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| Content Provider | ACM Digital Library |
|---|---|
| Author | Jha, Niraj K. |
| Abstract | We have arrived at the dawn of the Internet-of-Things (IoT) era. 25 billion devices (things or physical objects) are already connected to the Internet, and this number is expected to grow to 50 billion by 2020. IoT is a network of physical objects. These objects contain sensors, actuators, and processing elements that enable us to gather data, monitor the health of the object, make intelligent decisions, and optimize processes. IoT is expected to have a potential economic impact of \$3-6 trillion per year by 2025, with \$1-2.5 trillion of this economic impact (its largest fraction) coming from smart healthcare applications. These applications will be enabled by a personal healthcare system consisting of implantable and wearable medical sensors and devices connected to a personal health hub (e.g., a smartphone or smartwatch) that is connected to the Internet. In this talk, we will explore this Internet-of-Medical-Things from two angles: energy-efficient inference and security. We will first explore energy-efficient inference on sensor nodes. This exploits sparsity, which is characteristic of a signal that allows us to represent information efficiently. We will look at an approach that enables efficient representations based on sparsity to be utilized throughout a signal processing system, with the aim of reducing the energy and/or resources required for computation, communication, and storage. Such intelligent sensor nodes can be expected to be an important building block of IoT. We will then show how wearable medical sensors, which are being increasingly used as part of a body-area network to provide proactive healthcare, can be used in a completely different domain: continuous authentication, through monitoring of the biological aura of the person. Unfortunately, as with any other technology, along with the upside, we also have the downside of IoT -- if the security challenges facing IoT are not addressed, it may just become an Internet-of-Things-to-be-Hacked. Hence, in the last part of the talk, we will focus on the security of a body-area network that consists of implantable/wearable medical devices and a health hub. We will also explore physiological side channels that leak information about our health condition. |
| Starting Page | 7 |
| Ending Page | 7 |
| Page Count | 1 |
| File Format | |
| ISBN | 9781450349727 |
| DOI | 10.1145/3060403.3066861 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-05-10 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Medical devices Body-area network Sparsity Inference Energy efficiency Security Iot |
| Content Type | Text |
| Resource Type | Article |
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