Healthcare Data Protection Using Cellular Automata Encryption Techniques

Author(s):  
Manisankar Sannigrahi ◽  
Suneeta Mohanty ◽  
Prasant Kumar Pattnaik
2007 ◽  
Vol 14 (2) ◽  
pp. 189-195 ◽  
Author(s):  
Renate Gertz

AbstractOn the 1st of December 2006, the Court of Session in Edinburgh issued the first decision on Freedom of Information and health data regarding a request for information on incidences of childhood leukemia, in the range of 0 - 14 years, by year and census ward from 1990 to 2003 for the Dumfries and Galloway postal areas. The case, which provides an example for the collision course between the Freedom of Information and Data Protection regime, had been anticipated as a landmark decision, however, due to several problems and inconsistencies it sadly failed to meet those expectations.


Author(s):  
Jesus D. Terrazas Gonzalez ◽  
Witold Kinsner

This paper presents a new cryptosystem based on chaotic continuous-interval cellular automata (CCA) to increase data protection as demonstrated by their flexibility to encrypt and decrypt information from distinct sources. Enhancements to cryptosystems are also presented including (i) a model based on a new chaotic CCA attractor, (ii) the dynamical integration of modules containing dynamical systems to generate complex sequences, and (iii) an enhancement for symmetric cryptosystems by allowing them to generate an unlimited number of keys. This paper also presents a process of mixing chaotic sequences obtained from cellular automata, instead of using differential equations, as a basis to achieve higher security and higher speed for the encryption and decryption processes, as compared to other recent approaches. The complexity of the mixed sequences is measured using the variance fractal dimension trajectory to compare them to the unmixed chaotic sequences to verify that the former are more complex. This type of polyscale measure and evaluation has never been done in the past outside this research group.


2014 ◽  
Vol 177 (2) ◽  
pp. 510-511 ◽  
Author(s):  
Giuseppe Rosano ◽  
Francesco Pelliccia ◽  
Carlo Gaudio ◽  
Andrew J. Coats

2020 ◽  
Author(s):  
Dario Salvi ◽  
Carmelo Velardo ◽  
Arvin Rishi Goburdhun ◽  
Lionel Tarassenko

BACKGROUND The use of mobile phone apps and connected wearable devices offers a great opportunity for health research. In order make healthcare data accessible across organisations, physicians and patients, recent platforms like Apple HealthKit, Google Fit or Samsung Health allow to securely store and share health data among smartphone apps with the consent of the user. These mobile health records can be combined with software platforms, like ResearchKit and ResearchStack to simplify the development of research apps by providing ready-made common use cases while being compliant to regulations in data protection and health research. Even though a plethora of such platforms exist, none of them can be considered as a widely established tool yet. OBJECTIVE To provide recommendations for new platforms through the analysis of the limitations posed by existing platforms and by identifying common needs and established practices in mHealth development. METHODS We first analyse the state of the art of mobile-health development in research settings, including existing tools and frameworks to support it. To complement the scant literature, we disseminated a survey among mobile-health researchers and developers to understand best practices, what type of tools are used and which would be desirable. RESULTS Related to current practices and unmet needs in mHealth development we identify the following themes: a) costs and resources, b) usability and context awareness, c) middleware and software architectures, d) multi-platform support, e) mobile connectivity, f) reliability and testing, g) data protection and regulatory compliance and h) interoperability. In relation to existing platforms we identified these common shortcomings: 1) poor regulatory compliance, 2) lack of documentation, 3) low maturity, 4) poor usability (from the developer’s perspective) and intuitiveness. Our survey received 28 very varied responses, which identify a core of concerns shared for most of the reported projects and not entirely met by the current offer of development platforms. Based on these results, we provide recommendations for future mobile-health platforms, particularly focusing on multi-operating system support, integration with existing health records, regulatory compliance, involvement of stakeholders, modularity, extensibility and overall quality of the code base. CONCLUSIONS Our recommendations intend to guide the development of a platform to be used as a common tool for future research in mobile-health.


Author(s):  
Jesus D. Terrazas Gonzalez ◽  
Witold Kinsner

This paper presents a new cryptosystem based on chaotic continuous-interval cellular automata (CCA) to increase data protection as demonstrated by their flexibility to encrypt and decrypt information from distinct sources. Enhancements to cryptosystems are also presented including (i) a model based on a new chaotic CCA attractor, (ii) the dynamical integration of modules containing dynamical systems to generate complex sequences, and (iii) an enhancement for symmetric cryptosystems by allowing them to generate an unlimited number of keys. This paper also presents a process of mixing chaotic sequences obtained from cellular automata, instead of using differential equations, as a basis to achieve higher security and higher speed for the encryption and decryption processes, as compared to other recent approaches. The complexity of the mixed sequences is measured using the variance fractal dimension trajectory to compare them to the unmixed chaotic sequences to verify that the former are more complex. This type of polyscale measure and evaluation has never been done in the past outside this research group.


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