Physical layer security of MIMO–OFDM systems by beamforming and artificial noise generation

Romero-Zurita, Nabil; Ghogho, Mounir; McLernon, Des

doi:10.1016/j.phycom.2011.10.004

Cited by 34 publications

(29 citation statements)

References 15 publications

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“…Typically, the transmission power of a jamming signal is equal to the transmission power of the information-bearing signal [48], which means that an additional radio unit is required to transmit the jamming signal. As a result, the energy consumption of the transmitter employing secrecy-coding is doubled.…”

Section: Efficiency Of Polar-ldpc Secrecy Coding Schemementioning

confidence: 99%

Evaluating the Efficiency of Physical and Cryptographic Security Solutions for Quantum Immune IoT

et al. 2018

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Abstract:The threat of quantum-computer-assisted cryptanalysis is forcing the security community to develop new types of security protocols. These solutions must be secure against classical and post-quantum cryptanalysis techniques as well as feasible for all kinds of devices, including energy-restricted Internet of Things (IoT) devices. The quantum immunity can be implemented in the cryptographic layer, e.g., by using recent lattice-based key exchange algorithms NewHope or Frodo, or in the physical layer of wireless communication, by utilizing eavesdropping-resistant secrecy coding techniques. In this study, we explore and compare the feasibility and energy efficiency of selected cryptographic layer and physical layer approaches by applying an evaluation approach that is based on simulation and modeling. In particular, we consider NewHope and Frodo key exchange algorithms as well as novel physical layer secrecy coding approach that is based on polar codes. The results reveal that our proposed physical layer implementation is very competitive with respect to the cryptographic solutions, particularly in short-range wireless communication. We also observed that the total energy consumption is unequally divided between transmitting and receiving devices in all the studied approaches. This may be an advantage when designing security architectures for energy-restricted devices.

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Section: Efficiency Of Polar-ldpc Secrecy Coding Schemementioning

confidence: 99%

Evaluating the Efficiency of Physical and Cryptographic Security Solutions for Quantum Immune IoT

et al. 2018

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“…As such, the relationship between the information signal power (P x ) and the total source power (P s ) can be written as P x = εP s , where ε ∈ [0, 1) is the fraction factor, whereas the relationship between the AN power and the total power is σ . To allocate the source power, we consider the following two approaches [6], [16]. In the first approach, the fraction factor is progressively varied from 0 to 1, then the impact of this variation on the secrecy rate can be observed.…”

Section: B Source Power Allocationmentioning

confidence: 99%

Improving Physical Layer Security of AF Relay Networks via Beam-Forming and Jamming

Salem

Hamdi²

2016

2016 IEEE 84th Vehicular Technology Conference (VTC-Fall)

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Abstract-In this paper the cooperation of beam-forming and artificial noise (AN) in two-hop amplify-and-forward (AF) relaying system is proposed to enhance the security. we consider a half duplex AF relaying network with a multi-antenna source node and a destination in the presence of a passive eavesdropper. Since channel state information (CSI) of the eavesdropper is unknown, the AN transmitted by the source in the first phase and by the relays in the second phase is in all directions except the legitimate node one. As such two scenarios are considered here,: i) when all the relays amplify and forward the information source signal ii) when only the best relay is selected to amplify and forward the information source signal. The beam-former weights and the power allocation are obtained by solving an optimization problem. Results reveal that the proposed system can provide considerable improvements in terms of secrecy rate. It is also found that increasing the AN power, relative to the information signal power, will further improve the secrecy rate.

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“…During this iterative process, periodically, a member sensor node observes its fitness in an entirely distributed mode and evaluates its current fitness with the average fitness of the whole WSNs. If the difference is larger than a predefined maximum bound, then the member International Journal of Distributed Sensor Networks 7 sensor node selects a new power level strategy according to the selection dynamics from (15). This interactive process goes on until the ESS of the secrecy rate game towards WSNs is achieved.…”

Section: Secrecy Rate Adaptationmentioning

confidence: 99%

Evolutionary Game-Based Secrecy Rate Adaptation in Wireless Sensor Networks

Jiang

Shen

et al. 2015

International Journal of Distributed Sensor Networks

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Physical layer security, whose aim is to maximize the secrecy rate of a source while keeping eavesdroppers ignorant of data transmitted, is extremely suitable for Wireless Sensor Networks (WSNs). We therefore, by developing the classical wire-tap channel, construct an approach to compute the secrecy rate between a sensor node and its responsible cluster head in the clustered WSNs. A noncooperative secrecy rate game towards WSNs is formulated to solve contradictions between maximizing the secrecy rate of a sensor node and minimizing power consumed for data transmission. Using evolutionary game theory, we set up a selection dynamics upon which a power level can be adaptively selected by a sensor node. Thus, the objective of secrecy rate adaptation for maximizing the fitness of member sensor nodes is achieved. We also prove the game is stable; that is, there exist evolutionarily stable strategies (ESSs) that explain which strategies will be selected by a sensor node in the end. Moreover, a corresponding algorithm of secrecy rate adaptation is given. Numerical experiments show our proposed approach can adaptively adjust the secrecy rate of a sensor node, which provides a novel way to guarantee the confidentiality of WSNs.

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Physical layer security of MIMO–OFDM systems by beamforming and artificial noise generation

Cited by 34 publications

References 15 publications

Evaluating the Efficiency of Physical and Cryptographic Security Solutions for Quantum Immune IoT

Evaluating the Efficiency of Physical and Cryptographic Security Solutions for Quantum Immune IoT

Improving Physical Layer Security of AF Relay Networks via Beam-Forming and Jamming

Evolutionary Game-Based Secrecy Rate Adaptation in Wireless Sensor Networks

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