Abstract
IoT or Internet of Things is a modern term describing the ever growing system of widely interrelated devices which communicate automatically. Almost all devices we consider to be mobile work through an IoT network and participate in this sharing of information. As of late, there has been a rising need to secure communications across smaller, more embedded devices that are increasing in number within IoT networks. These embedded devices may include sensors sending sampled data to a processing unit, or processors themselves that are the brain of a specific embedded device. Securing these systems can be done through cryptography, but standard cryptography is not fully compatible with these small devices. The new constraints presented by securing communications on these devices include minimizing power consumption and resource utilization, while allowing for a viable throughput [Gubbi, Jayavardhana, et al., 2013]. In this paper, a lightweight cryptography algorithm, which attempts to optimize the previously mentioned constraints, is implemented in a system. This implementation was designed using a mix of HDLs (Hardware Description Languages) and designed to be dynamic to be able to accommodate systems with a variety of security requirements. The implementation is applied to a system of sonars that send each other encrypted distance data relative to each other, and use the decrypted data to detect whether they need to adjust their positioning. The aim of using this test system is to emulate use cases in industries where devices must process relative positioning data and communicate securely, while relying on a limited power supply. Examples of these systems include UAVs, drones used for surveillance and recon, etc.
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Acknowledgment
This research was supported in part by the Air Force Research Laboratory Academy Center for Cyberspace Research (ACCR) Directorate, through the Air Force Office of Scientific Research Summer Faculty Fellowship Program®, Contract Numbers FA8750-15-0-6003 and FA9550-15-0001. Moreover, the IBM-ILLINOIS Center for Cognitive Computing Systems Research (C3SR) - a member of the IBM Cognitive Horizon Network, and the Applications Driving Architectures (ADA) Research Center - one of the JUMP Centers co-sponsored by SRC and DARPA. The authors are grateful to **linx, Inc. and **linx Development Corp. for donations which made work on some of the aspects of the RECO-DryGASCON processor possible.
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Herndon, R., El-Issa, R., Heer, D., **ong, J., Hwu, WM., El-Hadedy, M. (2021). RECO-DryGASCON: Re-configurable Lightweight DryGASCON Engine. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Proceedings of the Future Technologies Conference (FTC) 2020, Volume 3. FTC 2020. Advances in Intelligent Systems and Computing, vol 1290. Springer, Cham. https://doi.org/10.1007/978-3-030-63092-8_47
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DOI: https://doi.org/10.1007/978-3-030-63092-8_47
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