Biblio

Healthcare Internet of Things (HIoT) is transforming healthcare industry by providing large scale connectivity for medical devices, patients, physicians, clinical and nursing staff who use them and facilitate real-time monitoring based on the information gathered from the connected things. Heterogeneity and vastness of this network provide both opportunity and challenges for information collection and sharing. Patient-centric information such as health status and medical devices used by them must be protected to respect their safety and privacy, while healthcare knowledge should be shared in confidence by experts for healthcare innovation and timely treatment of patients. In this paper an overview of HIoT is given, emphasizing its characteristics to those of Big Data, and a security and privacy architecture is proposed for it. Context-sensitive role-based access control scheme is discussed to ensure that HIoT is reliable, provides data privacy, and achieves regulatory compliance.

The panic among medical control, information, and device administrators is due to surmounting number of high-profile attacks on healthcare facilities. This hostile situation is going to lead the health informatics industry to cloud-hoarding of medical data, control flows, and site governance. While different healthcare enterprises opt for cloud-based solutions, it is a matter of time when fog computing environment are formed. Because of major gaps in reported techniques for fog security administration for health data i.e. absence of an overarching certification authority (CA), the security provisioning is one of the the issue that we address in this paper. We propose a security provisioning model (AZSPM) for medical devices in fog environments. We propose that the AZSPM can be build by using atomic security components that are dynamically composed. The verification of authenticity of the atomic components, for trust sake, is performed by calculating the processor clock cycles from service execution at the resident hardware platform. This verification is performed in the fully sand boxed environment. The results of the execution cycles are matched with the service specifications from the manufacturer before forwarding the mobile services to the healthcare cloud-lets. The proposed model is completely novel in the fog computing environments. We aim at building the prototype based on this model in a healthcare information system environment.

Differential privacy is an approach that preserves patient privacy while permitting researchers access to medical data. This paper presents mechanisms proposed to satisfy differential privacy while answering a given workload of range queries. Representing input data as a vector of counts, these methods partition the vector according to relationships between the data and the ranges of the given queries. After partitioning the vector into buckets, the counts of each bucket are estimated privately and split among the bucket's positions to answer the given query set. The performance of the proposed method was evaluated using different workloads over several attributes. The results show that partitioning the vector based on the data can produce more accurate answers, while partitioning the vector based on the given workload improves privacy. This paper's two main contributions are: (1) improving earlier work on partitioning mechanisms by building a greedy algorithm to partition the counts' vector efficiently, and (2) its adaptive algorithm considers the sensitivity of the given queries before providing results.

Mobile Healthcare Networks (MHN) continuouslycollect the patients' health data sensed by wearable devices, andanalyze the collected data pre-processed by servers combinedwith medical histories, such that disease diagnosis and treatmentare improved, and the heavy burden on the existing healthservices is released. However, the network is vulnerable to Sybilattacks, which would degrade network performance, disruptproceedings, manipulate data or cheat others maliciously. What'smore, the user is reluctant to leak identity privacy, so the identityprivacy preserving makes Sybil defenses more difficult. One ofthe best choices is mutually authenticating each other with noidentity information involved. Thus, we propose a fine-grainedauthentication scheme based on Attribute-Based Signature (ABS)using lattice assumption, where a signer is authorized by an at-tribute set instead of single identity string. This ABS scheme usesFiat-Shamir framework and supports flexible threshold signaturepredicates. Moreover, to anonymously guarantee integrity andavailability of health data in MHN, we design an anonymousanti-Sybil attack protocol based on our ABS scheme, so thatSybil attacks are prevented. As there is no linkability betweenidentities and services, the users' identity privacy is protected. Finally, we have analyzed the security and simulated the runningtime for our proposed ABS scheme.

In recent years a wide range of wearable IoT healthcare applications have been developed and deployed. The rapid increase in wearable devices allows the transfer of patient personal information between different devices, at the same time personal health and wellness information of patients can be tracked and attacked. There are many techniques that are used for protecting patient information in medical and wearable devices. In this research a comparative study of the complexity for cyber security architecture and its application in IoT healthcare industry has been carried out. The objective of the study is for protecting healthcare industry from cyber attacks focusing on IoT based healthcare devices. The design has been implemented on Xilinx Zynq-7000, targeting XC7Z030 - 3fbg676 FPGA device.

More and more medical data are shared, which leads to disclosure of personal privacy information. Therefore, the construction of medical data privacy preserving publishing model is of great value: not only to make a non-correspondence between the released information and personal identity, but also to maintain the data utility after anonymity. However, there is an inherent contradiction between the anonymity and the data utility. In this paper, a Principal Component Analysis-Grey Relational Analysis (PCA-GRA) K anonymous algorithm is proposed to improve the data utility effectively under the premise of anonymity, in which the association between quasi-identifiers and the sensitive information is reckoned as a criterion to control the generalization hierarchy. Compared with the previous anonymity algorithms, results show that the proposed PCA-GRA K anonymous algorithm has achieved significant improvement in data utility from three aspects, namely information loss, feature maintenance and classification evaluation performance.

The Information Centric Networking (ICN) is a novel concept of a large scale ecosystem of wireless actuators and computing technologies. ICN technologies are getting popular in the development of various applications to bring day-to-day comfort and ease in human life. The e-healthcare monitoring services is a subset of ICN services which has been utilized to monitor patient's health condition in a smart and ubiquitous way. However, there are several challenges and attacks on ICN. In this paper we have discussed ICN attacks and ICN based healthcare scenario. We have proposed a novel ICN stack for healthcare scenario for securing biomedical data communication instead of communication networks. However, the biomedical data communication between patient and Doctor requires reliable and secure networks for the global access.

Recent advances in Wireless Sensor Networks have given rise to many application areas in healthcare such as the new field of Wireless Body Area Networks. The health status of humans can be tracked and monitored using wearable and non-wearable sensor devices. Security in WBAN is very important to guarantee and protect the patient's personal sensitive data and establishing secure communications between BAN sensors and external users is key to addressing prevalent security and privacy concerns. In this paper, we propose secure and efficient key management scheme based on ECC algorithm to protect patient's medical information in healthcare system. Our scheme divided into three phases as setup, registration, verification and key exchange. And we use the identification code which is the SIM card number on a patient's smart phone with the private key generated by the legal use instead of the third party. Also to prevent the replay attack, we use counter number at every process of authenticated message exchange to resist.