

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“…Physiological data are collected through WBAN nodes from the patient and transmitted to the sink [15]; thus, WBAN helps in the continuous monitoring of the patient and updates the status of the patient to a remote doctor [16]. Wearable equipment on the market now allows for providing users improved healthcare service [17].…”

Section: Introductionmentioning

confidence: 99%

Wireless Body Area Network (WBAN)-Based Telemedicine for Emergency Care

Latha

Pandu

2020

Sensors

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This paper is a collection of telemedicine techniques used by wireless body area networks (WBANs) for emergency conditions. Furthermore, Bayes’ theorem is proposed for predicting emergency conditions. With prior knowledge, the posterior probability can be found along with the observed evidence. The probability of sending emergency messages can be determined using Bayes’ theorem with the likelihood evidence. It can be viewed as medical decision-making, since diagnosis conditions such as emergency monitoring, delay-sensitive monitoring, and general monitoring are analyzed with its network characteristics, including data rate, cost, packet loss rate, latency, and jitter. This paper explains the network model with 16 variables, with one describing immediate consultation, as well as another three describing emergency monitoring, delay-sensitive monitoring, and general monitoring. The remaining 12 variables are observations related to latency, cost, packet loss rate, data rate, and jitter.

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BAN-GZKP: Optimal Zero Knowledge Proof based Scheme for Wireless Body Area Networks

Cited by 16 publications

References 13 publications

Mutual Authentication in Body Area Networks Using Signal Propagation Characteristics

Mutual Authentication in Body Area Networks Using Signal Propagation Characteristics

Wireless Broadcast with short labelling

Wireless Body Area Network (WBAN)-Based Telemedicine for Emergency Care

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