Practical Secrecy at the Physical Layer: Key Extraction Methods with Applications in Cognitive Radio

The broadcast nature of wireless communication imposes the risk of information leakage to adversarial or unauthorized receivers. Therefore, information security between intended users remains a challenging issue. Currently, wireless security relies on cryptographic techniques and protocols that lie at the upper layers of the wireless network. One main drawback of these existing techniques is the necessity of a complex key management scheme in the case of symmetric ciphers and high computational complexity in the case of asymmetric ciphers. On the other hand, physical layer security has attracted significant interest from the research community due to its potential to generate information-theoretic secure keys. In addition, since the vast majority of physical layer security techniques exploit the inherent randomness of the communication channel, key exchange is no longer mandatory. However, additive white Gaussian noise, interference, channel estimation errors and the fact that communicating transceivers employ different radio frequency (RF) chains are among the reasons that limit utilization of secret key generation (SKG) algorithms to high signal to noise ratio levels. The scope of this dissertation is to design novel secret key generation algorithms to overcome this main drawback. In particular, we design a channel based SKG algorithm that increases the dynamic range of the key generation system. In addition, we design an algorithm that exploits angle of arrival (AoA) as a common source of randomness to generate the secret key. Existing AoA estimation systems either have high hardware and computation complexities or low performance, which hinder their incorporation within the context of SKG. To overcome this challenge, we design a novel high performance yet simple and efficient AoA estimation system that fits the objective of collecting sequences of AoAs for SKG. Cognitive radio networks (CRNs) are designed to increase spectrum usage efficiency by allowing secondary users (SUs) to exploit spectrum slots that are unused by the spectrum owners, i.e., primary users (PUs). Hence, spectrum sensing (SS) is essential in any CRN. CRNs can work both in opportunistic (interweaved) as well as overlay and/or underlay (limited interference) fashions. CRNs typically operate at low SNR levels, particularly, to support overlay/underlay operations. Similar to other wireless networks, CRNs are susceptible to various physical layer security attacks including spectrum sensing data falsification and eavesdropping. In addition to the generalized SKG methods provided in this thesis and due to the peculiarity of CRNs, we further provide a specific method of SKG for CRNs. After studying, developing and implementing several SS techniques, we design an SKG algorithm that exploits SS data. Our algorithm does not interrupt the SS operation and does not require additional time to generate the secret key. Therefore, it is suitable for CRNs

Performance and Security Enhancements in Practical Millimeter-Wave Communication Systems

Millimeter-wave (mm-wave) communication systems achieve extremely high data rates and provide interference-free transmissions. to overcome high attenuations, they employ directional antennas that focus their energy in the intended direction. Transmissions can be steered such that signals only propagate within a specific area-of-interest. Although these advantages are well-known, they are not yet available in practical networks. IEEE 802.11ad, the recent standard for communications in the unlicensed 60 GHz band, exploits a subset of the directional propagation effects only. Despite the large available spectrum, it does not outperform other developments in the prevalent sub-6 GHz bands. This underutilization of directional communications causes unnecessary performance limitations and leaves a false sense of security. For example, standard compliant beam training is very time consuming. It uses suboptimal beam patterns, and is unprotected against malicious behaviors. Furthermore, no suitable research platform exists to validate protocols in realistic environments. To address these challenges, we develop a holistic evaluation framework and enhance the performance and security in practical mm-wave communication systems. Besides signal propagation analyses and environment simulations, our framework enables practical testbed experiments with off-the-shelf devices. We provide full access to a tri-band router’s operating system, modify the beam training operation in the Wi-Fi firmware, and create arbitrary beam patterns with the integrated antenna array. This novel approach allows us to implement custom algorithms such as a compressive sector selection that reduces the beam training overhead by a factor of 2.3. By aligning the receive beam, our adaptive beam switching algorithm mitigates interference from lateral directions and achieves throughput gains of up to 60%. With adaptive beam optimization, we estimate the current channel conditions and generate directional beams that implicitly exploit potential reflections in the environment. These beams increase the received signal strength by about 4.4 dB. While intercepting a directional link is assumed to be challenging, our experimental studies show that reflections on small-scale objects are sufficient to enable eavesdropping from afar. Additionally, we practically demonstrate that injecting forged feedback in the beam training enables Man-in-the Middle attacks. With only 7.3% overhead, our authentication scheme protects against this beam stealing and enforces responses to be only accepted from legitimate devices. By making beam training more efficient, effective, and reliable, our contributions finally enable practical applications of highly directional transmissions

Secrecy rate analysis of UAV-enabled mmWave networks using matern hardcore point processes

IEEE Communications aided by low-altitude unmanned aerial vehicles (UAVs) have emerged as an effective solution to provide large coverage and dynamic capacity for both military and civilian applications, especially in unexpected scenarios. However, because of their broad coverage, UAV communications are prone to passive eavesdropping attacks. This paper analyzes the secrecy performance of UAVs networks at the millimeter wave (mmWave) band and takes into account unique features of air-toground channels and practical constraints of UAV deployment. To be specific, it explores the 3D antenna gain in the air-toground links and uses the Matérn hardcore point process to guarantee the safety distance between the randomly deployed UAV base stations. In addition, we propose the transmit jamming strategy to improve the secrecy performance in which part of UAVs send jamming signals to confound the eavesdroppers. Simulation results verify our analysis and demonstrate the impact of different system parameters on the achievable secrecy rate. It is also revealed that optimizing the density of jamming UAVs will significantly improve security of UAV-enabled networks