Secure and efficient data extraction for ubiquitous computing applications

Ubiquitous computing creates a world where computers have blended seamlessly into our physical environment. In this world, a computer is no longer a monitor-and-keyboard setup, but everyday objects such as our clothing and furniture. Unlike current computer systems, most ubiquitous computing systems are built using small, embedded devices with limited computational, storage and communication abilities. A common requirement for many ubiquitous computing applications is to utilize the data from these small devices to perform more complex tasks. For critical applications such as healthcare or medical related applications, there is a need to ensure that only authorized users have timely access to the data found in the small device. In this dissertation, we study the problem of how to securely and efficiently extract data from small devices.;Our research considers two categories of small devices that are commonly used in ubiquitous computing, battery powered sensors and battery free RFID tags. Sensors are more powerful devices equipped with storage and sensing capabilities that are limited by battery power, whereas tags are less powerful devices with limited functionalities, but have the advantage of being operable without battery power. We also consider two types of data access patterns, local and remote access. In local data access, the application will query the tag or the sensor directly for the data, while in remote access, the data is already aggregated at a remote location and the application will query the remote location for the necessary information, The difference between local and remote access is that in local access, the tag or sensor only needs to authenticate the application before releasing the data, but in remote access, the small device may have to perform additional processing to ensure that the data remains secure after being collected. In this dissertation, we present secure and efficient local data access solutions for a single RFID tag, multiple RFID tags, and a single sensor, and remote data access solutions for both RFID tag and sensor

Chemical Characterisation of Podzols in Sabah, East Malaysia

Chemical analyses were carried out on three podzol samples from the Tambunan and Keningau districts in Sabah. The values of pH, Organic carbon content, cation exchange capacity and HCI extractable metals vary distinctly between horizons. Such variation was most significant between horizons E and Bh and except for pH, the values for the above parameters were lowest and highest in horizons E and Bh respectively

Soft computing applications in dynamic model identification of polymer extrusion process

This paper proposes the application of soft computing to deal with the constraints in conventional modelling techniques of the dynamic extrusion process. The proposed technique increases the efficiency in utilising the available information during the model identification. The resultant model can be classified as a ‘grey-box model’ or has been termed as a ‘semi-physical model’ in the context. The extrusion process contains a number of parameters that are sensitive to the operating environment. Fuzzy ruled-based system is introduced into the analytical model of the extrusion by means of sub-models to approximate those operational-sensitive parameters. In drawing the optimal structure for the sub-models, a hybrid algorithm of genetic algorithm with fuzzy system (GA-Fuzzy) has been implemented. The sub-models obtained show advantages such as linguistic interpretability, simpler rule-base and less membership functions. The developed model is adaptive with its learning ability through the steepest decent error back-propagation algorithm. This ability might help to minimise the deviation of the model prediction when the operational-sensitive parameters adapt to the changing operating environment in the real situation. The model is first evaluated through simulations on the consistency of model prediction to the theoretical analysis. Then, the effectiveness of adaptive sub-models in approximating the operational-sensitive parameters during the operation is further investigated

Privacy protection for RFID-based tracking systems

Abstract—RFID technology is increasingly being deployed in ubiquitous computing environments for object tracking and localization. Existing tracking architecture usually assumes the use of a trusted server which is invulnerable to compromise by internal and external adversaries. However, maintaining such a trusted server is unlikely in the real world. In this paper, we consider the problem of adding privacy protection to object tracking systems built upon passive RFID tags, without relying on a trusted server assumption. Our protocol continues to protect user privacy in the event of partial compromise of a server. I

Unpacking the indirect effects and consequences of environmental regulation

Environmental regulation and its corresponding measures and control is an important issue but have not been fully investigated. Literature on the unintended consequences of regulation control and measures appears to be sparse. Through a series of exploratory case studies in China, this paper examines the various unintended impacts of ecological civilisation (EC) regulation on firms’ operations and their related consequences to performance. Findings showed that there were interrelated themes that underpin the indirect and unintended effects of regulatory control and performance management. This exploratory study can contribute to both theory building and provide important EC policy implications by: (a) enriching the conceptual understanding of the unintended consequences of environmental regulation on firms’ behaviours and outcomes, (b) providing policy maker important insights and practical advices for regulating environmental performance