2026-09-20T11:46:54Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/24212 2023-07-10 col_2142_10761 col_2142_5131 com_2142_10755 com_2142_234 com_2142_5130

Gunter, Carl A. Gunter, Carl A. Abdelzaher, Tarek F. Borisov, Nikita Chandra, Ranveer Fatemieh, Seyed Omid 2011-05-25T14:52:16Z 2011-05-25T14:52:16Z 2011-05-25T14:52:16Z 2011-05 The emerging paradigm for using the wireless spectrum more efficiently is based on enabling secondary users to exploit white-space frequencies that are not occupied by primary users. An enabling technology for forming networks over white spaces is distributed spectrum measurement to identify and assess the quality of unused channels. This spectrum availability data is often aggregated at a central base station or database to govern the usage of spectrum. This process, also referred to as radio spectrum telemetry, is vulnerable to integrity violations if the devices are malicious and misreport spectrum sensing results. There may be nodes that seek to exploit a spectrum in a given region by falsely reporting that a primary signal is present, or, dually, seek to vandalize a primary by reporting that its signal is not present, thereby encouraging interference from secondaries. This dissertation focuses on assuring robustness of radio spectrum telemetry against exploitation and vandalism attacks. This problem is particularly challenging when: (1) attackers are omniscient and coordinated, and constitute a large fraction of the nodes in an area, and (2) the quantity under measurement (signal power) faces natural spatial and temporal variations, as well as uncertainties due to noise, shadowing, and fading. These circumstances make it easier for sophisticated attackers to hide the likely abnormalities of their reports. As illustrative examples, this work investigates two new applications for white-space networks; the communications of the advanced meter infrastructure (AMI) and broadband Internet access for public school students. These applications are utilized to underline the importance of the considered security attacks in practical settings. In addition, the thesis offers communication architectures for these applications and shows the practical, economical, and societal benefits. This work formulates the problem of robust radio spectrum telemetry using a grid-based model and offers a range of solutions. The solutions include (1) model-based techniques that probabilistically detect abnormalities using knowledge about signal propagation and shadowing formulas, (2) data-based techniques based on machine learning classifiers that do not assume prior knowledge about signal propagation models and only rely on direct training data, and (3) trust-based techniques that use a small subset of remotely-attestable nodes as a foundation for trust, and subsequently deter attacks using a combination of statistical sequential estimation and classification techniques. The proposed techniques are evaluated using a novel methodology that relies in part on predicted propagation data derived from real-world registered TV transmitter and terrain data (from the databases of the FCC and NASA) for areas in Illinois and Pennsylvania. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2011-01-28T19:30:47Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Fatemieh_SeyedOmid.pdf: 3530893 bytes, checksum: 1718b0b33b954b4b3f6bf6cca2b42802 (MD5) Made available in DSpace on 2011-05-25T14:52:16Z (GMT). No. of bitstreams: 2 Fatemieh_SeyedOmid.pdf: 3530893 bytes, checksum: 1718b0b33b954b4b3f6bf6cca2b42802 (MD5) license.txt: 4064 bytes, checksum: 1e43bcb0b3a60d19fc5f0177e600e83b (MD5) http://hdl.handle.net/2142/24212 en Copyright 2011 Seyed Omid Fatemieh Security Distributed Spectrum Sensing White Space Networks Radio Spectrum Telemetry Coordinated Malicious False Reports Exploitation Vandalism Assuring robustness of radio spectrum telemetry against vandalism and exploitation Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Dissertation Ph.D. PHD:Computer Science -UIUC 10KS0112PHD