A Methodological Evaluation of Crypto-Watermarking System for Medical Images

Health care institution demands exchange of medical images of number of patients to sought opinions from different experts. In order to reduce storage and for secure transmission of the medical images, Crypto-Watermarking techniques are adopted. The system is considered to be combinations of encryption technique with watermarking or steganography means adopted for safe transfer of medical images along with embedding of optional medical information. The Digital Watermarking is the process of embedding data to multimedia content. This can be done in spatial as well as frequency domain of the cover image to be transmitted. The robustness against attacks is ensured while embedding the encrypted data into transform domain, the encrypted data can be any secret key for the content recovery or patient record or the image itself. This chapter presents basic aspects of crypto-watermarking technique, as an application. It gives a detailed assessment on different approaches of crypto-watermarking for secure transmission of medical images and elaborates a case study on it.

Trust, Privacy, Issues in Cloud-Based Healthcare Services

In recent era individuals and organizations are migrating towards the cloud computing services to store and retrieve the data or services. However, they have less confidence on cloud as all the task are handled by the service provider without any involvement of the data owner. Cloud system provides features to the owner, to store their data on some remote locations and allow only authorized users to access the data according to the role, access capability or attribute they possess. Storing the personal health records on cloud server (third party) is a promising model for healthcare services to exchange information with the help of cloud provider. In this chapter, we highlight the various security issues and concerns such as trust, privacy and access control in cloud based healthcare system that needs to be known while storing the patient's information over a cloud system.

Cloud Based Secure Data Sharing Algorithm for Health Care

Cloud computing is one of most fast developing technology and many organizations are now offering a wide range of cloud services. Although the services provided are the same there is no common programming language, technology and protocol to access the entirety of the cloud services. Client who use a service provided by a certain organization are often limited and confined to that specific organization its structure and technologies. A Cloud federation is one solution to that interoperability through which computing resources of one Cloud Service Provider is rented or sold to another service provider or the services provided by one Cloud Service Provider is replicated into another Cloud Service Provider without having to lose any functionality and performance. This process is a tedious task and is prone to multiple limitations. In this paper we proposed the architectural framework and algorithm for the possible interoperability between the cloud service providers based on SLA in prospective of health sector as the application of cloud in health sector is highly needed in future.

Personalized Neuro-Fuzzy Expert System for Determination of Nutrient Requirements

In the modern fast and stressful life, an individual does not have time to take an extra care for one's self. Support from general information about health and nutrient requirement through modern computing infrastructure is very limited and common. Generic information on the Web and other media sometime raises genuine queries about the good health. Further, typical solutions available may not interact with users in friendly way and deal with vague inputs provided by users. To resolve this issue, a system is required which knows its users, acts smartly and friendly, learns from past data & history and provides customised advisory. This chapter introduces a neuro-fuzzy architecture, based on which an expert system for determination of nutrient requirements is presented. The chapter includes in depth literature survey, concepts, implementation details with sample code, neural network structure, fuzzy membership functions used, sample input–output screens of the system and future work.

Data Protection and Security Issues in Social Media

Cloud Computing changes the way Information Technology (IT) is expended and oversaw, promising enhanced cost efficiencies, quickened advancement, quicker time-to-market, and the capacity to scale applications of interest (Leighton, 2009). Users have started to explore new ways to interact with each other with the omnipresent nature of Social Networks and Cloud Computing. Facebook, YouTube, Orkut, Twitter, Flickr, Google+, Four Square, Pinterest, and the likes have distorted the way the Internet (Social Cloud) is being used. However, there is an absence of comprehension of protection and security issues of online networking. The protection and security of online networking should be explored, concentrated on and portrayed from different viewpoints (PCs, social, mental and so on). It is basic to distinguish security dangers and shield protection through constant and adaptable frameworks. Subsequent to there is no intelligent limits of the social networking, it is vital to consider the issue from a worldwide viewpoint as well.

IBM's Watson Analytics for Health Care

With the advent of Internet and Computers, Information Technology (IT) has become a major tool to aid medical issues. IBM Watson is one such initiative by IBM, which provides integration with any application to build Internet of Things (IoT), based health applications and also assists by its existing services. The strength of Watson is its data analytics and Artificial Intelligence. The four variants of Watsons are Watson Discovery Advisor, Oncology, Clinical Trial Matching and Curam. It is based on Open Source Apache UIMA, Apache Lucene. Its integration with IBM Bluemix Cloud, Platform as a Service (PaaS) makes it easily available to users.

Diabetes Patients Monitoring by Cloud Computing

The healthcare system is important due to the focus on human care and the interference with human lives. In recent years, we have witnessed a rapid rise in e-healthcare technologies such as Electronic Health Records (EHR) and the importance of emergency detection and response. Cloud computing is one of the new approaches in distributed systems that can handle some of the challenges of smart healthcare in terms of security, sharing, integration and management. In this study, an architecture design of a cloud-based pervasive healthcare system for diabetes treatment has been proposed. For this, three different components are defined as follows: (1) The home context manager which gathers necessary information from patients while simultaneously providing feedback, (2) a patient health record manager that is accessible by nurses or physicians at the hospital, and (3) a diabetes management system which is located with the cloud infra-structure for managing and accessing patient's information. The performance of proposed architecture is demonstrated through a user scenario.

Cloud Based Wireless Infrastructure for Health Monitoring

The wireless infrastructure based devices can collect data for long period of time even with a tiny power source as they perform specific function of collection of health related data and sending to gateways. The sensing data of healthcare monitoring consumes low power but they had limited computation power to process this data, where the cloud computing plays a vital role and compliment the loophole of wireless infrastructure based systems. In cloud computing with its immense computation power for easily deployment of healthcare monitoring algorithms and helps to process sensed data. As these two technologies did great jobs in their respective fields a conflate framework of these two technologies may lead to a great architecture for healthcare applications. This chapter reviews complete state-of-the-art and several use cases related to healthcare monitoring using different wireless infrastructure and adapting cloud based technologies in providing the healthcare services.

Big Data Analytics for Childhood Pneumonia Monitoring

In developing countries pediatric pneumonia is the second leading cause of deaths and 98% of pneumonia-induced deaths are identified across the world. It is mandatory to identify the symptoms of pneumonia in children to avoid mortality causing complications. Early identification of children at risk for treatment failure or at increased risk for death will help to improve overall health outcomes. If pneumonia is suspected, it is important to seek medical attention promptly so that an accurate diagnosis can be made and appropriate treatment is given in time. The proposed approach quickly provides history of previous patient's details, expert doctor's opinions who are in globe and their previous treatment for the same symptoms, all diagnostic reports such as blood tests, x-ray etc., from the cloud and gives analytics from big data to take fast and precise decisions by the doctors.

An Adaptive Cloud Proto Type Model for Health Care System

In the current Information Technology virtualization is one of the key components during the performance evaluation of network enabled environment including distributed computing, cloud computing, grid computing or pervasive computing. The network administrators and forensic teams are working on software defined networking (SDN) using which the network components can be controlled and managed using virtual infrastructure and global view of the physical network. On the physical implementation viewpoint, the single error or oversight can be damage the entire network integration. Now days, the advent of SDN products are being used in the research, development and corporate industry so that the effective control including routing, scheduling, security and related algorithms can be implemented on real networks. There are number of real life applications where the software defined networking and service oriented architecture (SOA) can be implemented for the social and global cause. Medical and Health Care Service is one of the key domain can make use SDN approach in which the number of medical decisions are to be taken based availability of the enterprise information. In this research work, the case analysis and a prototype for health care management service is accomplished. In this chapter, a unique and pragmatic implementation of the SDN based on virtualization is done and the prototype which we proposed in this chapter will be validated in future by using mininet-openflow integration to evaluate the performance of network and data packets transmission.