Optimal Pilots for Anti-Eavesdropping Channel Estimation

Zhu, Qiping; Wu, Shuo; Hua, Yingbo

doi:10.1109/tsp.2020.2986307

Cited by 12 publications

(9 citation statements)

References 25 publications

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“…Any set of pilots satisfying rank(P (i) ) = N T − N for all i and rank( P) = r ≤ N T − 1 is called a set of ANECE pilots. Optimal designs of the ANECE pilots are discussed in [9].…”

Section: A System Modelmentioning

confidence: 99%

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Total Secrecy From Anti-Eavesdropping Channel Estimation

Hua

2022

IEEE Trans. Signal Process.

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“…Any set of pilots satisfying rank(P (i) ) = N T − N for all i and rank( P) = r ≤ N T − 1 is called a set of ANECE pilots. Optimal designs of the ANECE pilots are discussed in [9].…”

Section: A System Modelmentioning

confidence: 99%

“…A major finding is that the SDoF of C key with respect to the channel training energy is the same for all these training methods. The analysis of C key builds on the prior work in [9] where optimal ANECE pilots were derived.…”

Section: Introductionmentioning

confidence: 99%

Total Secrecy From Anti-Eavesdropping Channel Estimation

Hua

2022

IEEE Trans. Signal Process.

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“…If the security of the reference signal is ensured, the attacker can not learn about the environment. Several techniques have been proposed in the literature to ensure the security of reference signal including pilot tone manipulation [68], artificial noise embedding [69], and anti-eavesdropping pilot design [70].…”

Section: ) Security For Reference Signalmentioning

confidence: 99%

“…In [69], artificial noise is embedded in the pilot signal based on the uplink CSI to degrade the channel estimation performance at the attacker during downlink pilot transmission. Finally, [70] is based on the design of special anti-eavesdropping pilots for legitimate nodes with full-duplex capabilities. Particularly, the pilots from the legitimate nodes are designed in such a way that the composite pilot matrix has a full rank for legitimate nodes while having rank deficiency with respect to the attacker.…”

Section: ) Security For Reference Signalmentioning

confidence: 99%

Wireless Communication, Sensing, and REM: A Security Perspective

Furqan

Solaija

Türkmen

et al. 2021

IEEE Open J. Commun. Soc.

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The diverse requirements of next-generation communication systems necessitate awareness, flexibility, and intelligence as essential building blocks of future wireless networks. The awareness can be obtained from the radio signals in the environment using wireless sensing and radio environment mapping (REM) methods. This is, however, accompanied by threats such as eavesdropping, manipulation, and disruption posed by malicious attackers. To this end, this work analyzes the wireless sensing and radio environment awareness mechanisms, highlighting their vulnerabilities and provides solutions for mitigating them. As an example, the different threats to REM and its consequences in a vehicular communication scenario are described. Furthermore, the use of REM for securing communications is discussed and future directions regarding sensing/REM security are highlighted.INDEX TERMS 5G, 6G, cryptography, joint radar and communication (JRC), physical layer security, radio environment mapping (REM), REM security, sensing security, vehicle-to-everything (V2X) communication, wireless sensing, WLAN sensing.As explained earlier, our surroundings contain a myriad of radio signals. These signals can be leveraged to extract information about the environment itself and the users/devices within. As such, a malicious node might have the following motivations when attacking a (communication and/or sensing) wireless network:• Confidentiality Violation: The malicious node tries to intercept either the communication or characteristics of the legitimate nodes. In the context of sensing, this information may include a user's location, mobility pattern, social trends, etc. • Degradation: The malicious node attempts to impair the communication link and/or sensing capabilities of the legitimate parties. • Exploitation: The malicious node tries to exploit the communication and/or sensing for its own benefit. This may include learning and then manipulating the legitimate communication (or sensing) to acquire resources for itself.Corresponding to the aforementioned intentions of the malicious attackers, the network strives to guarantee that its nodes and users are protected. This includes ensuring no illegitimate access to the information/transmission is allowed, the data shared between legitimate nodes is accurate, and there is no disruption of the services offered by the network [16]. B. SECURITY THREATS -COMMUNICATION VS SENSINGThe broadcast nature of wireless communication (or signals in general) renders it susceptible to various security threats. Given below is an overview of how these threats compare for communication and sensing aspects.

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“…On top of that, power allocation between pilot and noise signal needs to be done intelligently in order to enhance security performance. Similarly, in [23], anti-eavesdropping pilots are designed such that the channel can be estimated at legitimate nodes only. However, the proposed algorithm requires full-duplex communication.…”

Section: A Pls Literature Reviewmentioning

confidence: 99%

Flexible Physical Layer Security for Joint Data and Pilots in Future Wireless Networks

Zegrar¹,

Furqan²,

Arslan³

2021

Preprint

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In this work, novel physical layer security (PLS) schemes are proposed for orthogonal frequency-division multiplexing (OFDM) to secure both data and pilots. The majority of previous studies focus on only securing the data without considering the security of the pilots used for channel estimation. However, the leakage of channel state information (CSI) from a legitimate node to an eavesdropper allows the latter to acquire knowledge about the channel of the legitimate nodes. To this end, we propose adaptive and flexible PLS algorithms which can 1) secure data, 2) secure pilots, and 3) jointly secure both data and pilots. Particularly, minimum-phase all-pass channel decomposition is exploited, where the proposed algorithms use the all-pass component to provide security without harming the performance of the legitimate user. In the analysis for data security, we evaluated the secrecy under correlated and uncorrelated eavesdropping channels via closed-form bit error rate (BER) formulas. For pilot security, we analyzed the normalized mean squared error (NMSE) performance of the estimated channel. The simulation results along with theoretical analysis demonstrate that the proposed algorithms can effectively enhance the communication secrecy of the overall system.

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Optimal Pilots for Anti-Eavesdropping Channel Estimation

Cited by 12 publications

References 25 publications

Total Secrecy From Anti-Eavesdropping Channel Estimation

Total Secrecy From Anti-Eavesdropping Channel Estimation

Wireless Communication, Sensing, and REM: A Security Perspective

Flexible Physical Layer Security for Joint Data and Pilots in Future Wireless Networks

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