Reliable Medical Image Communication in Healthcare IoT

2019 ◽  
pp. 1-26 ◽  
Author(s):  
Siva Janakiraman ◽  
Sundararaman Rajagopalan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Secure Communication ◽  
Medical Image ◽  
Personal Information ◽  
Medical Diagnostics ◽  
Medical Field ◽  
Reliable Communication ◽  
Pixel Resolution ◽  
Image Communication ◽  
Iot Applications ◽  
Performance Validation

Images have been widely used in the medical field for various diagnostic purposes. In the field of healthcare IoT, secure communication of a medical image concerned with an individual is a crucial task. Embedding patients' personal information as an invisible watermark in their medical images helps to authenticate the ownership identification process. Reliable communication of medical image can be thereby ensured concerning authentication and integrity. Images in DICOM format with a pixel resolution of 8-bit depth are used for medical diagnostics. This chapter deals about the development of a lightweight algorithm to insert patients' identities as an invisible watermark in random edge pixels of DICOM images. This chapter describes the implementation of the proposed lightweight watermarking algorithm on a RISC microcontroller suitable for healthcare IoT applications. Imperceptibility level of the watermarked medical image was analyzed besides its lightweight performance validation on the constrained IoT platform.

Secured Medical Image Hashing Based on Frequency Domain with Chaotic Map

2021 ◽  
Vol 39 (5A) ◽  
pp. 711-722
Author(s):  
Amira K. Jabbar ◽  
Ashwaq T. Hashim ◽  
Qusay F. Al-Doori
Keyword(s):  
Medical Image ◽  
Personal Information ◽  
Chaotic Map ◽  
Region Of Interest ◽  
Image Hashing ◽  
Medical Field ◽  
Hash Algorithm ◽  
Frequency Domains ◽  
Hash Code ◽  
Shift Keying

Recently, online-medicine got increased global interest, particularly during COVID19 pandemic. Data protection is important in the medical field since when promoting telemedicine applications, it is necessary to protect the patient data and personal information. A secured process is needed to transmit medical images over the Internet. In this paper hash algorithm is employed to protect the data by using powerful features from the coupled frequency domains of the Slantlet Transformation (SLT) and the Discrete Cosine Transform (DCT). The Region of Interest (ROI) is localized from an MRI image then extraction of a feature set is performed for calculating the hash code. Then, hash code is enciphered to maintain security by employing a secure Chaotic Shift Keying (CSK). The suggested method of security is ensured by the strength of the CSK and the encryption key secrecy.  A detailed analysis was conducted using 1000 uncompressed images that were chosen randomly from a publicly available AANLIB database. The proposed methodology can be useful for JPEG compression. Also, this method could resist many attacks of image processing likes filtering, noise addition, and some geometric transforms.

scholarly journals Mitigating the Impact on Users’ Privacy Caused by over Specifications in the Design of IoT Applications

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4318 ◽  
Author(s):  
Alfredo Pérez Fernández ◽  
Guttorm Sindre
Keyword(s):  
Life Cycle ◽  
Positive Impact ◽  
System Development ◽  
Personal Information ◽  
The Other ◽  
Iot Applications ◽  
Design Time ◽  
It Systems ◽  
Development Life Cycle ◽  
The Impact

Privacy has long been an important issue for IT systems that handle personal information, and is further aggravated as technology for collecting and analyzing massive amounts of data is becoming increasingly effective. There are methods to help practitioners analyze the privacy implications of a system during the design time. However, this is still a difficult task, especially when dealing with Internet of Things scenarios. The problem of privacy can become even more unmanageable with the introduction of overspecifications during the system development life cycle. In this paper, we carried out a controlled experiment with students performing an analysis of privacy implications using two different methods. One method aims at reducing the impact of overspecifications through the application of a goal-oriented analysis. The other method does not involve a goal-oriented analysis and is used as a control. Our initial findings show that conducting a goal-oriented analysis early during design time can have a positive impact over the privacy friendliness of the resulting system.

scholarly journals Elliptic Curve Blended Cross Chaos Based Secure Image Communication

2019 ◽  
Vol 8 (3) ◽  
pp. 4481-4484
Keyword(s):  
Elliptic Curve ◽  
Image Encryption ◽  
Elliptic Curve Cryptography ◽  
Secure Communication ◽  
Chaotic Map ◽  
Chaotic Sequence ◽  
Symmetric Encryption ◽  
Image Communication ◽  
Chaotic Sequences ◽  
Asymmetric Encryption

Image encryption has proven a successful method to communicate the confidential information. Some of the images may or may not be confidential. So there is a need to secure the confidential images. Initially, symmetric encryption is used for security purpose. But it has the problem that if the key is revealed the interceptors can immediately decode it. To make the key transformation more secure, asymmetric encryption is introduced. In this two different keys are used for encoding and decoding. So even the interceptors hacked the key it cannot be possible to decode. In this project Elliptic Curve Cryptography (ECC) is utilized for generating the keys and the cross chaotic map used for generating the chaotic sequence. These chaotic sequences are utilized to encode the image for secure communication.

scholarly journals Performance Improvement for Medical Image Transmission Systems using Turbo-Trellis Coded Modulation (TTCM)

2021 ◽  
Vol 11 (2) ◽  
pp. 6965-6569
Author(s):  
M. Fayssal ◽  
B. M. Sofiane ◽  
Z. Mahdjoub ◽  
M. R. Lahcene ◽  
A. Zerroug
Keyword(s):  
Medical Image ◽  
Digital Images ◽  
Turbo Code ◽  
Error Correcting Code ◽  
Image Transmission ◽  
Transmission System ◽  
Coded Modulation ◽  
Medical Field ◽  
Trellis Coded Modulation ◽  
Trellis Coded

Digital images have become an essential working tool in several areas such as the medical field, the satellite and astronomical field, film production, etc. The efficiency of a transmission system to exchange digital images is crucial to allow better and accurate reception. Generally, transmitted images are infected with noise. In the medical field, this noise makes the process of diagnosing difficult. To eliminate the transmission errors, an Error Correcting Code (ECC) can be used with the aim to guarantee excellent reception of the images and allowing a good diagnosis. In this paper, source and channel encoding/ decoding functions are studied during medical image transmission (LUNG). At first, the Turbo-Code (TC) is used as ECC and subsequently the Turbo-Trellis Coded Modulation (TTCM). The simulation results represent the curves giving the Bit Error Rate (BER) as a function of the signal to noise ratio (Eb/N0). In order to compare these two systems properly, the MSSIM (Mean Structural Similarity) parameter was used. The obtained results showed the effect and importance of ECC on the transmission of medical images using TTCM which gave better results compared to TC with regard to increasing the performance of the transmission system by eliminating transmission noise.

scholarly journals Blockchain-Based Reversible Data Hiding for Securing Medical Images

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Ji-Hwei Horng ◽  
Ching-Chun Chang ◽  
Guan-Long Li ◽  
Wai-Kong Lee ◽  
Seong Oun Hwang
Keyword(s):  
Data Hiding ◽  
Private Information ◽  
Medical Diagnosis ◽  
Reversible Data Hiding ◽  
Secure Communication ◽  
Medical Images ◽  
Personal Information ◽  
Embedding Capacity ◽  
Image Block ◽  
Encrypted Images

Medical images carry a lot of important information for making a medical diagnosis. Since the medical images need to be communicated frequently to allow timely and accurate diagnosis, it has become a target for malicious attacks. Hence, medical images are protected through encryption algorithms. Recently, reversible data hiding on the encrypted images (RDHEI) schemes are employed to embed private information into the medical images. This allows effective and secure communication, wherein the privately embedded information (e.g., medical records and personal information) is very useful to the medical diagnosis. However, existing RDHEI schemes still suffer from low embedding capacity, which limits their applicability. Besides, such solution still lacks a good mechanism to ensure its integrity and traceability. To resolve these issues, a novel approach based on image block-wise encryption and histogram shifting is proposed to provide more embedding capacity in the encrypted images. The embedding rate is over 0.8 bpp for typical medical images. On top of that, a blockchain-based system for RDHEI is proposed to resolve the traceability. The private information is stored on the blockchain together with the hash value of the original medical image. This allows traceability of all the medical images communicated over the proposed blockchain network.

scholarly journals Denoising of MRI Brain Images using Adaptive Clahe Filtering Method

2019 ◽  
Vol 9 (1S) ◽  
pp. 91-95
Keyword(s):  
Contrast Enhancement ◽  
Medical Image ◽  
Signal To Noise Ratio ◽  
Medical Image Analysis ◽  
Medical Field ◽  
Brain Images ◽  
Process Computer ◽  
Cancerous Cells ◽  
Mri Brain Images

Image processing is a method of making the quality of an image better after removing unwanted information from image in various applications and domains to process computer effectively. Enhancement is, used to improve the quality effects of an image for further analysis. Enhancement of image can be done by filtering, de noising and contrast enhancement. Even though contrast enhancement of images is applied in different fields it is used effectively in the medical field. Medical Imaging is now recently used in most of the applications like Radiography, MRI, Nuclear medicine, Ultrasound Imaging, Tomography, Cardiograph, and Fundus Imagery and so on. The main problem in analysis of medical images is the poor contras .in medical image analysis the detection of tumor, cancerous cells, malignant or benign has to be classified effectively. In this paper various spatial domain techniques and their effectiveness in terms of quality improvement are discussed. The measuring metrics used for comparing different methods are parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE), DICE coefficient, etc,.

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