Usability and Security in Medication Administration Applications

The traditional process of filling the medicine trays and dispensing the medicines to the patients in the hospitals is manually done by reading the printed paper medicine chart. This process can be very strenuous and error-prone, given the number of sub-tasks involved in the entire workflow and the dynamic nature of the work environment. Therefore, efforts are being made to digitalise the medication dispensation process by introducing a mobile application called Smart Dosing application. The introduction of the Smart Dosing application into hospital workflow raises security concerns and calls for security requirement analysis. This thesis is written as a part of the smart medication management project at Embedded Systems Laboratory, A° bo Akademi University. The project aims at digitising the medicine dispensation process by integrating information from various health systems, and making them available through the Smart Dosing application. This application is intended to be used on a tablet computer which will be incorporated on the medicine tray. The smart medication management system include the medicine tray, the tablet device, and the medicine cups with the cup holders. Introducing the Smart Dosing application should not interfere with the existing process carried out by the nurses, and it should result in minimum modifications to the tray design and the workflow. The re-designing of the tray would include integrating the device running the application into the tray in a manner that the users find it convenient and make less errors while using it. The main objective of this thesis is to enhance the security of the hospital medicine dispensation process by ensuring the security of the Smart Dosing application at various levels. The methods used for writing this thesis was to analyse how the tray design, and the application user interface design can help prevent errors and what secure technology choices have to be made before starting the development of the next prototype of the Smart Dosing application. The thesis first understands the context of the use of the application, the end-users and their needs, and the errors made in everyday medication dispensation workflow by continuous discussions with the nursing researchers. The thesis then gains insight to the vulnerabilities, threats and risks of using mobile application in hospital medication dispensation process. The resulting list of security requirements was made by analysing the previously built prototype of the Smart Dosing application, continuous interactive discussions with the nursing researchers, and an exhaustive stateof- the-art study on security risks of using mobile applications in hospital context. The thesis also uses Octave Allegro method to make the readers understand the likelihood and impact of threats, and what steps should be taken to prevent or fix them. The security requirements obtained, as a result, are a starting point for the developers of the next iteration of the prototype for the Smart Dosing application.

Usability and Security in Medication. Administration Applications

The traditional process of filling the medicine trays and dispensing the medicines to the patients in the hospitals is manually done by reading the printed paper medicinechart. This process can be very strenuous and error-prone, given the number of sub-tasksinvolved in the entire workflow and the dynamic nature of the work environment.Therefore, efforts are being made to digitalise the medication dispensation process byintroducing a mobile application called Smart Dosing application. The introduction ofthe Smart Dosing application into hospital workflow raises security concerns and callsfor security requirement analysis. This thesis is written as a part of the smart medication management project at EmbeddedSystems Laboratory, A˚bo Akademi University. The project aims at digitising the medicine dispensation process by integrating information from various health systems, and making them available through the Smart Dosing application. This application is intended to be used on a tablet computer which will be incorporated on the medicine tray. The smart medication management system include the medicine tray, the tablet device, and the medicine cups with the cup holders. Introducing the Smart Dosing application should not interfere with the existing process carried out by the nurses, and it should result in minimum modifications to the tray design and the workflow. The re-designing of the tray would include integrating the device running the application into the tray in a manner that the users find it convenient and make less errors while using it. The main objective of this thesis is to enhance the security of the hospital medicine dispensation process by ensuring the security of the Smart Dosing application at various levels. The methods used for writing this thesis was to analyse how the tray design, and the application user interface design can help prevent errors and what secure technology choices have to be made before starting the development of the next prototype of the Smart Dosing application. The thesis first understands the context of the use of the application, the end-users and their needs, and the errors made in everyday medication dispensation workflow by continuous discussions with the nursing researchers. The thesis then gains insight to the vulnerabilities, threats and risks of using mobile application in hospital medication dispensation process. The resulting list of security requirements was made by analysing the previously built prototype of the Smart Dosing application, continuous interactive discussions with the nursing researchers, and an exhaustive state-of-the-art study on security risks of using mobile applications in hospital context. The thesis also uses Octave Allegro method to make the readers understand the likelihood and impact of threats, and what steps should be taken to prevent or fix them. The security requirements obtained, as a result, are a starting point for the developers of the next iteration of the prototype for the Smart Dosing application.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Cyber foraging for green computing, improving performance and prolonging battery life of mobile devices

The increasing dependency of everyday life on mobile devices also increases the number and complexity of computing tasks to be supported by these devices. However, the inherent requirement of mobility restricts them from being resources rich both in terms of energy (battery capacity) and other computing resources such as processing capacity, memory and other resources. This thesis looks into cyber foraging technique of offloading computing tasks. Various experiments on android mobile devices are carried out to evaluate offloading benefits in terms of sustainability advantage, prolonging battery life and augmenting the performance of mobile devices. This thesis considers two scenarios of cyber foraging namely opportunistic offloading and competitive offloading. These results show that the offloading scenarios are important for both green computing and resource augmentation of mobile devices. A significant advantage in battery life gain and performance enhancement is obtained. Moreover, cyber foraging is proved to be efficient in minimizing energy consumption per computing tasks. The work is based on scavenger cyber foraging system. In addition, the work can be used as a basis for studying cyber foraging and other similar approaches such as mobile cloud/edge computing for internet of things devices and improving the user experiences of applications by minimizing latencies through the use of potential nearby surrogates.

Applying Augmented Reality to Outdoors Industrial Use

Augmented Reality (AR) is currently gaining popularity in multiple different fields. However, the technology for AR still requires development in both hardware and software when considering industrial use. In order to create immersive AR applications, more accurate pose estimation techniques to define virtual camera location are required. The algorithms for pose estimation often require a lot of processing power, which makes robust pose estimation a difficult task when using mobile devices or designated AR tools. The difficulties are even larger in outdoor scenarios where the environment can vary a lot and is often unprepared for AR. This thesis aims to research different possibilities for creating AR applications for outdoor environments. Both hardware and software solutions are considered, but the focus is more on software. The majority of the thesis focuses on different visual pose estimation and tracking techniques for natural features. During the thesis, multiple different solutions were tested for outdoor AR. One commercial AR SDK was tested, and three different custom software solutions were developed for an Android tablet. The custom software solutions were an algorithm for combining data from magnetometer and a gyroscope, a natural feature tracker and a tracker based on panorama images. The tracker based on panorama images was implemented based on an existing scientific publication, and the presented tracker was further developed by integrating it to Unity 3D and adding a possibility for augmenting content. This thesis concludes that AR is very close to becoming a usable tool for professional use. The commercial solutions currently available are not yet ready for creating tools for professional use, but especially for different visualization tasks some custom solutions are capable of achieving a required robustness. The panorama tracker implemented in this thesis seems like a promising tool for robust pose estimation in unprepared outdoor environments.

A Mobile High Sensitivity On-field Organophosphorous Compounds Detecting System for IoT Based Food Safety Tracking

Food safety has always been a social issue that draws great public attention. With the rapid development of wireless communication technologies and intelligent devices, more and more Internet of Things (IoT) systems are applied in the food safety tracking field. However, connection between things and information system is usually established by pre-storing information of things into RFID Tag, which is inapplicable for on-field food safety detection. Therefore, considering pesticide residue is one of the severe threaten to food safety, a new portable, high-sensitivity, low-power, on-field organophosphorus (OP) compounds detection system is proposed in this thesis to realize the on-field food safety detection. The system is designed based on optical detection method by using a customized photo-detection sensor. A Micro Controller Unit (MCU) and a Bluetooth Low Energy (BLE) module are used to quantize and transmit detection result. An Android Application (APP) is also developed for the system to processing and display detection result as well as control the detection process. Besides, a quartzose sample container and black system box are also designed and made for the system demonstration. Several optimizations are made in wireless communication, circuit layout, Android APP and industrial design to realize the mobility, low power and intelligence.

Specification of a smart meter/actuator description mechanism & development of a mobile application

Home Automation holds the potential of realizing cost savings for end users while reducing the carbon footprint of domestic energy consumption. Yet, adoption is still very low. High cost of vendor-supplied home automation systems is a major prohibiting factor. Open source systems such as FHEM, Domoticz, OpenHAB etc. are a cheaper alternative and can drive the adoption of home automation. Moreover, they have the advantage of not being limited to a single vendor or communication technology which gives end users flexibility in the choice of devices to include in their installation. However, interaction with devices having diverse communication technologies can be inconvenient for users thus limiting the utility they derive from it. For application developers, creating applications which interact with the several technologies in the home automation systems is not a consistent process. Hence, there is the need for a common description mechanism that makes interaction smooth for end users and which enables application developers to make home automation applications in a consistent and uniform way. This thesis proposes such a description mechanism within the context of an open source home automation system – FHEM, together with a system concept for its application. A mobile application was developed as a proof of concept of the proposed description mechanism and the results of the implementation are reflected upon.