Secure Two-Way Transmission via Wireless-Powered Untrusted Relay and External Jammer

In this paper, we propose a two-way secure communication scheme where two transceivers exchange confidential messages via a wireless powered untrusted amplify-and-forward (AF) relay in the presence of an external jammer. We take into account both friendly jamming (FJ) and Gaussian noise jamming (GNJ) scenarios. Based on the time switching (TS) architecture at the relay, the data transmission is done in three phases. In the first phase, both the energy-starved nodes, the untrustworthy relay and the jammer, are charged by non-information radio frequency (RF) signals from the sources. In the second phase, the two sources send their information signals and concurrently, the jammer transmits artificial noise to confuse the curious relay. Finally, the third phase is dedicated to forward a scaled version of the received signal from the relay to the sources. For the proposed secure transmission schemes, we derive new closed-form lower-bound expressions for the ergodic secrecy sum rate (ESSR) in the high signal-to-noise ratio (SNR) regime. We further analyze the asymptotic ESSR to determine the key parameters; the high SNR slope and the high SNR power offset of the jamming based scenarios. To highlight the performance advantage of the proposed FJ, we also examine the scenario of without jamming (WoJ). Finally, numerical examples and discussions are provided to acquire some engineering insights, and to demonstrate the impacts of different system parameters on the secrecy performance of the considered communication scenarios. The numerical results illustrate that the proposed FJ significantly outperforms the traditional one-way communication and the Constellation rotation approach, as well as our proposed benchmarks, the two-way WoJ and GNJ scenarios.Comment: 14 pages, 6 figures, Submitted to IEEE Transactions on Vehicular Technolog

Secrecy Energy Efficiency of MIMOME Wiretap Channels with Full-Duplex Jamming

Full-duplex (FD) jamming transceivers are recently shown to enhance the information security of wireless communication systems by simultaneously transmitting artificial noise (AN) while receiving information. In this work, we investigate if FD jamming can also improve the systems secrecy energy efficiency (SEE) in terms of securely communicated bits-per- Joule, when considering the additional power used for jamming and self-interference (SI) cancellation. Moreover, the degrading effect of the residual SI is also taken into account. In this regard, we formulate a set of SEE maximization problems for a FD multiple-input-multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel, considering both cases where exact or statistical channel state information (CSI) is available. Due to the intractable problem structure, we propose iterative solutions in each case with a proven convergence to a stationary point. Numerical simulations indicate only a marginal SEE gain, through the utilization of FD jamming, for a wide range of system conditions. However, when SI can efficiently be mitigated, the observed gain is considerable for scenarios with a small distance between the FD node and the eavesdropper, a high Signal-to-noise ratio (SNR), or for a bidirectional FD communication setup.Comment: IEEE Transactions on Communication

Physical-Layer Security Enhancement in Wireless Communication Systems

Without any doubt, wireless infrastructures and services have fundamental impacts on every aspect of our lives. Despite of their popularities, wireless communications are vulnerable to various attacks due to the open nature of radio propagation. In fact, communication security in wireless networks is becoming more critical than ever. As a solution, conventional cryptographic techniques are deployed on upper layers of network protocols. Along with direct attacks from lower layer, wireless security challenges come with the rapid evolution of sophisticated decipher techniques. Conventional security mechanisms are not necessarily effective against potential attacks from the open wireless environment anymore. As an alternative, physical-layer(PHY) security, utilizing unique features from lower layer, becomes a new research focus for many wireless communication systems. In this thesis, three mechanisms for PHY security enhancement are investigated. Beginning with a discussion on the security vulnerability in highly standardized infrastructures, the thesis proposed a time domain scrambling scheme of orthogonal frequency division multiplexing (OFDM) system to improve the PHY security. The method relies on secretly scrambling each OFDM symbol in time domain, resulting in constellation transformation in frequency domain, to hide transmission features. As a complement to existing secrecy capacity maximization based optimal cooperative jamming systems, a security strategy based on the compromised secrecy region (CSR) minimization in cooperative jamming is then proposed when instantaneous channel state information(CSI) is not available. The optimal parameters of the jammer are derived to minimize the CSR which exhibits high secrecy outage probability. At last, security enhancement of OFDM system in cooperative networks is also investigated. The function selection strategies of cooperative nodes are studied. Our approach is capable of enhancing the security of broadband communications by selecting the proper function of each cooperative node. Numerical results demonstrate the feasibility of three proposed physical layer security mechanisms by examining the communication reliability, achievable CSR and secrecy capacity respectively

Preprint: Using RF-DNA Fingerprints To Classify OFDM Transmitters Under Rayleigh Fading Conditions

The Internet of Things (IoT) is a collection of Internet connected devices capable of interacting with the physical world and computer systems. It is estimated that the IoT will consist of approximately fifty billion devices by the year 2020. In addition to the sheer numbers, the need for IoT security is exacerbated by the fact that many of the edge devices employ weak to no encryption of the communication link. It has been estimated that almost 70% of IoT devices use no form of encryption. Previous research has suggested the use of Specific Emitter Identification (SEI), a physical layer technique, as a means of augmenting bit-level security mechanism such as encryption. The work presented here integrates a Nelder-Mead based approach for estimating the Rayleigh fading channel coefficients prior to the SEI approach known as RF-DNA fingerprinting. The performance of this estimator is assessed for degrading signal-to-noise ratio and compared with least square and minimum mean squared error channel estimators. Additionally, this work presents classification results using RF-DNA fingerprints that were extracted from received signals that have undergone Rayleigh fading channel correction using Minimum Mean Squared Error (MMSE) equalization. This work also performs radio discrimination using RF-DNA fingerprints generated from the normalized magnitude-squared and phase response of Gabor coefficients as well as two classifiers. Discrimination of four 802.11a Wi-Fi radios achieves an average percent correct classification of 90% or better for signal-to-noise ratios of 18 and 21 dB or greater using a Rayleigh fading channel comprised of two and five paths, respectively.Comment: 13 pages, 14 total figures/images, Currently under review by the IEEE Transactions on Information Forensics and Securit

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions