Biblio

Mobile healthcare (mHealth) application and technologies have promised their cost-effectiveness to enhance healthcare quality, particularly in rural areas. However, the increased security incidents and leakage of patient data raise the concerns to address security risks and privacy issues of mhealth applications urgently. While recent mobile health applications that rely on password-based authentication cannot withstand password guessing and cracking attacks, several countermeasures such as One-Time Password (OTP), grid-based password, and biometric authentication have recently been implemented to protect mobile health applications. These countermeasures, however, can be thwarted by brute force attacks, man-in-the-middle attacks and persistent malware attacks. This paper proposed grid-based honey encryption by hybridising honey encryption with grid-based authentication. Compared to recent honey encryption limited in the hardening password attacks process, the proposed grid-based honey encryption can be further employed against shoulder surfing, smudge and replay attacks. Instead of rejecting access as a recent security defence mechanism in mobile healthcare applications, the proposed Grid-based Honey Encryption creates an indistinct counterfeit patient's record closely resembling the real patients' records in light of each off-base speculation legitimate password.

mHealth apps have a vital role in facilitation of human health management. Users have to enter sensitive health related information in these apps to fully utilize their functionality. Unauthorized sharing of sensitive health information is undesirable by the users. mHealth apps also collect data other than that required for their functionality like surfing behavior of a user or hardware details of devices used. mHealth software and their developers also share such data with third parties for reasons other than medical support provision to the user, like advertisements of medicine and health insurance plans. Existence of a comprehensive and easy to understand data privacy policy, on user data acquisition, sharing and management is a salient requirement of modern user privacy protection demands. Readability is one parameter by which ease of understanding of privacy policy is determined. In this research, privacy policies of 27 free Android, medical apps are analyzed. Apps having user rating of 4.0 and downloads of 1 Million or more are included in data set of this research.RGL, Flesch-Kincaid Reading Grade Level, SMOG, Gunning Fox, Word Count, and Flesch Reading Ease of privacy policies are calculated. Average Reading Grade Level of privacy policies is 8.5. It is slightly greater than average adult RGL in the US. Free mHealth apps have a large number of users in other, less educated parts of the World. Privacy policies with an average RGL of 8.5 may be difficult to comprehend in less educated populations.

Community Health Workers (CHWs) have been using Mobile Health Data Collection Systems (MDCSs) for supporting the delivery of primary healthcare and carrying out public health surveys, feeding national-level databases with families' personal data. Such systems are used for public surveillance and to manage sensitive data (i.e., health data), so addressing the privacy issues is crucial for successfully deploying MDCSs. In this paper we present a comprehensive privacy threat analysis for MDCSs, discuss the privacy challenges and provide recommendations that are specially useful to health managers and developers. We ground our analysis on a large-scale MDCS used for primary care (GeoHealth) and a well-known Privacy Impact Assessment (PIA) methodology. The threat analysis is based on a compilation of relevant privacy threats from the literature as well as brain-storming sessions with privacy and security experts. Among the main findings, we observe that existing MDCSs do not employ adequate controls for achieving transparency and interveinability. Thus, threatening fundamental privacy principles regarded as data quality, right to access and right to object. Furthermore, it is noticeable that although there has been significant research to deal with data security issues, the attention with privacy in its multiple dimensions is prominently lacking.