About OpenKnowledge@NAU | For NAU Authors

Enhancing security and radio spectrum efficiency in cognitive IoT networks

Korenda, Ashwija Reddy (2018) Enhancing security and radio spectrum efficiency in cognitive IoT networks. Masters thesis, Northern Arizona University.

[img] Text
Korenda_AR_2018_Enhancing_security_radio_spectrum_efficiency_IoT_networks.pdf - Published Version
Restricted to Repository staff only

Download (5MB) | Request a copy


The emergence of Internet of Things (IoT) has led to a technology breakthrough by facilitating a new generation of sensing and control applications such as smart cities, smart health, and smart homes to only name a few. However, such a large-scale network of sensors and actuators involve a set of new challenges including security, radio spectrum scarcity, complexity of network, data management, and lack of global standards. In order to accommodate the growing number of IoT devices which is predicted to be over 20.4 billion by the year 2020, a new generation wireless protocols are required to scale up to such huge networks. In this thesis, the problem of dynamic spectrum management and security in IoT networks are considered. Security is one of the critical challenges in IoT networks, where the connected devices need to be protected from potential malicious and selfish attacks. The malicious attacks refer to the attacks where illegitimate and intruding entities attempt to disrupt the network performance through jamming or other unauthorized actions. Several cryptographic methods have been widely utilized to protect the communication devices from such attacks. However, such conventional methods are not easily scalable to large-scale IoT networks as they often rely on generation, distribution, and storing secret keys in the devices and are prone to several attacks such as man-in-the-middle attacks. Hardware-based security methods attempt to utilize the unique variations in the electronic devices as a metric for identification, authentication, and even secret key generation. While such methods have been fairly successful in identification and authentication applications, they still cannot offer a reliable solution for key generation applications as the performance of such methods highly depends on the physical and environmental factors. In this work, we developed a hardware-based secret key generation mechanism that utilizes the random variations in embedded memories in IoT devices to generate reproducible and reliable cryptographic keys by proposing a new error correction and fuzzy extractor structure. Furthermore, we developed a reputation-based spectrum leasing mechanism to provide a potential solution for spectrum scarcity in IoT networks. While the current static approaches of spectrum management resulted in inefficient usage of spectrum which is an expensive resource, the recent advancements in communication devices led to development of dynamic spectrum management techniques. Such dynamic spectrum management can be in the forms of spectrum sharing without involving the licensed users or more sophisticated methods of spectrum leasing, where the spectrum owners can willingly allocate a part of their spectrum to the unlicensed users in exchange for some benefit. While such spectrum sharing solutions can generally enhance the efficiently of spectrum utilization and the Quality of Service (QoS) for spectrum owners, they are highly sensitive to potential selfish attacks. Selfish attacks refer to the attacks by authenticated users who try to increase their own benefits. For example, in cooperative spectrum leasing scenarios, the selfish users may attempt to increase their own transmission rate by using the leased spectrum for their own selfish transmissions by not allocating enough power for relaying licensed user packets. Here, we propose a reputation-based spectrum leasing model to monitor the behavior of self-interested users to enhance the performance of common spectrum leasing techniques against selfish attacks.

Item Type: Thesis (Masters)
Publisher’s Statement: © Copyright is held by the author. Digital access to this material is made possible by the Cline Library, Northern Arizona University. Further transmission, reproduction or presentation of protected items is prohibited except with permission of the author.
Keywords: Coalition Formation; Cognitive Radio; ReRAM PUF; Secret key
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
NAU Depositing Author Academic Status: Student
Department/Unit: Graduate College > Theses and Dissertations
College of Engineering, Informatics, and Applied Sciences > School of Informatics, Computing, and Cyber Systems
Date Deposited: 05 May 2021 20:19
URI: http://openknowledge.nau.edu/id/eprint/5446

Actions (login required)

IR Staff Record View IR Staff Record View


Downloads per month over past year