Learning End-to-End Codes for the BPSK-constrained Gaussian Wiretap Channel

Finite-length codes are learned for the Gaussian wiretap channel in an end-to-end manner assuming that the communication parties are equipped with deep neural networks (DNNs), and communicate through binary phase-shift keying (BPSK) modulation scheme. The goal is to find codes via DNNs which allow a pair of transmitter and receiver to communicate reliably and securely in the presence of an adversary aiming at decoding the secret messages. Following the information-theoretic secrecy principles, the security is evaluated in terms of mutual information utilizing a deep learning tool called MINE (mutual information neural estimation). System performance is evaluated for different DNN architectures, designed based on the existing secure coding schemes, at the transmitter. Numerical results demonstrate that the legitimate parties can indeed establish a secure transmission in this setting as the learned codes achieve points on almost the boundary of the equivocation region

An Overview of Physical Layer Security with Finite-Alphabet Signaling

Providing secure communications over the physical layer with the objective of achieving perfect secrecy without requiring a secret key has been receiving growing attention within the past decade. The vast majority of the existing studies in the area of physical layer security focus exclusively on the scenarios where the channel inputs are Gaussian distributed. However, in practice, the signals employed for transmission are drawn from discrete signal constellations such as phase shift keying and quadrature amplitude modulation. Hence, understanding the impact of the finite-alphabet input constraints and designing secure transmission schemes under this assumption is a mandatory step towards a practical implementation of physical layer security. With this motivation, this article reviews recent developments on physical layer security with finite-alphabet inputs. We explore transmit signal design algorithms for single-antenna as well as multi-antenna wiretap channels under different assumptions on the channel state information at the transmitter. Moreover, we present a review of the recent results on secure transmission with discrete signaling for various scenarios including multi-carrier transmission systems, broadcast channels with confidential messages, cognitive multiple access and relay networks. Throughout the article, we stress the important behavioral differences of discrete versus Gaussian inputs in the context of the physical layer security. We also present an overview of practical code construction over Gaussian and fading wiretap channels, and we discuss some open problems and directions for future research.Comment: Submitted to IEEE Communications Surveys & Tutorials (1st Revision

Randomized Convolutional Codes for the Wiretap Channel

We study application of convolutional codes to the randomized encoding scheme introduced by Wyner as a way of confusing the eavesdropper over a wiretap channel. We describe optimal and practical sub-optimal decoders for the main and the eavesdropper's channels, and estimate the security gap, which is used as the main metric. The sub-optimal decoder works based on the trellis of the code generated by a convolutional code and its dual, where one encodes the data bits and the other encodes the random bits. By developing a code design metric, we describe how these two generators should be selected for optimal performance over a Gaussian wiretap channel. We also propose application of serially concatenated convolutional codes to this setup so as to reduce the resulting security gaps. Furthermore, we provide an analytical characterization of the system performance by extending existing lower and upper bounds for coded systems to the current randomized convolutional coding scenario. We illustrate our findings via extensive simulations and numerical examples, which show that the newly proposed coding scheme can outperform the other existing methods in the literature in terms of security gap. © 1972-2012 IEEE

Developing a relationship between static Young’s modulus and seismic parameters

Mechanical properties of petroleum reservoirs can be determined via static techniques based on laboratory triaxial tests under reservoir conditions. Dynamic approaches represent an alternative in cases where such static laboratory data are unavailable. Dynamic elastic properties are calculated using ultrasonic wave measurements in the laboratory or in situ well logging. Different relationships have been proposed to estimate static properties from dynamic ones based on the available data from a particular reservoir. However, these relationships are often reservoir-specific, making them inadequate for general seismic inversion purposes. This research proposes a method for developing relationships between seismic parameters and static Young’s modulus in carbonate reservoirs by integrating ultrasonic measurements, well logging data, and rock mechanic tests. A multistage triaxial test simulating the reservoir conditions was used to fully control the stress and strain during the geomechanical experiments. Static Young’s modulus was cross-correlated with a broad spectrum of seismic parameters that can be extracted from seismic inversion (e.g., acoustic impedance, shear impedance, Lambda–rho, and mu–rho). Separate analytic relationships were proposed to convert dynamic Young’s modulus and seismic parameters into static Young’s modulus. Analysis of variance was used to evaluate the results and study the applicability and reliability of the obtained relationships. Furthermore, the reliability of the obtained relationships was successfully confirmed by well logging data and blind well analysis. The proposed methodology can be used to predict rock behavior for geomechanical and structural modeling

Effect of brine-CO2 fracture flow on velocity and electrical resistivity of naturally fractured tight sandstones

Fracture networks inside geological CO2 storage reservoirs can serve as primary fluid flow conduit, particularly in low-permeability formations. While some experiments focused on the geophysical properties of brine- and CO2-saturated rocks during matrix flow, geophysical monitoring of fracture flow when CO2 displaces brine inside the fracture seems to be overlooked. We have conducted laboratory geophysical monitoring of fluid flow in a naturally fractured tight sandstone during brine and liquid CO2 injection. For the experiment, the low-porosity, low-permeability naturally fractured core sample from the Triassic De Geerdalen Formation was acquired from the Longyearbyen CO2 storage pilot at Svalbard, Norway. Stress-dependence, hysteresis and the influence of fluid-rock interactions on fracture permeability were investigated. The results suggest that in addition to stress level and pore pressure, mobility and fluid type can affect fracture permeability during loading and unloading cycles. Moreover, the fluid-rock interaction may impact volumetric strain and consequently fracture permeability through swelling and dry out during water and CO2 injection, respectively. Acoustic velocity and electrical resistivity were measured continuously in the axial direction and three radial levels. Geophysical monitoring of fracture flow revealed that the axial P-wave velocity and axial electrical resistivity are more sensitive to saturation change than the axial S-wave, radial P-wave, and radial resistivity measurements when CO2 was displacing brine, and the matrix flow was negligible. The marginal decreases of acoustic velocity (maximum 1.6% for axial Vp) compared to 11% increase in axial electrical resistivity suggest that in the case of dominant fracture flow within the fractured tight reservoirs, the use of electrical resistivity methods have a clear advantage compared to seismic methods to monitor CO2 plume. The knowledge learned from such experiments can be useful for monitoring geological CO2 storage where the primary fluid flow conduit is fracture network.acceptedVersio

Programming Wireless Security through Learning-Aided Spatiotemporal Digital Coding Metamaterial Antenna

The advancement of future large-scale wireless networks necessitates the development of cost-effective and scalable security solutions. Conventional cryptographic methods, due to their computational and key management complexity, are unable to fulfill the low-latency and scalability requirements of these networks. Physical layer (PHY) security has been put forth as a cost-effective alternative to cryptographic mechanisms that can circumvent the need for explicit key exchange between communication devices, owing to the fact that PHY security relies on the physics of the signal transmission for providing security. In this work, a space-time-modulated digitally-coded metamaterial (MTM) leaky wave antenna (LWA) is proposed that can enable PHY security by achieving the functionalities of directional modulation (DM) using a machine learning-aided branch and bound (B&B) optimized coding sequence. From the theoretical perspective, it is first shown that the proposed space-time MTM antenna architecture can achieve DM through both the spatial and spectral manipulation of the orthogonal frequency division multiplexing (OFDM) signal received by a user equipment. Simulation results are then provided as proof-of-principle, demonstrating the applicability of our approach for achieving DM in various communication settings. To further validate our simulation results, a prototype of the proposed architecture controlled by a field-programmable gate array (FPGA) is realized, which achieves DM via an optimized coding sequence carried out by the learning-aided branch-and-bound algorithm corresponding to the states of the MTM LWA's unit cells. Experimental results confirm the theory behind the space-time-modulated MTM LWA in achieving DM, which is observed via both the spectral harmonic patterns and bit error rate (BER) measurements

An Overview of Physical Layer Security with Finite Alphabet Signaling

Providing secure communications over the physical layer with the objective of achieving secrecy without requiring a secret key has been receiving growing attention within the past decade. The vast majority of the existing studies in the area of physical layer security focus exclusively on the scenarios where the channel inputs are Gaussian distributed. However, in practice, the signals employed for transmission are drawn from discrete signal constellations such as phase shift keying and quadrature amplitude modulation. Hence, understanding the impact of the finite-alphabet input constraints and designing secure transmission schemes under this assumption is a mandatory step towards a practical implementation of physical layer security. With this motivation, this article reviews recent developments on physical layer security with finite-alphabet inputs. We explore transmit signal design algorithms for single-antenna as well as multi-antenna wiretap channels under different assumptions on the channel state information at the transmitter. Moreover, we present a review of the recent results on secure transmission with discrete signaling for various scenarios including multi-carrier transmission systems, broadcast channels with confidential messages, cognitive multiple access and relay networks. Throughout the article, we stress the important behavioral differences of discrete versus Gaussian inputs in the context of the physical layer security. We also present an overview of practical code construction over Gaussian and fading wiretap channels, and discuss some open problems and directions for future research