<div>The Internet-of-Things (IoT) is one of the fastest-growing technologies in computing, revolutionizing several application domains such as wearable computing, home automation, industrial manufacturing, <i>etc</i>. This rapid proliferation, however, has given rise to a plethora of new security and privacy concerns. For example, IoT devices frequently access sensitive and confidential information (<i>e.g.,</i> physiological signals), which has made them attractive targets for various security attacks. Moreover, with the hardware components in these systems sourced from manufacturers across the globe, instances of counterfeiting and piracy have increased steadily. Security mechanisms such as device authentication and key exchange are attractive options for alleviating these challenges.</div><div><br></div><div>In this dissertation, we address the challenge of enabling low-cost and low-overhead device authentication and key exchange in off-the-shelf embedded systems. The first part of the dissertation focuses on a hardware-intrinsic mechanism and proposes the design of two Physically Unclonable Functions (PUFs), which leverage the memory (DRAM, SRAM) in the system, thus, requiring minimal (or no) additional hardware for operation. Two lightweight authentication and error-correction techniques, which ensure robust operation under wide environmental and temporal variations, are also presented. Experimental results obtained from prototype implementations demonstrate the effectiveness of the design. The second part of the dissertation focuses on the application of these techniques in real-world systems through a new end-to-end authentication and key-exchange protocol in the context of an Implantable Medical Device (IMD) ecosystem. Prototype implementations exhibit an energy-efficient design that guards against security and privacy attacks, thereby making it suitable for resource-constrained devices such as IMDs.</div><div><br></div>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/12743390 |
| Date | 30 July 2020 |
| Creators | Soubhagya Sutar (9187907) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/Memory-based_Hardware-intrinsic_Security_Mechanisms_for_Device_Authentication_in_Embedded_Systems/12743390 |
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