Moving Trading Communication Systems (TCSs) services to the cloud may seem to be a cost-effective choice. However, operating cloud-based TCSs across the Internet does face a number of challenges including availability, quality of service (QoS), performance and security issues. This research examines the feasibility for creation of a usable model to enable assessment of the design and implementation of TCSs in relation to both time-critical performance and appropriate security levels as TCSs are migrated to a public cloud environment. A realworld case study of a company operating a TCS, which is recently scheduled for movement to a public cloud, is used to enable assessment of a simulation system using OPNET. The simulation results show 1) that the performance of a cloud-based TCS may be inferior to traditional circuit-switched and leasedline-based TCSs, where equivalent services requirements and costs are involved; and 2) a methodology relevant to how to best manage and control a cloud-based TCS to realize true benefit while maintaining required level of QoS, performance and overall security is possible.
With predictions suggesting there will be 18 billion Internet of Things (IoT) devices live by 2022, performance of these low powered devices, as well as security is of utmost importance. Managing security and performance is a balancing act. Achieving this balance will always continue to be a challenge. This research presents two main contributions to this area. The first contribution is a framework to measure cryptographic performance of IoT devices. The areas of measurement are power consumption, time cost, energy cost, random access memory (RAM) usage and flash usage. The second contribution is an insightful comparison of the performance of the ATmega328, STM32F103C8T6 and ESP8266 low powered microcontroller devices. Experiments were conducted on these devices running various cryptographic operations. The measured operations are from three encryption algorithms: Advanced Encryption Standard (AES), ChaCha and Acorn. The proposed methods from this research are real-world in nature rather than simulated, and can be used by others wishing to conduct their own IoT performance testing. The results show that the ATmega328 has the lowest overall power consumption. The ESP8266 was generally the fastest performing device. ChaCha outperformed AES in both time cost and energy cost. Both algorithms outperformed Acorn in these metrics. The STM32F103C8T6 device displayed the best overall energy cost, while still performing well in terms of time. The results from the experiments conducted in this study can be used by network designers, developers and others to make appropriate decisions in IoT deployments with regards to balancing performance and security.
Energy market trading systems are undergoing rapid transformation due to an increasing demand for renewable energy sources to be integrated into the power grid, coupled with the dynamic and evolving needs of future energy customers. In the current energy trading system, which is based on mega power generation, energy is traded by insecure means of communication based on mutual trust. In addition, electricity from both renewable and non-renewable sources is mixed in the grid, impeding customers' ability to definitively track the source of energy dispatched to their premises. Although blockchain technology has been studied for energy trading on a peer-to-peer microgrid trading, to our knowledge none of the previous work focused on using blockchain for trading energy in a national wholesale energy market in macrogrid. In this paper, we address security architectures required of the energy market trading system in an Australian context, we propose a cryptocurrency token-based structure and a smart contract that provides data confidentiality that verifies and audits transactional records. The proposed trading system architecture not only enhances overall system security but provides additional capabilities in the operation of the scheme so that sources of energy dispatched to customer premises are known. The energy market trading system we propose also presents higher security compared to existing trading systems.
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