Browsing by Author "Mutandavari, Mainford"

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Enhancing Security in Electronic Health Records using AES and PBKDF2: A case study of Zimbabwe e-health system
(IST-Africa, 2018-01-28) Mutandavari, Mainford; Matema, Chantel; Gotora, Tatenda; Mukosera, Macdonald; Manjoro, Wellington
As health IT is evolving, the use of traditional methods of storing patient information is being phased out. Notably Zimbabwe has begun digitalizing its medical records in most private and public health centres but limited internet connectivity and patient data harmonisation is still an issue. The viable solution lies in adopting Electronic Health Records (EHRs) which promote data sharing across healthcare providers while also ensuring data integrity and availability. Despite the many efforts by various researchers in suggesting strong encryption and biometric techniques to circumvent data loss or hacks, cyber criminals are getting more experienced due to the availability of more exploitation tools. This technical research presents an analysis of some of the widely implemented security techniques used in securing EHRs and proposes an enhanced hybrid mechanism for EHRs using AES and PBKDF2 within the Zimbabwe health care context. Observations made indicate the enhancement of data integrity, authentication and improved service delivery within the private and public health set up. Furthermore if scaled the e-health platform requires rigorous health personnel training in usage and changing mentality towards user acceptance.
A Survey of the Security Use Cases in Big Data
(International Journal of Innovative Research in Computer and Communication Engineering, 2014-05-01) Zvarevashe, Kudakwashe; Mutandavari, Mainford; Gotora, Trust
Big data is the collection of large and complex data sets that are difficult to process using on-hand database management tools or traditional data processing applications. The invention of online social networks, smart phones, fine tuning of ubiquitous computing and many other technological advancements have led to the generation of multiple petabytes of both structured, unstructured and semi-structured data. These massive data sets have lead to the birth of some distributed data processing and storage technologies like Apache Hadoop and MongoDB. To tackle the security issues in Hadoop, the Kerberos protocol has been introduced in its second edition. However, this technological movement has created some security loopholes in the processing and storage of the data sets. This paper tries to list some of the directions research on Big Data challenges has taken for the past five years together with their corresponding Use cases.
Towards More Efficient DSP Implementations: An Analysis into the Sources of Error in DSP Design
(International Journal of Innovative Research in Computer and Communication Engineering, 2014-05-12) Zwavashe, Tinotenda; Duri, Rudo; Mutandavari, Mainford
This paper aims to highlight the commonly encountered sources of errors in Digital Signal Processing applications. Digital signal processing now finds application in a variety of fields due to the simplicity of handling digital signals and many more advantages which come with digital signals over analogue signals (as shall be specified in the introduction). As designers and scholars become more aware of the sources of errors in the processing of digital signals then the efficiency and accuracy of computed results increases. The knowledge also, in some way, aid in the efficient utilization of the available system resources as people become more aware of the overall system being required and the performance characteristics expected while taking down erroneous values to their minimum possible levels. The approach used will take into account the architecture of the Digital Signal Processing system and then analyze the causes of erroneous output from the system by taking into consideration the building blocks of the DSP system.