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With the widespread availability of cost effective wireless devices, the usage of such devices for the monitoring a patient's vital parameters have become ubiquitous. The use of such devices has given rise to Wireless Body Area Sensor Networks (WBASNs) that can enable a healthcare professional to remotely monitor an individual, thereby eliminating costly trips to the hospital. However, since WBASNs carry sensitive patient information, maintaining security is paramount. Public Key Cryptography (PKC) provides robust security than other cryptographic systems. However, PKC requires a substantial computational overhead to be effective which renders them unsuitable for low powered devices used in WBASNs. Elliptic Curve Cryptography (ECC) provides a computationally low overhead for achieving robust security. In this paper we define and propose a Modified Elliptic Curve Cryptography (MECC) technique for use in WBASNs. We also propose to use this method for the secure transmission of data to be used for the wireless monitoring of patients suffering from Parkinson's disease in an indoor environment such as the patient's residence or a hospice. Our system would continuously monitor a patient in real time and detect events that generally precede a fall or a Freezing of Gait (FoG).

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In the last decade, the rise of hosted Software-as-a-Service (SaaS) application programming interfaces (APIs) across both academia and industry has exploded, and simultaneously, microservice architectures have replaced monolithic application platforms for the flexibility and maintainability they offer. These SaaS APIs rely on small, independent and reusable microservices that can be assembled relatively easily into more complex applications. As a result, developers can focus on their own unique functionality and surround it with fully functional, distributed processes developed by other specialists, which they access through APIs. The Tapis framework, a NSF funded project, provides SaaS APIs to allow researchers to achieve faster scientific results, by eliminating the need to set up a complex infrastructure stack. In this paper, we describe the best practices followed to create Tapis APIs using Python and the Stream API as an example implementation illustrating authorization and authentication with the Tapis Security Kernel, Tenants and Tokens APIs, leveraging OpenAPI v3 specification for the API definitions and docker containerization. Finally, we discuss our deployment strategy with Kubernetes, which is an emerging orchestration technology and the early adopter use cases of the Streams API service.