The first line of defence against wireless attacks in Radio Frequency Identi cation (RFID)
systems is authentication of tags and readers. RFID tags are very constrained in terms of
power, memory and size of circuit. Therefore, RFID tags are not capable of performing
sophisticated cryptographic operations. In this dissertation, we have designed light-weight
authentication schemes to securely identify the RFID tags to readers and vice versa. The
authentication schemes require simple binary operations and can be readily implemented
in resource-constrained Radio Frequency Identi cation (RFID) tags. We provide a formal
proof of security based on the di culty of solving the Syndrome Decoding (SD) problem.
Authentication veri es the unique identity of an RFID tag making it possible to track a
tag across multiple readers. We further protect the identity of RFID tags by a light-weight
privacy protecting identifi cation scheme based on the di culty of the Learning Parity with
Noise (LPN) complexity assumption. To protect RFID tags authentication against the relay
attacks, we have designed a resistance scheme in the analog realm that does not have the
practicality issues of existing solutions. Our scheme is based on the chaos-suppression theory
and it is robust to inconsistencies, such as noise and parameters mismatch. Furthermore,
our solutions are based on asymmetric-key algorithms that better facilitate the distribution of cryptographic keys in large systems. We have provided a secure broadcast encryption protocol to effi ciently distribute cryptographic keys throughout the system with minimal communication overheads. The security of the proposed protocol is formally proven in the adaptive adversary model, which simulates the attacker in the real world.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OOU./en#10393/19937 |
| Date | 03 May 2011 |
| Creators | Malek, Behzad |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thèse / Thesis |
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