| 1. |
- Chen, Zhiwei, et al.
(författare)
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Cross-Device Radio Frequency Fingerprinting Identification Based on Domain Adaptation
- 2024
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Ingår i: IEEE transactions on consumer electronics. - : Institute of Electrical and Electronics Engineers (IEEE). - 0098-3063 .- 1558-4127. ; 70:1, s. 2391-2400
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Tidskriftsartikel (refereegranskat)abstract
- Radio frequency fingerprinting (RFF) is a lightweight authentication technology for resource-limited terminal nodes by exploiting the unique hardware imperfections resulting from the manufacturing process. Previous studies about radio frequency fingerprinting identification (RFFI) mainly concentrate on improving the accuracy which is evaluated by the single receiver device that trains and identifies all the nodes. Due to the mobility of the consumer electronic terminals, these terminal nodes may need to be identified by the different receivers. In this paper, we propose a cross-device radio frequency fingerprinting identification scheme which allows enrolled nodes to be authenticated by different devices. Motivated by the observation that signals collected by different receiver devices have a distribution shift that would violate the basic independent and identically distributed (i.i.d) assumption of supervised learning. Domain adaptation is adopted to improve the accuracy under different receivers, which can align the data captured from different devices and eliminate the distribution shift through the labeled data from one receiver device and unlabeled data from the other device. By this way, the distribution shift from different devices is corrected. Extensive experiment configurations under various Signal-to-noise ratio (SNR) are carried out to demonstrate the performance of domain adaptation with the same model structure. The results indicate that classification accuracy under different devices can be increased by 7%-15% and get a stable accuracy rate higher than 90% by leveraging our proposed cross-device RFFI scheme.
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| 2. |
- Lei, Wenxin, et al.
(författare)
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FDI Attack Detection at the Edge of Smart Grids Based on Classification of Predicted Residuals
- 2022
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 18:12, s. 9302-9311
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Tidskriftsartikel (refereegranskat)abstract
- The introduction of information and communication technologies makes network environments increasingly open, leaving smart-grid control systems incredibly vulnerable to malicious attacks. False data injection (FDI) attacks stealthily tamper with measurement data, resulting in erroneous decisions made by the control center that greatly influence the normal operation of the power system. By taking advantage of real-time data acquisition with edge computing, in this article, we propose a scheme based on classification of predicted residuals (CPRs) for the FDI attack detection. The CPR scheme first predicts the acquired measurement data at the edge of the sensing network via developing an accurate prediction model. Followed the novel real-time classification method under the edge devices supporting, it classifies the predicted residuals independent of the false data to enhance the detection accuracy. Through these two steps, the detection rate of FDI attacks is greatly improved. The proposed scheme is validated in a real microgrid testbed. Experimental results show that the CPR scheme performs well in detecting FDI attacks and remains sensitive in injection attack probability and magnitude. The detection scheme even has effectiveness at low injection attack probability and magnitude (5% and 0.018 per thousand, respectively). Furthermore, it also proves that the proposed scheme has applicability in high real-time requirements at the edge of smart grids.
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| 3. |
- Han, Zheng, et al.
(författare)
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Dynamic contrast-enhanced CEST MRI using a low molecular weight dextran
- 2022
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 35:3
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Tidskriftsartikel (refereegranskat)abstract
- Natural and synthetic sugars have great potential for developing highly biocompatible and translatable chemical exchange saturation transfer (CEST) MRI contrast agents. In this study, we aimed to develop the smallest clinically available form of dextran, Dex1 (molecular weight, MW ~ 1 kDa), as a new CEST agent. We first characterized the CEST properties of Dex1 in vitro at 11.7 T and showed that the Dex1 had a detectable CEST signal at ~1.2 ppm, attributed to hydroxyl protons. In vivo CEST MRI studies were then carried out on C57BL6 mice bearing orthotopic GL261 brain tumors (n = 5) using a Bruker BioSpec 11.7 T MRI scanner. Both steady-state full Z-spectral images and single offset (1.2 ppm) dynamic dextran-enhanced (DDE) images were acquired before and after the intravenous injection of Dex1 (2 g/kg). The steady-state Z-spectral analysis showed a significantly higher CEST contrast enhancement in the tumor than in contralateral brain (∆MTRasym 1.2 ppm = 0.010 ± 0.006 versus 0.002 ± 0.008, P = 0.0069) at 20 min after the injection of Dex1. Pharmacokinetic analyses of DDE were performed using the area under the curve (AUC) in the first 10 min after Dex1 injection, revealing a significantly higher uptake of Dex1 in the tumor than in brain tissue for tumor-bearing mice (AUC[0-10 min] = 21.9 ± 4.2 versus 5.3 ± 6.4%·min, P = 0.0294). In contrast, no Dex1 uptake was foundling in the brains of non-tumor-bearing mice (AUC[0-10 min] = -1.59 ± 2.43%·min). Importantly, the CEST MRI findings were consistent with the measurements obtained using DCE MRI and fluorescence microscopy, demonstrating the potential of Dex1 as a highly translatable CEST MRI contrast agent for assessing tumor hemodynamics.
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| 4. |
- Lei, Wenxin, et al.
(författare)
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Edge-enabled Zero Trust Architecture for ICPS with Spatial and Temporal Granularity
- 2023
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Ingår i: Proceedings - 2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems, ICPS 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Motivated by the rapid advancement of industrial cyber-physical systems (ICPS) and rising voices in favor of zero trust (ZT) security, in this paper, we present an edge-enabled zero trust architecture (ZTA) for ICPS. ZT is thought to be relevant to ICPS with the spatial and temporal granularity in the suggested architecture. In addition to continuous authentication and a dynamic access-control mechanism at the temporal granularity, we recommend edge segmentation at the spatial granularity with microservices as the division units. Finally, we conduct a security assessment of the proposed architecture in the presence of threats faced by ICPS. Overall, our analysis shows that the proposed ZTA helps to promote the security of ICPS.
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| 5. |
- Pan, Fei, et al.
(författare)
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Clone Detection Based on Physical Layer Reputation for Proximity Service
- 2019
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Ingår i: IEEE Access. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2169-3536. ; 7, s. 3948-3957
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Tidskriftsartikel (refereegranskat)abstract
- Proximity-based service (ProSe) provides direct communications among smart sensor nodes in proximity which aims at reserving resource consumption and alleviating the load in base stations, which is a promising solution for smart sensor systems that possess limited computing and energy resources. During the ProSe direct communications, most of the prior art security methods are usually provided by the ProSe function and are based on complex cryptography. However, despite the computing complexity, it is difficult for cryptographic methods to detect clone attack which is a common kind of attack in sensor systems. Clone nodes feature different physical positions but claim colliding IDs with captured nodes. Thus, clone nodes can be detected by spatial differences, in particular, by the surveillance of physical layer channel state information (CSI). However, CSI is not absolute static due to the random noise in wireless propagation environment. Accordingly, the detection accuracy varies with the stability of CSI. To address this challenge, we take the first attempt to introduce physical layer reputation and then elaborate the physical layer reputation based clone detection protocol to detect clone attack in multiple scenarios. The proposed protocol significantly improves the detection rate and false alarm rate and it is validated both by simulations and realizations.
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| 6. |
- Pan, Fei, et al.
(författare)
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Physical-Layer Security for Industrial Wireless Control Systems
- 2018
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Ingår i: IEEE Industrial Electronics Magazine. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1932-4529 .- 1941-0115. ; 12:4, s. 18-27
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Tidskriftsartikel (refereegranskat)abstract
- Wireless networks for industrial control systems are promising because of their reduced cost, flexible structure, and improved long-term reliability. However, wireless control systems are vulnerable to probing-free attacks (PFAs), which are not possible in wired control systems. Thus, wireless control systems must be made as secure as wired systems. Physical (PHY)-layer security technology (PHY-Sec) may be a new strategy for securing industrial wireless control systems. Among all PHY-Sec technologies, PHY-layer authentication is the first step for PHYSec in industrial wireless control systems. This article discusses the principles of PHY-Sec, its application to wireless control systems, and potential research directions.
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| 7. |
- Pan, Fei, et al.
(författare)
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Threshold-Free Physical Layer Authentication Based on Machine Learning for Industrial Wireless CPS
- 2019
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Ingår i: IEEE Transactions on Industrial Informatics. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1551-3203 .- 1941-0050. ; 15:12, s. 6481-6491
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Tidskriftsartikel (refereegranskat)abstract
- Wireless industrial cyber-physical systems are increasingly popular in critical manufacturing processes. These kinds of systems, besides high performance, require strong security and are constrained by low computational capabilities. Physical layer authentication (PHY-AUC) is a promising solution to meet these requirements. However, the existing threshold-based PHY-AUC methods only perform ideally in stationary scenarios. To improve the performance of PHY-AUC in mobile scenarios, this article proposes a novel threshold-free PHY-AUC method based on machine learning (ML), which replaces the traditional threshold-based decision-making with more adaptive classification based on ML. This article adopts channel matrices estimated by the wireless nodes as the authentication input and investigates the optimal dimension of the channel matrices to further improve the authentication accuracy without increasing too much computational burden. Extensive simulations are conducted based on a real industrial dataset, with the aim of tuning the authentication performance, then further field validations are performed in an industrial factory. The results from both the simulations and validations show that the proposed method significantly improves the authentication accuracy.
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| 8. |
- Xie, Feiyi, et al.
(författare)
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Weighted Voting in Physical Layer Authentication for Industrial Wireless Edge Networks
- 2022
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 18:4, s. 2796-2806
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Tidskriftsartikel (refereegranskat)abstract
- Edge computing (EC) is an essential component of large-scale intelligent manufacturing systems for Industry 4.0, which promises to provide a preprocessing platform for the massive data generated by the terminals and guarantee lower delay and more security compared to directly processing data in cloud computing. Nevertheless, access authentication is a crucial security issue of current EC systems, and, thus, this article presents a solution to enhance the access classification accuracy by exploiting the physical layer information. Our method employs a weighted voting scheme for channel state information based authentication using a single sample which includes sample segmentation, grouping, and weighted voting and finally achieves the fast and low complexity secure-access requirement of the EC system without increasing the individual devices' sample size and computational complexity. Experimental results utilizing public datasets and field-measured datasets demonstrate that the proposed weighted voting method has higher accuracy and robustness than existing methods.
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| 9. |
- Zhan, Ming, et al.
(författare)
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Reverse Calculation-Based Low Memory Turbo Decoder for Power Constrained Applications
- 2021
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Ingår i: IEEE Transactions on Circuits and Systems Part 1. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1549-8328 .- 1558-0806. ; 68:6, s. 2688-2701
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Tidskriftsartikel (refereegranskat)abstract
- Turbo codes are a family of near Shannon limit error correction coding schemes that usually are adopted for wireless data transmission. To reduce the power dissipation of a long-term evolution (LTE) advanced turbo decoder, in this paper, we propose a reverse calculation based low memory turbo decoder architecture by partitioning the trellis diagram and simplifying the max* operator. The designed forward state metrics calculation architecture is merged with two classical decoding schemes. Through field programmable gate array (FPGA) hardware implementation, the state metrics cache (SMC) capacity is reduced by 65%, the power dissipation of the reverse calculation architecture is significantly reduced for all tested clock frequencies, and the decoding performance is not affected as compared with classical decoding schemes. The proposed reverse calculation architecture is an effective technique to achieve better decoding performance for power-constrained applications.
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| 10. |
- Zhou, Jinyuan, et al.
(författare)
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Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T : Application to brain tumors
- 2022
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 88:2, s. 546-574
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Tidskriftsartikel (refereegranskat)abstract
- Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.
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