Title:
SPLICE: Securing the lifecycle of Smart Homes
Speaker: Prof. David Kotz
Abstract: Our homes are increasingly embedded with “Smart Things,” networked with each other and with the Internet, forming “Smart Homes.” What happens when an occupant moves out or transfers ownership of her Smart Home? How does an occupant identify and decommission all the Things in a home before she moves out? How does a new occupant discover, identify, validate, and configure all the Things in the home he adopts? When a person moves from smart home to smart office to smart hotel, how is a new environment vetted for safety and security, how are personal settings migrated, and how are they securely deleted on departure? When the original vendor of a Thing (or the service behind it) disappears, how can that Thing (and its data, and its configuration) be transferred to a new service provider? What interface can enable lay people to manage these complex challenges, and be assured of their privacy, security, and safety? We present a list of key research questions to address these important challenges, then give an overview of results from our own collaborative research project, SPLICE: Security and Privacy in the Lifecycle of IoT in Consumer Environments.
Bio: David Kotz is the Provost, and the Pat and John Rosenwald Professor in the Department of Computer Science, at Dartmouth College. He previously served as Associate Dean of the Faculty for the Sciences, as a Core Director at the Center for Technology and Behavioral Health, and as the Executive Director of the Institute for Security Technology Studies. His current research involves security and privacy in smart homes, and wireless networks. He has published over 250 refereed papers, obtained $89m in grant funding, and mentored over 100 research students and postdocs. He is an ACM Fellow, an IEEE Fellow, a 2008 Fulbright Fellow to India, a 2019 Visiting Professor at ETH Zürich, and an elected member of Phi Beta Kappa. He received his AB in Computer Science and Physics from Dartmouth in 1986, and his PhD in Computer Science from Duke University in 1991.
Title: Towards the Internet of (Wild) Things
Speaker: Prof. Andrew Markham
Abstract: The use of sensor technology for conservation and wildlife management is increasing rapidly due to the wider availability of low cost solutions that allow for widespread deployments. In this talk, I will present an overview of the current technological landscape and highlight exciting new areas. In particular, I will draw on experiences that our group has from over a decade of applications. I will also discuss the issue common to many emerging IoT systems where sensing and processing is becoming cheaper and cheaper in terms of energy allowing always-on-sensing, yet wireless communication remains a limiting factor. This is particularly relevant to wild animal tracking where there is a lack of infrastructure and the scale of national parks can be immense. This motivates the use of edge based machine learning in an attempt to extract information of value in a timely manner. However, we find that just like an ecosystem itself is an interconnected network of trophic links, treating collocated information as interlinked leads to increased efficiency, at the cost of system complexity. I will present a vision for a future Internet of Wild Things, setting out a roadmap for converging technology and sensing – from satellites to swarms of drones to long-lived sensors.
Bio: Andrew Markham is a Professor of Computer Science in the Department of Computer Science at the University of Oxford. His research broadly falls under the umbrella of cyber-physical systems, with particular application to obtaining the maximum value from noisy sensor data through signal processing and machine learning. He obtained his bachelor’s degree in electrical and electronic engineering in 2004, followed by his PhD in 2008, both from the University of Cape Town, South Africa. He has published over 150 papers and attracted over £10M in funding. He has a particular interest in applying novel sensing systems to challenging real-world problems such as wildlife monitoring and first-responder tracking.