Securing electronics healthcare records in Healthcare 4.0 : A biometric-based approach

Hathaliya, Jigna J.; Tanwar, Sudeep; Tyagi, Sudhanshu; Kumar, Neeraj

doi:10.1016/j.compeleceng.2019.04.017

Cited by 164 publications

(56 citation statements)

References 20 publications

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“…This section briefly discusses existing studies [17][18][19][20][21][22][23][24][25] designed to secure patient data in the EMR and highlights their drawbacks.…”

Section: Related Existing Researchmentioning

confidence: 99%

“…Their scheme was based on the identity signature (Bilinear Map) to protect information and data aggregated by integration and authentication. Hathaliya et al [24] proposed an elliptic curve cryptography (160 bits) scheme to encrypt and authenticate patients' biometric properties. They used wearable sensors to collect patient data and used a mobile device to send and store these data in the medical repository (cloud server).…”

Section: Related Existing Researchmentioning

confidence: 99%

“…Besides, an intruder can send messages from a forged unit and deceive users after penetrating this module and revealing information. REISCH is robust against information leakage, while the scheme in [24] uses a 160-bit key that is vulnerable to attacks. It explicitly sends patient identities within the encrypted message in the login and authentication phases.…”

Section: Reisch Scheme With Avispamentioning

confidence: 99%

“…It also addresses only computations in transport while REISCH addresses computations in transport and processing using BLAKE2bp and homomorphic property. The schemes in [20,24,25] rely on the use of encryption to protect data without a homomorphic property, since encryption processes extremely consume SNs resources (as mentioned in Section 3.3, Point 3), while REISCH uses signatures and homomorphic property to improve HWSN network performance. Although the scheme in [23] uses encryption and signature of data with homomorphic properties, encryption can particularly affect network performance, especially through a burden on the servers.…”

Section: Performance Comparisonmentioning

confidence: 99%

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REISCH: Incorporating Lightweight and Reliable Algorithms into Healthcare Applications of WSNs

Al-Zubaidie

Zhang

2020

Applied Sciences

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Healthcare institutions require advanced technology to collect patients’ data accurately and continuously. The tradition technologies still suffer from two problems: performance and security efficiency. The existing research has serious drawbacks when using public-key mechanisms such as digital signature algorithms. In this paper, we propose Reliable and Efficient Integrity Scheme for Data Collection in HWSN (REISCH) to alleviate these problems by using secure and lightweight signature algorithms. The results of the performance analysis indicate that our scheme provides high efficiency in data integration between sensors and server (saves more than 24% of alive sensors compared to traditional algorithms). Additionally, we use Automated Validation of Internet Security Protocols and Applications (AVISPA) to validate the security procedures in our scheme. Security analysis results confirm that REISCH is safe against some well-known attacks.

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“…This section briefly discusses existing studies [17][18][19][20][21][22][23][24][25] designed to secure patient data in the EMR and highlights their drawbacks.…”

Section: Related Existing Researchmentioning

confidence: 99%

Section: Related Existing Researchmentioning

confidence: 99%

Section: Reisch Scheme With Avispamentioning

confidence: 99%

Section: Performance Comparisonmentioning

confidence: 99%

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REISCH: Incorporating Lightweight and Reliable Algorithms into Healthcare Applications of WSNs

Al-Zubaidie

Zhang

2020

Applied Sciences

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“…This leads us to the vision of a smart surroundings where the users can able to access ubiquitously available digital services from the nearby ambient environment and with minimum or no support of gadgets [4,49]. The key challenge in accessing these medical services in the gadget-free and smart environment is the secure authentication mechanism of the user by service or smart environment [21,23,29,32,35,66,91]. The research community are exploring various potential methods for secure authentication mechanism which are mainly based on biometrics features [30,31,38,77].…”

Section: Introductionmentioning

confidence: 99%

AGE: authentication in gadget-free healthcare environments

et al. 2019

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Mobile and sensor related technologies are significantly revolutionizing the medical and healthcare sectors. In current healthcare systems, gadgets are the prominent way of acquiring medical services. However, the recent technological advancements in smart and ambient environments are offering users new ways to access the healthcare services without using any explicit gadgets. One of the key challenges in such gadget-free environments is performing secure user authentication with the intelligent surroundings. For example, a secure, efficient and user-friendly authentication mechanism is essential for elderly/disabled people or patients in critical conditions requiring medical services. Hence, modern authentication systems should be sophisticated enough to identify such patients without requiring their physical efforts or placing gadgets on them. This paper proposes an anonymous and privacy-preserving biometrics based authentication scheme for such gadget-free healthcare environment. We performed formal security verification of our proposed scheme using CDVT /AD tool and our results indicate that the proposed scheme is secure for such smart and gadget-free environments. We verify that the proposed scheme can resist against various well-known security attacks. Moreover, the proposed system showed better performance as compared with existing biometrics based remote user authentication schemes.

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3T‐FASDM: Linear discriminant analysis‐based three‐tier face anti‐spoofing detection model using support vector machine

Bakshi

Gupta

et al. 2020

Int J Communication

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SummaryIn recent years, to solve the problem of face spoofing, momentous work has been done in this field, but still, there is a need for establishing counter measures to the biometric spoofing attacks. Although trained and evaluated on different databases, impressive results have been achieved in existing face anti‐spoofing techniques, but biometric authentication is a very significant problem as imposters are using lots of reconstructed samples or fake synthetic material or structure that can be used for various attack purposes. For the first time, to the best of our knowledge, this paper explains the security for face anti‐spoofing detection using linear discriminant analysis and validates the results by calculating HTER and accuracy on different databases (i.e., REPLAY ATTACK and CASIA). The proposed model, that is, three‐tier face anti‐spoofing detection model (3T‐FASDM), is used for the detection of the fake biometric user and works well for real‐time applications. The proposed methods tested on a set of state‐of‐the‐art anti‐spoofing features for the face mode gives a very low degree of complexity as 26 general image quality measures are applied to differentiate among legitimate and imposter samples. The outcomes obtained from publically available data show that this technique has improved performance and accuracy by analyzing the HTER and machine learning classifiers that are helpful to differentiate among real and fake traits.

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Securing electronics healthcare records in Healthcare 4.0 : A biometric-based approach

Cited by 164 publications

References 20 publications

REISCH: Incorporating Lightweight and Reliable Algorithms into Healthcare Applications of WSNs

REISCH: Incorporating Lightweight and Reliable Algorithms into Healthcare Applications of WSNs

AGE: authentication in gadget-free healthcare environments

3T‐FASDM: Linear discriminant analysis‐based three‐tier face anti‐spoofing detection model using support vector machine

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