Secure space-time block coding via artificial noise alignment

Fakoorian, S. Ali. A.; Jafarkhani, Hamid; Swindlehurst, A. Lee

doi:10.1109/acssc.2011.6190083

Cited by 21 publications

(24 citation statements)

References 10 publications

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“…This scrambles the PSK symbols in all the directions other than that of the legitimate receiver. Other strategies for securing communications without the knowledge of the eavesdropper's channel are proposed in [50] and [52]. Zhang et al develop a Tomlinson-Harashima precoding in [50] where the transmitter allocates part of its power in order to achieve a target mean squared error (MSE) at the legitimate receiver, and the remaining power is used to transmit artificial noise to degrade the eavesdropper's reception.…”

Section: Perfect Mcsi Onlymentioning

confidence: 99%

An Overview of Physical Layer Security With Finite-Alphabet Signaling

Aghdam

Nooraiepour

Duman

2019

IEEE Commun. Surv. Tutorials

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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 toward a practical implementation of physical layer security. With this motivation, this paper 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.

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Section: Perfect Mcsi Onlymentioning

confidence: 99%

An Overview of Physical Layer Security With Finite-Alphabet Signaling

Aghdam

Nooraiepour

Duman

2019

IEEE Commun. Surv. Tutorials

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“…The fact that STBCs were designed to operate without CSIT and have low complexity raises the question if they can also be applied to secrecy scenarios. The limited work in this area includes [84]- [86], for MIMO scenarios with multiple transmit and receive antennas. Fakoorian et al [84] proposed a rate-one secure STBC that allows for separable, low complexity (symbolwise) decoding at the intended receiver but not at the EFC (which must perform ML detection).…”

Section: Secure Space-time Codingmentioning

confidence: 99%

“…The limited work in this area includes [84]- [86], for MIMO scenarios with multiple transmit and receive antennas. Fakoorian et al [84] proposed a rate-one secure STBC that allows for separable, low complexity (symbolwise) decoding at the intended receiver but not at the EFC (which must perform ML detection). This is achieved by ensuring that the effective STBC precoding matrix over two time slots has orthogonal columns when seen at the intended receiver, however, this scheme assumes complete CSIT of the main channel.…”

Section: Secure Space-time Codingmentioning

confidence: 99%

“…The decoding performance of the intended receiver and the EFC will be different, since with high probability the two strongest transmit antennas on the main channel will not be the two strongest antennas to the EFC. However, unlike [84] which used BER to characterize EFC performance, the average SINR to the EFC is also assumed to be known at the transmitter so as to achieve a nonzero secrecy rate.…”

Section: Secure Space-time Codingmentioning

confidence: 99%

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Physical-Layer Security in the Internet of Things: Sensing and Communication Confidentiality Under Resource Constraints

2015

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| The Internet of Things (IoT) will feature pervasive sensing and control capabilities via a massive deployment of machine-type communication (MTC) devices. The limited hardware, low-complexity, and severe energy constraints of MTC devices present unique communication and security challenges. As a result, robust physical-layer security methods that can supplement or even replace lightweight cryptographic protocols are appealing solutions. In this paper, we present an overview of low-complexity physical-layer security schemes that are suitable for the IoT. A local IoT deployment is modeled as a composition of multiple sensor and data subnetworks, with uplink communications from sensors to controllers, and downlink communications from controllers to actuators. The state of the art in physical-layer security for sensor networks is reviewed, followed by an overview of communication network security techniques. We then pinpoint the most energy-efficient and low-complexity security techniques that are best suited for IoT sensing applications. This is followed by a discussion of candidate low-complexity schemes for communication security, such as ON-OFF switching and space-time block codes. The paper concludes by discussing open research issues and avenues for further work, especially the need for a theoretically well-founded and holistic approach for incorporating complexity constraints in physical-layer security designs.

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“…Therefore, interference emerges as a potentially valuable resource for wireless network secrecy [2]. The idea of enhancing network secrecy through the use of interference has been investigated in several recent works, under the name of artificial noise [3], [4], artificial noise alignment [5], [6], friendly jamming [7], [8], or cooperative jamming [9]- [12]. A major challenge in utilizing interference to enhance secrecy is L. Ruan that while impeding the ERs, interference affects the LRs as well.…”

Section: A Background and Surveymentioning

confidence: 99%

Generalized Interference Alignment—Part II: Application to Wireless Secrecy

Ruan

Lau

Win

2016

IEEE Trans. Signal Process.

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Abstract-In contrast to its wired counterpart, wireless communication is highly susceptible to eavesdropping due to the broadcast nature of the wireless propagation medium. Recent works have proposed the use of interference to reduce eavesdropping capabilities in wireless wiretap networks. However, the concurrent effect of interference on both eavesdropping receivers (ERs) and legitimate receivers (LRs) has not been thoroughly investigated, and carefully engineering the network interference is required to harness the full potential of interference for wireless secrecy. This two part paper addresses this issue by proposing a generalized interference alignment (GIA) technique, which jointly designs the transceivers at the legitimate partners to impede the ERs without interfering with LRs. In Part I, we have established a theoretical framework for the GIA technique. In Part II, we will first propose an efficient GIA algorithm that is applicable to large-scale networks and then evaluate the performance of this algorithm in stochastic wireless wiretap network via both analysis and simulation. These results reveal insights into when and how GIA contributes to wireless secrecy.

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Secure space-time block coding via artificial noise alignment

Cited by 21 publications

References 10 publications

An Overview of Physical Layer Security With Finite-Alphabet Signaling

An Overview of Physical Layer Security With Finite-Alphabet Signaling

Physical-Layer Security in the Internet of Things: Sensing and Communication Confidentiality Under Resource Constraints

Generalized Interference Alignment—Part II: Application to Wireless Secrecy

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