Lauren M. Huie

Secret Key Generation in the Two-Way Relay Channel With Active Attackers

Most of the existing work on key generation from wireless fading channels requires a direct wireless link between legitimate users so that they can obtain correlated observations from the common wireless link. This paper studies the key generation problem in the two-way relay channel, in which there is no direct channel between the key generating terminals. We propose an effective key generation scheme that achieves a substantially larger key rate than that of a direct channel mimic approach. Unlike existing schemes, there is no need for the key generating terminals to obtain correlated observations in our scheme. We also investigate the effects of an active attacker on the proposed key generation protocol. We characterize the optimal attackers strategy that minimizes the key rate of the proposed scheme. Furthermore, we establish the maximal attackers power under which our scheme can still achieve a nonzero key rate.

Physical layer challenge-response authentication in wireless networks with relay.

Exploiting physical layer characteristics to enhance or complement authentication strength in wireless networks has been attracting research attention recently. Existing physical layer authentication mechanisms mainly tackle single-hop communications. In this paper, we propose two physical layer challenge-response authentication mechanisms for wireless networks with relay. One mechanism, named PHY-CRAMR, is an extension of the existing PHY-CRAM protocol. It fully utilizes the randomness, reciprocity, and location decorrelation features of the wireless fading channel to hide/encrypt the challenge response messages at the physical layer, and is immune to outside attacks with a trusted relay. The other novel mechanism, named PHY-AUR, exploits randomness, coherence, and location decorrelation properties of wireless fading channel to securely convey the product of the channel state information on consecutive links and uses the fading channel to encrypt challenge and response messages. PHY-AUR is immune to both outside and inside attacks with an untrusted relay. Both PHY-CRAMR and PHY-AUR adopt OFDM technique to modulate the authentication key and challenge-response messages on subcarriers. Physical layer pilots and preambles are eliminated to prevent an attacker from gaining knowledge about the channel state information, and as a result prevent the authentication key from being revealed to untrusted attackers. We analyze the security strength of both mechanisms and conduct extensive simulations to evaluate them. It shows that both PHY-CRAMR and PHY-AUR can achieve both a high successful authentication rate and low false acceptance rate, and the performance improves as the signal to noise ratio (SNR) increases.

Simultaneously generating multiple keys in many to one networks

The problem of simultaneously establishing multiple keys, one for each user in a set of users, is considered with possible assist from a group of dedicated helpers. For the case in which all users are required to generate keys, we develop a scheme that is sum rate optimal. For the case with dedicated helpers, we develop an achievable scheme and derive an outer bound. We identify conditions under which the developed scheme achieves the full capacity region and conditions under which it is sum rate optimal. We then specialize the study to a pairwise independent network model, for which we convert the key generation problem to a single-source multi-commodity flow over a network problem. Coupling results from graph theory, we fully characterize the capacity region for the general case of generating multiple keys with multiple helpers under the PIN model.

System state estimation in the presence of false information injection

The problem of system state estimation in the presence of an adversary is investigated for linear dynamic systems. It is assumed that the adversary injects additive false information into the sensor measurement. The impact of the false information on the Kalman filters estimation performance is analyzed for a general dynamic system. To be concrete, a target tracking system has been used as an example. In such a system, if the false information is injected only once, the effect of the false information on the Kalman filter proves to be diminishing over time, even when the Kalman filter is unaware of the false information injection. The convergence rate as a function of the maneuvering index is analyzed. If the false information is repeatedly injected into the system, the induced estimation error proves to reach a finite steady state. Numerical examples are presented to support the theoretical results.

Distributed estimation in sensor networks with imperfect model information: An adaptive learning-based approach

The paper considers the problem of distributed estimation of an unknown deterministic scalar parameter (the target signal) in wireless sensor networks (WSNs), in which each sensor receives a single snapshot of the field. The observation or sensing mode is only partially known at the corresponding nodes, perhaps, due to their limited sensing capabilities or other unpredictable physical factors. Specifically, it is assumed that the observation process at a node switches stochastically between two modes, with mode one corresponding to the desired signal plus noise observation mode (a valid observation), and mode two corresponding to pure noise with no signal information (an invalid observation). With no prior information on the local sensing modes (valid or invalid), the paper introduces a learning-based distributed estimation procedure, the mixed detection-estimation (MDE) algorithm, based on closed-loop interactions between the iterative distributed mode learning and estimation. The online learning (or sensing mode detection) step re-assesses the validity of the local observations at each iteration, thus refining the ongoing estimation update process. The convergence of the MDE algorithm is established analytically. Simulation studies show that, in the high signal-to-noise ratio (SNR) regime, the MDE estimation error converges to that of an ideal (centralized) estimator with perfect information about the node sensing modes. This is in contrast with the estimation performance of a naive average consensus based distributed estimator (with no mode learning), whose estimation error blows up with an increasing SNR.

Hop-by-Hop cooperative detection of selective forwarding attacks in energy harvesting wireless sensor networks

Due to the lack of physical protections and security requirements of the network routing protocols, Wireless Sensor Networks (WSNs) are vulnerable to Denial-of-Service (DoS) attacks. Inherent resource constraints also hinder WSNs from deploying conventional encryption schemes and secure routing protocols. In this paper, we investigate a counter selective forwarding attack to efficiently detect the forwarding misbehaviors of malicious nodes and seamlessly deliver sensory data in energy harvesting WSNs. We first analyze a set of adversarial scenarios under an implicit acknowledgment overhearing and identify a vulnerable case. Then we propose a Hop-by-hop Cooperative Detection (HCD) scheme to efficiently detect the forwarding misbehaviors and mitigate the forwarding probabilities of malicious nodes. Extensive simulation results indicate that the proposed scheme can significantly reduce the number of forwarding misbehaviors by quickly decreasing the dropping probabilities of malicious nodes and achieve more than 95% packet delivery ratio in energy harvesting WSNs.

Robust Distributed Least-Squares Estimation in Sensor Networks with Node Failures

Algorithms are studied for distributed least-squares (DLS) estimation of a scalar target signal in sensor networks. Due to the observation locality and the limited sensing ability, the individual sensor estimates are far from being reliable. To obtain a more reliable estimate of the target signal, the sensors could collaborate by iteratively exchanging messages with their neighbors, to refine their local estimates over time. Such an iterative DLS algorithm is investigated in this paper with and without the consideration of node failures. In particular, without sensor node failures it is shown that every instantiation of the DLS algorithm converges, i.e., consensus is reached among the sensors, with the limiting agreement value being the centralized least-squares estimate. With node failures during the iterative exchange process, the convergence of the DLS algorithm is still guaranteed; however, an error exists between the limiting agreement value and the centralized least-squares estimate. In order to reduce this error, a modified DLS scheme, the M-DLS, is provided. The M-DLS algorithm involves an additional weight compensation step, in which a sensor performs a one-time weight compensation procedure whenever it detects the failure of a neighbor. Through analytical arguments and simulations, it is shown that the M-DLS algorithm leads to a smaller error than the DLS algorithm, where the magnitude of the improvement dependents on the network topology.

Emitter location in the presence of information injection

One sensor network task of particular interest is estimating with maximum accuracy the location of an emitter. In this paper, we focus on the impact of a single rogue sensor which injects spurious information into a sensor network in order to maximally degrade location estimation accuracy. Our focus is on understanding and characterizing the impact of such a rogue sensor where as on-going work is focusing on methods to mitigate its impact. The goal is to exploit the nature of the shared wireless medium and sensitivity of localization methods to inaccurate sensor positioning. We find the false location that minimizes the accuracy of a sensor network tasked with estimating the location of an emitter. We assume a means for injecting the false location exists and that the network uses a time and frequency difference of arrival (TDOA/FDOA) localization method. We determine the best location to inject by formulating the problem as the minimization of the determinant of the Fisher Information Matrix (FIM). A numerical method for determining the false location is presented and we show that it significantly reduces the location estimates accuracy independent of sensor-emitter geometry.

Learning-Based Distributed Detection-Estimation in Sensor Networks With Unknown Sensor Defects

The problem of distributed estimation of an unknown deterministic scalar parameter (the target signal) in a wireless sensor network is considered, where each sensor receives a single snapshot of the field. It is assumed that the observation at each node randomly falls into one of two modes: a valid or an invalid observation mode. Specifically, mode one corresponds to the desired signal plus noise observation mode (valid), and mode two corresponds to the pure noise mode (invalid) due to node defect or damage. With no prior information on such local sensing modes, a learning-based distributed procedure is introduced, called the mixed detection-estimation (MDE) algorithm, based on iterative closed-loop interactions between mode learning (detection) and target estimation. The online learning step reassesses the validity of the local observations at each iteration, thus refining the ongoing estimation update process. The convergence of the MDE algorithm is established analytically. Asymptotic analysis shows that, in the high signal-to-noise ratio regime, the MDE estimation error converges to that of an ideal (centralized) estimator with perfect information about the node sensing modes.

Key generation in two-way relay wireless channels

Most of the existing work on key generation from wireless fading channels requires a direct wireless link between legitimate users so that they can obtain correlated observations from the common wireless link. This paper studies the key generation problem in the two-way relay channel, in which there is no direct channel between the key generating terminals. We propose an effective key generation scheme that achieves a substantially larger key rate than that of a direct channel mimic approach. Unlike existing schemes, there is no need for the key generating terminals to obtain correlated observations in our scheme. We then extend our study to the case of a relay with multiple antennas. For this scenario, we derive the optimal power allocation at the relay that maximizes the key rate achieved using our protocol.