A Collaborative PHY-Aided Technique for End-to-End IoT Device Authentication

Peng, Hao; Wang, Xianbin; Shen, Weiming

doi:10.1109/access.2018.2859781

Cited by 48 publications

(38 citation statements)

References 37 publications

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“…6 shows the offline MEB quantization boundaries derived by Algorithm 1 with the comparison of the two other methods, which are named uniform and random. To be specific, the widths of all M quantization intervals are the same regardless of the PDF of a in the uniform method [30]. In the random method, all boundaries are randomly picked within [a min , a max ].…”

Section: A Numerical Resultsmentioning

confidence: 99%

“…We assume that an ED's imperfect RF front-end can process signals using the in-phase/quadrature-phase (IQ) processing, where the signals suffer from the imbalanced gain and phase-shift between I-channel and Q-channel mainly due to the imperfect local oscillator and mixer [31]. We use θ and α to represent phaseshift mismatch and amplitude mismatch, respectively, where the independent θ and α follow the uniform distributions , θ ∼ U (−θ m , θ m ) and α ∼ U (−α m , α m ), and θ m > 0 and α m > 0 are regulated by the RF manufacturer/market [30], [32], [33]. We consider that all EDs in the MECD's coverage are produced under the same maximum α and θ requirement.…”

Section: Framework Of the System And Proposed Methodsmentioning

confidence: 99%

“…The well-established RF fingerprinting technology is robust in nature due to the immense difficulty in arbitrarily changing hardware-level RF features within the short duration of an authentication session. Additionally, given the low distinguishability of rangelimited RF parameters, the authors of [30] used the entropy to measure the randomness of PHY-ID and proposed the multiple-attributes multiple-observations (MAMO) technique to improve the authentication accuracy through increasing the entropy. However, the optimal entropy-based method was not derived, and thus its performance under a high density of IoT devices is obviously deteriorated.…”

Section: B Related Work and Technical Problemsmentioning

confidence: 99%

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Integrating PHY Security Into NDN-IoT Networks By Exploiting MEC: Authentication Efficiency, Robustness, and Accuracy Enhancement

Peng

Wang

2019

IEEE Trans. on Signal and Inf. Process. over Networks

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2 signal compensation purposes. These readily available estimates can be cost-effectively used to produce an unforgeable PHY identity (PHY-ID) for transmitter authentication [13]- [17], which has the potential to help relieve the excessive computational burden of the signature encryption.Exploitation of MEC: MEC devices (MECDs) located at the network edge can quickly observe/collect the PHY information of the served IoT devices, including the RF fingerprints, and usually possess more powerful CPUs than the EDs for performing encryption. The NDN naming and in-network caching schemes with built-in interest/data primitives are wellsuited for MEC-enabled networks [18], [19].Consequently, it is practically feasible to replace the NDN packet signing at the resource-constrained ED with two steps: 1) MECD authenticates ED using PHY-ID, and 2) MECD works with the authenticated EDs in a coordinated manner to offload the signing task from EDs [20]- [22].

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Section: A Numerical Resultsmentioning

confidence: 99%

Section: Framework Of the System And Proposed Methodsmentioning

confidence: 99%

Section: B Related Work and Technical Problemsmentioning

confidence: 99%

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Integrating PHY Security Into NDN-IoT Networks By Exploiting MEC: Authentication Efficiency, Robustness, and Accuracy Enhancement

Peng

Wang

2019

IEEE Trans. on Signal and Inf. Process. over Networks

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“…Strategies such as Light-weight security protocols, Elliptic Curve Cryptography (ECC), Identity Based Encryption (IBE), and security protocols for direct Machine Type Communication (MTC) and UE engagement as proposed in [25], could be utilized for forming authentication mechanisms through this channel [26]. Moreover, Physical Unclonable Functions (PUF) are offering possibilities to derive bio-metric resembled unique features for IoT devices, which are enhancing the security of authentication and data transferring mechanisms conducted in UE enrolled communication channels [27].…”

Section: Possible Solutionsmentioning

confidence: 99%

Realizing Multi-Access Edge Computing Feasibility: Security Perspective

Ranaweera

Jurcut

Liyanage

2019

2019 IEEE Conference on Standards for Communications and Networking (CSCN)

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Internet of Things (IoT) and 5G are emerging technologies that prompt a mobile service platform capable of provisioning billions of communication devices which enable ubiquitous computing and ambient intelligence. These novel approaches are guaranteeing gigabit-level bandwidth, ultra-low latency and ultra-high storage capacity for their subscribers. To achieve these limitations, ETSI has introduced the paradigm of Multi-Access Edge Computing (MEC) for creating efficient data processing architecture extending the cloud computing capabilities in the Radio Access Network (RAN). Despite the gained enhancements to the mobile network, MEC is subjected to security challenges raised from the heterogeneity of IoT services, intricacies in integrating virtualization technologies, and maintaining the performance guarantees of the mobile networks (i.e. 5G). In this paper, we are identifying the probable threat vectors in a typical MEC deployment scenario that comply with the ETSI standards. We analyse the identified threat vectors and propose solutions to mitigate them.

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“…Significance of security and trust is discussed by Hudson [17]. Device authentication problem has been discussed by Hao et al [18] where the physical layer has been used while Li et al [19] has used trust factor as a part of the evaluation process.…”

Section: Introductionmentioning

confidence: 99%

Novel authentication framework for securing communication in internet-of-things

Patil¹,

Biradar²

2020

IJECE

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Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats.The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.

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A Collaborative PHY-Aided Technique for End-to-End IoT Device Authentication

Cited by 48 publications

References 37 publications

Integrating PHY Security Into NDN-IoT Networks By Exploiting MEC: Authentication Efficiency, Robustness, and Accuracy Enhancement

Integrating PHY Security Into NDN-IoT Networks By Exploiting MEC: Authentication Efficiency, Robustness, and Accuracy Enhancement

Realizing Multi-Access Edge Computing Feasibility: Security Perspective

Novel authentication framework for securing communication in internet-of-things

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