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The Centre for Internet of Things and Pervasive Systems is organising a seminar on "Hardware-Based Security Solutions for the Internet of Things" from Dr Basel Halak. The event is open to anyone from across the University to attend. The Internet of Things (IoT) is expected to generate tremendous economic benefit; this promise is undermined by major security threats. First of all the vast majority of these devices are expected to communicate wirelessly, and will be connected to the Internet, which makes them especially susceptible to confidentiality threats from attackers snooping for messages contents. Second, most IoT devices are expected to be deployed in remote locations with little or no protection; therefore they can be vulnerable to both invasive and side channel attacks, malicious adversaries can potentially gain access to a device and apply well know power or timing analyses to extract sensitive data that might be stored on the IoT node, such as encryption keys, digital identifiers, and recorded measurements. Furthermore, with ubiquitous systems, it can no longer be assumed that the attacker is remote. Indeed, the attack could even come from within the system itself, from rogue embedded hardware (e.g. Trojans). A large proportion of IoT devices operate in an energy-constrained environment with very limited computing resources, this makes the use of typical defence mechanisms such as classic cryptography algorithms prohibitively expensive. The challenges for building secure IoT are threefold: • How to develop hardware which is inherently resilient to physical attacks • How to implement complex security protocols with very limited resources • How to detect/diagnose anomalous behaviour of an IoT device This talk addresses the above three questions, as follows: 1) The first part of this talk addresses the first question, it presents two novel approaches for enhancing the security and reliability of physically unclonable functions, one of the enabling technologies designing Tamper resistant hardware. The first technique propose a physically unclonable function using instruction cache, typically found in all embedded processors. The design is optimised to improve resilience to ageing effects. The second approach aim to enhance the security of physically unclonable functions against modelling attacks by combining these with low cryptographic primitives such as permutation and substitution. The proposed techniques makes its affordable, secure and reliable to use physically unclonable technology in resources constrained systems. 2) The second part of this talk addressees the second question, it presents a new authentication protocol based on PUF technology, Then power consumption and memory utilization of the proposed protocol were estimated and compared with the existing solutions, namely: DTLS (datagram transport layer security) handshake protocol and UDP (user datagram protocol). Our results indicate that the proposed PUF based authentication saves up to 45% power and uses 12% less memory compared to DTLS handshake authentication. 3) The third part of this talk addresses the final question, it presents a new detection technique for malicious/abnormal behaviour of embedded using data from Hardware Performance Counters (HPCs). Finally the talk concludes with a summary of outstanding challenges.

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The Centre for Internet of Things and Pervasive Systems is organising a seminar titled "Energy Driven Design of Self-Powered IoT Devices: Applications in Cycling Performance Monitoring" from Samuel Wong, a fourth year undergraduate student in ECS. The event is open to anyone from across the University to attend. The Energy Driven Paradigm is an approach to designing energy harvesting devices where explicit consideration is given to the energy supply and demand characteristics of the application at the very beginning of the development cycle. Instead of designing an IoT device and then optimizing for battery life, or using energy harvesting to extend battery life, what if we start from the harvester and design a system tailored to the harvester. This paradigm shift introduces some interesting challenges, for example the need to have sustained computation spanning intermittent power outages and to have energy aware devices which can respond dynamically to energy scarcity or abundance. Two IoT devices with dramatically different energy harvester characteristics are presented as a case study into the energy driven design process, which were researched through my undergraduate PIII project and summer research internship in ECS. The first device is a wind and inclination meter powered from a tiny wind turbine which gives a low but steady AC power, whereas the second is speed and distance meter powered from periodic pulses of energy. Both devices have wireless connectivity and are battery-less.

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The Centre for Internet of Things and Pervasive Systems is organising a seminar on "Automatic Aggregation of IoT Sensor Data for Health and Safety Monitoring" from Dr Paolo Pareti. The event is open to anyone from across the University to attend. Effective use of IoT sensor data often requires abstracting low-level information from multiple sensors into more high-level and actionable knowledge. In this talk I will present an automatic approach for the aggregation of sensor data and its evaluation. We will present the results of an experiment where human participants are presented with a simulation and asked to decide which emergency response action to take (if any). This study investigates the effectiveness of automatically-generated sensor summaries to support human decision making. We consider sensor summaries at different levels of granularity, and the the usefulness of modifying the granularity of these summaries on demand.

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The Centre for Internet of Things and Pervasive Systems is organising a seminar on "Crowdsourced Air Pollution Monitoring in Ho Chi Minh City-Vietnam with Low Cost Mobile Sensors" from Dr Long Tran-Thanh. The event is open to anyone from across the University to attend. Air pollution is well known to have significant negative impact on public health, especially in Ho Chi Minh City (HCMC), Vietnam, where the air pollution level is one of the worst in the world. Despite the need for detailed air pollution monitoring, and thus better understanding of air pollution dynamics, very little air pollution data has been collected since 2009 in HCMC. The only two working air pollution monitoring stations are the one maintained by the US Embassy, and another one run by the National University for educational purposes (the latter typically does not work for months per year due to maintenance reasons). However, both stations can only provide aggregated pollution data, and not with the required details (e.g., ground level air pollutant percentage, collected in real-time, or at least with high frequency). Since the cost of deploying additional monitoring stations, that together can provide the sufficient level of data collection, is prohibitively expensive (one such station’s deployment and maintenance cost can go up to £100K), there is a need to implement a more cost efficient solution to the air pollution monitoring problem. In this project we propose a new approach which combines low cost sensor technology with crowdsourcing techniques to monitor the air pollution within HCMC. In particular, we aim to set up a proof of concept collaborative project between Southampton and the Vietnamese-German University (VGU), which aims to (i) build low cost sensors that are suitable for measuring a number of key air pollutants, which will be mounted to motorbikes, cars, and buses to collect data; and (ii) develop incentive engineering mechanisms to motivate local residents to participate in the crowdsourced data collection process. In this talk, I will provide a progress report of the project (i.e., what we have achieved so far, and what still needs to be done).

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Inaugural Group Away Day for the Biomedical Electronics Group. Focus on PhD students, their projects and the Research Themes for the Group.

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Electric Propulsion Activities at the University of Brasilia ABSTRACT: Research in Electric Propulsion has been ongoing at the University of Brasilia for nearly 20 years, first at the Plasma Laboratory, Physics Institute and, much more recently, at the Space Systems Laboratory, Aerospace Engineering. Whereas, at the Physics Institute, experimental activities and numerical simulations have led to the development and testing of several versions of Permanent-Magnet Hall-Effect Thrusters, at Aerospace Engineering, only established in 2012, the Space Systems Laboratory facilities are still being implemented. Therefore, research until now has mostly been theoretical, and experimental activities are just starting in earnest. Topics that have been explored and are under consideration for future development include Pulsed Plasma Thrusters, Cylindrical Hall-Effect Thrusters, Arcjets and Helicon Double-Layer Thrusters.

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“UV-curable piezoelectric coatings” Abstract: The seminar will describe some recent progresses in the design of piezoelectric composites based on the use of ZnO as piezoceramic, embedded in a UV-curable acrylic matrix. These systems could be useful for the fabrication of wearable fabrics, for energy harvesting purposes. In particular, among the potential uses, the area of the piezocoating, coated on a fabric, could be partially exploited as gas sensing unit, exploiting the electrical energy produced by the piezo part for feeding the gas sensor, hence providing an autonomous operation of the entire device.

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Presentation Title：Time series data mining and its application on the condition evaluation of electrical equipment Abstract: With the rapid increasing of the data collected from different fields, the data mining techniques have attracted researchers’ attention. In this presentation, we focus on time series data mining technique and its application on the condition evaluation of electrical equipment. First of all, the concept and development of time series data mining technique and electrical equipment condition evaluation are briefly introduced. The general framework of how to perform condition evaluating on electrical equipment using data mining technique is presented in detail. Then, three data mining models, named TDPCR, IVDPC,CMBCF are discussed, which are used to represent the massive raw data in lower dimension, to cluster objects into different groups and to predict the forthcoming change of the target variables respectively. After reviewing these models, we move on the application case in which these models are properly applied. In the end, some future works are listed and discussed.