Physical layer assisted authentication for distributed ad hoc wireless sensor networks

Wen, Haiying; Ho, Pin–Han; Qi, Chun; Gong, Guang

doi:10.1049/iet-ifs.2009.0197

Cited by 37 publications

(16 citation statements)

References 7 publications

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“…AdaBoost Algorithm. AdaBoost is the abbreviation of adaptive boosting and developed by Yoav Freund [24] and is 4 Wireless Communications and Mobile Computing the most widely used form of boosting algorithm. Boosting is a powerful technique combined with base classifiers [25] to produce a form of committee whose performance can be significantly better than other base classifiers.…”

Section: Physical Authentication With Adaboost Algorithmmentioning

confidence: 99%

“…In [21], Peng Hao et al developed a practical authentication scheme by monitoring and analyzing the packet error rate (PER) and received signal strength indicator (RSSI) at the same time to enhance the spoofing attack detection capability. In [22][23][24], the authors analysed the spatial decorrelation property of the channel response and validated the efficacy of the channel-based authentication for spoofing detection in MIMO system by the comparison between channel information "difference" of two or several frames.…”

Section: Introductionmentioning

confidence: 99%

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Physical-Layer Channel Authentication for 5G via Machine Learning Algorithm

Chen

Wen

et al. 2018

Wireless Communications and Mobile Computing

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By utilizing the radio channel information to detect spoofing attacks, channel based physical layer (PHY-layer) enhanced authentication can be exploited in light-weight securing 5G wireless communications. One major obstacle in the application of the PHY-layer authentication is its detection rate. In this paper, a novel authentication method is developed to detect spoofing attacks without a special test threshold while a trained model is used to determine whether the user is legal or illegal. Unlike the threshold test PHY-layer authentication method, the proposed AdaBoost based PHY-layer authentication algorithm increases the authentication rate with one-dimensional test statistic feature. In addition, a two-dimensional test statistic features authentication model is presented for further improvement of detection rate. To evaluate the feasibility of our algorithm, we implement the PHY-layer spoofing detectors in multiple-input multiple-output (MIMO) system over universal software radio peripherals (USRP). Extensive experiences show that the proposed methods yield the high performance without compromising the computing complexity.

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Section: Physical Authentication With Adaboost Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Physical-Layer Channel Authentication for 5G via Machine Learning Algorithm

Chen

Wen

et al. 2018

Wireless Communications and Mobile Computing

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“…Zeng et al in [7] conducted a survey of several non-cryptographic methods that use physical layer information in both static and mobile wireless networks. Wen et al in [8] introduced a message authentication framework which uses physical layer data to perform cryptography.…”

Section: Authenticationmentioning

confidence: 99%

An improved authentication scheme for applying RFID in VANETs

Zhang

Almulla

Boukerche

2013

2013 IEEE Symposium on Computers and Communications (ISCC)

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This paper presents an improved authentication scheme for Radio-frequency identification (RFID) applied in VANETs. As often being considered as a precondition for the realization of IoT, RFID can be utilized in the vehicles, so as to make the vehicles identifiable and inventoriable by computers as long as they are fitted out with radio tags. One of the main concerns is to address the large number of security and privacy issues. A few light symmetric key management schemes have been proposed for RFID scenarios. We suggest EKA2 which is a new certificate revocation status validation scheme, and we use the concept of clustering from data mining to evaluate the trustiness of digital certificates.

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“…Authentication is an effective approach to deal with such identity-based attacks, by which the intended receivers can verify the identities of involved transmitting users and make sure that the received data come from the expected user [ 2 ]. Traditional authentication mechanisms are handled at the upper-layer using key-based cryptography.…”

Section: Introductionmentioning

confidence: 99%

“…Compared with traditional key-based authentication mechanisms, wireless channel characteristics are very hard to mimic. Consequently, physical-layer authentication can achieve fast and efficient message authentication [ 2 ], and therefore has been recently used as a complementary enhancement to existing upper-layer authentication [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

A Novel Physical Layer Assisted Authentication Scheme for Mobile Wireless Sensor Networks

Wang

2017

Sensors

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Physical-layer authentication can address physical layer vulnerabilities and security threats in wireless sensor networks, and has been considered as an effective complementary enhancement to existing upper-layer authentication mechanisms. In this paper, to advance the existing research and improve the authentication performance, we propose a novel physical layer assisted authentication scheme for mobile wireless sensor networks. In our proposed scheme, we explore the reciprocity and spatial uncorrelation of the wireless channel to verify the identities of involved transmitting users and decide whether all data frames are from the same sender. In our proposed scheme, a new method is developed for the legitimate users to compare their received signal strength (RSS) records, which avoids the information from being disclosed to the adversary. Our proposed scheme can detect the spoofing attack even in a high dynamic environment. We evaluate our scheme through experiments under indoor and outdoor environments. Experiment results show that our proposed scheme is more efficient and achieves a higher detection rate as well as keeping a lower false alarm rate.

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Physical layer assisted authentication for distributed ad hoc wireless sensor networks

Cited by 37 publications

References 7 publications

Physical-Layer Channel Authentication for 5G via Machine Learning Algorithm

Physical-Layer Channel Authentication for 5G via Machine Learning Algorithm

An improved authentication scheme for applying RFID in VANETs

A Novel Physical Layer Assisted Authentication Scheme for Mobile Wireless Sensor Networks

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