Biblio
Tele-radiology is a technology that helps in bringing the communication between the radiologist, patients and healthcare units situated at distant places. This involves exchange of medical centric data. The medical data may be stored as Electronic Health Records (EHR). These EHRs contain X-Rays, CT scans, MRI reports. Hundreds of scans across multiple radiology centers lead to medical big data (MBD). Healthcare Cloud can be used to handle MBD. Since lack of security to EHRs can cause havoc in medical IT, healthcare cloud must be secure. It should ensure secure sharing and storage of EHRs. This paper proposes the application of decoy technique to provide security to EHRs. The EHRs have the risk of internal attacks and external intrusion. This work addresses and handles internal attacks. It also involves study on honey-pots and intrusion detection techniques. Further it identifies the possibility of an intrusion and alerts the administrator. Also the details of intrusions are logged.
The ultrafast active cavitation imaging (UACI) based on plane wave can be implemented with high frame rate, in which adaptive beamforming technique was introduced to enhance resolutions and signal-to-noise ratio (SNR) of images. However, regular adaptive beamforming continuously updates the spatial filter for each sample point, which requires a huge amount of calculation, especially in the case of a high sampling rate, and, moreover, 3D imaging. In order to achieve UACI rapidly with satisfactory resolution and SNR, this paper proposed an adaptive beamforming on the basis of compressive sensing (CS), which can retain the quality of adaptive beamforming but reduce the calculating amount substantially. The results of simulations and experiments showed that comparing with regular adaptive beamforming, this new method successfully achieved about eightfold in time consuming.
In this paper, we investigate the performance of multiple-input multiple-output aided coded interleave division multiple access (IDMA) system for secured medical image transmission through wireless communication. We realize the MIMO profile using four transmit antennas at the base station and three receive antennas at the mobile station. We achieve bandwidth efficiency using discrete wavelet transform (DWT). Further we implement Arnold's Cat Map (ACM) encryption algorithm for secured medical transmission. We consider celulas as medical image which is used to differentiate between normal cell and carcinogenic cell. In order to accommodate more users' image, we consider IDMA as accessing scheme. At the mobile station (MS), we employ non-linear minimum mean square error (MMSE) detection algorithm to alleviate the effects of unwanted multiple users image information and multi-stream interference (MSI) in the context of downlink transmission. In particular, we investigate the effects of three types of delay-spread distributions pertaining to Stanford university interim (SUI) channel models for encrypted image transmission of MIMO-IDMA system. From our computer simulation, we reveal that DWT based coded MIMO- IDMA system with ACM provides superior picture quality in the context of DL communication while offering higher spectral efficiency and security.
Integrity of image data plays an important role in data communication. Image data contain confidential information so it is very important to protect data from intruder. When data is transmitted through the network, there may be possibility that data may be get lost or damaged. Existing system does not provide all functionality for securing image during transmission. i.e image compression, encryption and user authentication. In this paper hybrid cryptosystem is proposed in which biometric fingerprint is used for key generation which is further useful for encryption purpose. Secret fragment visible mosaic image method is used for secure transmission of image. For reducing the size of image lossless compression technique is used which leads to the fast transmission of image data through transmission channel. The biometric fingerprint is useful for authentication purpose. Biometric method is more secure method of authentication because it requires physical presence of human being and it is untraceable.
Using heterogeneous clouds has been considered to improve performance of big-data analytics for healthcare platforms. However, the problem of the delay when transferring big-data over the network needs to be addressed. The purpose of this paper is to analyze and compare existing cloud computing environments (PaaS, IaaS) in order to implement middleware services. Understanding the differences and similarities between cloud technologies will help in the interconnection of healthcare platforms. The paper provides a general overview of the techniques and interfaces for cloud computing middleware services, and proposes a cloud architecture for healthcare. Cloud middleware enables heterogeneous devices to act as data sources and to integrate data from other healthcare platforms, but specific APIs need to be developed. Furthermore, security and management problems need to be addressed, given the heterogeneous nature of the communication and computing environment. The present paper fills a gap in the electronic healthcare register literature by providing an overview of cloud computing middleware services and standardized interfaces for the integration with medical devices.