Browsing by Author "McGinthy, Jason M."

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    Further Analysis of PRNG-Based Key Derivation Functions
    McGinthy, Jason M.; Michaels, Alan J. (IEEE, 2019)
    The Internet of Things (IoT) is growing at a rapid pace. With everyday applications and services becoming wirelessly networked, security still is a major concern. Many of these sensors and devices have limitations, such as low power consumption, reduced memory storage, and reduced fixed point processing capabilities. Therefore, it is imperative that high-performance security primitives are used to maximize the lifetime of these devices while minimally impacting memory storage and timing requirements. Previous work presented a residue number system (RNS)-based pseudorandom number generator (PRNG)-based key derivation function (KDF) (PKDF) that showed good initial energy-efficient performance for the IoT devices. This paper provides additional analysis on the PRNG-based security and draws a comparison to a current industry-standard KDF. Subsequently, embedded software implementations were performed on an MSP430 and MSP432 and compared with the transport layer security (TLS) 1.3 hash-based message authentication code (HMAC) key derivation function (HKDF); these results demonstrate substantial computational savings for the PKDF approach, while both pass the NIST randomness quality tests. Finally, hardware translation for the PKDF is evaluated through the Mathworks' HDL Coder toolchain and mapping for throughput and die area approximation on an Intel (R) Arria 10 FPGA.
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    Solutions for Internet of Things Security Challenges: Trust and Authentication
    McGinthy, Jason M. (Virginia Tech, 2019-07-12)
    The continuing growth of Internet-connected devices presents exciting opportunities for future technology. These Internet of Things (IoT) products are being manufactured and interleaved with many everyday activities, which is creating a larger security concern. Sensors will collect previously unimaginable amounts of private and public data and transmit all of it through an easily observable wireless medium in order for other devices to perform data analytics. As more and more devices are produced, many are lacking a strong security foundation in order to be the "first to market." Moreover, current security techniques are based on protocols that were designed for more-capable devices such as desktop computers and cellular phones that have ample power, computational ability, and memory storage. Due to IoT's technological infancy, there are many security challenges without proper solutions. As IoT continues to grow, special considerations and protections must be in place to properly secure this data and protect the privacy of its users. This dissertation highlights some of the major challenges related to IoT and prioritizes their impacts to help identify where gaps are that must be filled. Focusing on these high priority concerns, solutions are presented that are tailored to IoT's constraints. A security feature-based framework is developed to help characterize classes of devices to help manage the heterogeneous nature of IoT devices and networks. A novel physical device authentication method is presented to show the feasibility in IoT devices and networks. Additional low-power techniques are designed and evaluated to help identify different security features available to IoT devices as presented in the aforementioned framework.