RETRACTED ARTICLE: A multilevel secure information communication model for healthcare systems

Panwar, Priya; Dhall, Sangeeta; Gupta, Shailender

doi:10.1007/s11042-020-10083-5

Cited by 9 publications

(5 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Inherent challenges of medical data; interoperability concerns. [41] Marriage of cryptography and steganography for data encryption-decryption.…”

Section: Table 1 (Continued)mentioning

confidence: 99%

See 1 more Smart Citation

A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

Wang,

Tabassum

2024

CMC

View full text Add to dashboard Cite

In an era characterized by digital pervasiveness and rapidly expanding datasets, ensuring the integrity and reliability of information is paramount. As cyber threats evolve in complexity, traditional cryptographic methods face increasingly sophisticated challenges. This article initiates an exploration into these challenges, focusing on key exchanges (encompassing their variety and subtleties), scalability, and the time metrics associated with various cryptographic processes. We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering. Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity, foundational pillars of information security. Our method employs a phased strategy, beginning with a detailed examination of traditional cryptographic processes, including Elliptic Curve Diffie-Hellman (ECDH) key exchanges. We also delve into encrypt/decrypt paradigms, signature generation modes, and the hashes used for Message Authentication Codes (MACs). Each process is rigorously evaluated for performance and reliability. To gain a comprehensive understanding, a meticulously designed simulation was conducted, revealing the strengths and potential improvement areas of various techniques. Notably, our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs, marking a significant advancement over existing methods. Furthermore, with integrity metrics at 9.35, the protocol's resilience is further affirmed. These metrics, derived from stringent testing, underscore the protocol's efficacy in enhancing data security.

show abstract

“…Inherent challenges of medical data; interoperability concerns. [41] Marriage of cryptography and steganography for data encryption-decryption.…”

Section: Table 1 (Continued)mentioning

confidence: 99%

“…This method achieves efficient image representation and robust encryption. The healthcare sector, with its specific security needs, has been addressed by Panwar et al [41]. They developed a multilevel secure information communication model tailored for healthcare systems, ensuring patient confidentiality and data integrity.…”

Section: Table 1 (Continued)mentioning

confidence: 99%

A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

Wang,

Tabassum

2024

CMC

View full text Add to dashboard Cite

show abstract

“…With the fast growth in telemedicine applications, the communication of a patient's diagnostic medical data has become more common in the healthcare sector [8], [9]. Technically, healthcare data should be secured using potential techniques of security, which provide more protection for sensitive data from various attacks [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

Secure Euclidean random distribution for patients’ magnetic resonance imaging privacy protection

Tayh Albderi,

Ben Said

2024

Bulletin EEI

View full text Add to dashboard Cite

Patients’ information and images transfer among medical institutes represent a major tool for delivering better healthcare services. However, privacy and security for healthcare information are big challenges in telemedicine. Evidently, even a small change in patients’ information might lead to wrong diagnosis. This paper suggests a new model for hiding patient information inside magnetic resonance imaging (MRI) cover image based on Euclidean distribution. Both least signification bit (LSB) and most signification bit (MSB) techniques are implemented for the physical hiding. A new method is proposed with a very high level of security information based on distributing the secret text in a random way on the cover image. Experimentally, the proposed method has high peak signal to noise ratio (PSNR), structural similarity index metric (SSIM) and reduced mean square error (MSE). Finally, the obtained results are compared with approaches in the last five years and found to be better by increasing the security for patient information for telemedicine.

show abstract

“…Secret text transfer over the network has increased significantly. Digital images represent the most cover material to hide secret text and send/receive over the networks [1]. This secure activity faces big challenges as a result of the potential number of hackers and organizations trying their best to intrude and obtain this private information [2][3] [4].…”

Section: Introductionmentioning

confidence: 99%

Hilbert Convex Similarity for Highly Secure Random Distribution of Patient Privacy Steganography

Alzubaidy,

Al-Shammary,

Abed

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Based on Hilbert Random Secure Distribution, a novel data-hiding method for embedding secret information about the patient in a cover image MRI sample has been proposed. Least significant bit (LSB) and most significant bit (MSB) techniques are applied for the physical hiding. Medical images confidentiality suffers from potential attacks and tracing by an unauthorized access. Technically, distributing the secret text in a random way on the cover image is the core security function of the proposed model. In order to evaluate the performance of the proposed solution, three quality metrics: Peak signal to noise ratio (PSNR), Mean Square Error (MSE) , percentage residual difference (PRD) and Structural Similarity Index measure (SSIM) were computed and compared on ten MRI images. Experimental results showed significant results in comparison with other models and reached average PSNR up to 61 db. Furthermore, the security analysis in case of 512 × 512 image samples show complex probability of distribution based on the Hilbert space model.

show abstract

RETRACTED ARTICLE: A multilevel secure information communication model for healthcare systems

Cited by 9 publications

References 38 publications

A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

Secure Euclidean random distribution for patients’ magnetic resonance imaging privacy protection

Hilbert Convex Similarity for Highly Secure Random Distribution of Patient Privacy Steganography

Contact Info

Product

Resources

About