Investigating of nodes and personal authentications utilizing multimodal biometrics for medical application of WBANs security

El‐Bendary, Mohsen A. M.; Kasban, H.; Haggag, Ayman; Eltokhy, Mostafa A. R.

doi:10.1007/s11042-020-08926-2

Cited by 23 publications

(6 citation statements)

References 52 publications

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“…Face Recognition [19] Webcam images of your face. Voice Recognition [27] Audio data recorded with the microphone of your device. Electroencephalogram (EEG) [95] Data from a sensor that monitors the activity of your brain.…”

Section: Biometric Trait Source Explanation Used In the Surveymentioning

confidence: 99%

Internet Users' Willingness to Disclose Biometric Data for Continuous Online Account Protection: An Empirical Investigation

Dehling,

Tolsdorf,

Federrath

et al. 2024

PoPETs

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Continuous authentication has emerged as a promising approach to increase user account security for online services. Unlike traditional authentication methods, continuous authentication provides ongoing security throughout the session, protecting against session takeover attacks due to illegitimate access. The effectiveness of continuous authentication systems relies on the continuous processing of users' sensitive biometric data. To balance security and privacy trade-offs, it's crucial to understand when users are willing to disclose biometric data for enhanced account security, addressing inevitable privacy concerns and user acceptance. To address this knowledge gap, we conducted an online study with 830 participants from the U.S., aiming to investigate user perceptions towards continuous authentication across different classes of online services. Our analysis identified four groups of biometric traits that directly reflect users' willingness to disclose them. Our findings demonstrate that willingness to disclose is influenced by both the specific biometric traits and the type of online service involved. User perceptions are strongly shaped by factors such as response efficacy, perceived privacy risks associated with the biometric traits, and concerns about the service providers' handling of such data. Our results emphasize the inadequacy of one-size-fits-all solutions and provide valuable insights for the design and implementation of continuous authentication systems.

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Section: Biometric Trait Source Explanation Used In the Surveymentioning

confidence: 99%

Internet Users' Willingness to Disclose Biometric Data for Continuous Online Account Protection: An Empirical Investigation

Dehling,

Tolsdorf,

Federrath

et al. 2024

PoPETs

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“…As discussed in [39], WBANs are valuable tools for researchers and clinical trials. They enable the collection of continuous and real-time data from participants, which can be used for medical research, drug efficacy studies, and the development of personalized healthcare approaches [40]- [42].…”

Section: Figure 2 Wban Sensor Communicationmentioning

confidence: 99%

Current security and privacy posture in wireless body area networks

Auko¹

2023

World J. Adv. Res. Rev.

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Wireless Body Area Networks (WBANs) have emerged as a promising technology for remote health monitoring and healthcare applications. However, ensuring the security and privacy of sensitive health data in WBANs is crucial to foster user trust and prevent unauthorized access or data breaches. This paper provides an overview of the key challenges, techniques, and research gaps in WBAN security and privacy. The findings indicate that the challenges in WBAN security and privacy include resource constraints, compatibility issues, privacy concerns, dynamic network environments, security and usability trade-offs, emerging threat landscape, and user awareness and education. To address these challenges, various security techniques have been developed, such as authentication and authorization mechanisms, encryption, access control, secure communication protocols, intrusion detection systems, and privacy-preserving data handling techniques. Despite the progress made, there are research gaps that require further investigation. These research gaps include the development of secure and lightweight authentication mechanisms, privacy-preserving data analysis techniques, trust and security management frameworks, resilience to insider threats, security of data aggregation and fusion, user-centric security designs, and addressing legal and ethical considerations. Addressing these research gaps and challenges requires collaboration between researchers, device manufacturers, policymakers, and end-users. Ongoing research and innovation are necessary to develop robust security techniques, privacy-enhancing technologies, and user-friendly solutions tailored for WBANs. Additionally, compliance with privacy regulations, user education, and awareness are critical for responsible and ethical use of WBANs.

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“…Because it combines various behavioral or physiological characteristics of the person to distinguish that person, multimodal biometric authentication encourages the matching accuracy of the authentication process and achieves greater reliability and security than a Unimodal biometric system. This paradigm prefers the use of many multi-level security solutions for data or picture security [6]. The fusing of distinct modality inputs, such as the facial picture and voice signal for example is the most significant problem that must be overcome when implementing a multimodal biometric scheme since the fusion procedure must take into account the specific modality of the biometric inputs.…”

Section: Introductionmentioning

confidence: 99%

“…The training samples that are closest to the query point are represented by the K symbol. As shown in Eq (6),. the Euclidian distance between the test point and each of its K closest neighbours isdetermined.-𝑑(𝑓, 𝑔) = √∑ (𝑓 𝑖 − 𝑔 𝑖 ) 2 𝑁 𝑖=1…”

mentioning

confidence: 98%

Effects of Partially/Masked Face on the Personality Identifying: Self-Multimodal Fusion Consideration

Esmail,

El-Bendary,

Aboshosha

et al. 2024

Preprint

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Due to the essential using of mask face in various fields and critical situations, there is urgent need to develop techniques for identifying personality to be more effective in presence the mask face. Also, Muslim women who wear Higab, they suffer from the traditional identifying processes. Facial recognition techniques have become ineffective with face mask. In this research, the technique of identifying the personality through the face with the mask was proposed by making a fusion between both the original face and part of the face, using Score fusion and features fusion. The research presented an extensive study of the effect of the mask on the difficulty of recognizing the face and changing the facial features. The research used more than one tool to extract the features of a face image with a mask, and a group of classification tools to identify the personality more accurately. More than one extraction tool has been combined to increase the classification accuracy. The different feature extracting of voice and masked face images are used with employing the various classifiers such as the Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gaussian Mixture Model (GMM) and Artificial Neural Network (ANN) tools. The simulation experiments results prove the superiority of score based fusion.

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Investigating of nodes and personal authentications utilizing multimodal biometrics for medical application of WBANs security

Cited by 23 publications

References 52 publications

Internet Users' Willingness to Disclose Biometric Data for Continuous Online Account Protection: An Empirical Investigation

Internet Users' Willingness to Disclose Biometric Data for Continuous Online Account Protection: An Empirical Investigation

Current security and privacy posture in wireless body area networks

Effects of Partially/Masked Face on the Personality Identifying: Self-Multimodal Fusion Consideration

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