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This dissertation presents a comprehensive body of research on authentication and message integrity verification for emerging wireless networks, focusing on secret-free and physical layer security techniques across diverse, challenging, and unconventional environments. It comprises four first-author contributions that span underground wireless systems, over-the-air (OTA) channels, vehicular communications, and nanoscale molecular networks.
The first contribution, Soil-Assisted Trust Establishment for Underground Wireless Networks (STUN), introduces a physical-layer trust bootstrapping protocol that achieves authentication and message integrity without pre-shared secrets. Leveraging underground-to-air propagation laws and trusted relay nodes, STUN resists active signal injection attacks and demonstrates security comparable to the unbalanced oil and vinegar cryptographic scheme, with practical applicability to underground agricultural IoT deployments.
The second contribution, RF Fingerprint-Based Location Authentication for Over-the-Air and Underground Wireless Networks (LAOUWN), proposes a robust location authentication framework based on channel impulse response (CIR) features and deep learning. It employs convolutional neural networks (ResNet-18/34/50) enhanced with transfer learning and adversarial domain adaptation, achieving over 90% authentication accuracy across diverse testbeds. The system demonstrates complete resistance to advanced adversaries including Friis-based and ray-tracing-enhanced attackers whose success rate is reduced to random guessing.
The third contribution, VET: Autonomous Vehicular Credential Verification using Trajectory and Motion Vectors, presents a lightweight, privacy-preserving authentication protocol for vehicular networks. VET verifies credential legitimacy using trajectory similarity and motion-based trust metrics (TMVs), achieving a 97% true positive rate under benign conditions and a 99.9% detection rate against remote signal-manipulating adversaries. It remains agnostic to wireless channel variability and scalable to multi-attacker scenarios.
Finally, a Systematization of Knowledge for Security in Molecular and Nano-Communications surveys current threats and defense mechanisms in nanoscale networks. It identifies critical gaps such as the lack of structured taxonomies, active threat mitigation, and cross-layer integration and proposes novel solutions, including bio-inspired cryptographic models and enhanced error correction strategies.
Together, these contributions advance the field of physical-layer security by delivering robust, practical, and hard-to-forge mechanisms for secure communication in next generation emerging wireless networks, especially in unconventional and resource constrained settings where traditional cryptographic approaches fall short.