In this paper, we propose a robust and efficient signature scheme for vehicle-to-infrastructure communications, called binary authentication tree (BAT). The BAT scheme can effectively eliminate the ...performance bottleneck when verifying a mass of signatures within a rigorously required interval, even under adverse scenarios with bogus messages. Given any n received messages with k ges 1 bogus ones, the computation cost to verify all these messages only requires approximately (k + 1) ldr log(n/k) + 4k - 2 time-consuming pairing operations. The BAT scheme can also be gracefully transplanted to other similar batch signature schemes. In addition, it offers the other conventional security for vehicular networks, such as identity privacy and traceability. Theoretical analysis and simulation results demonstrate the validity and practicality of the BAT scheme.
•We assessed self-reported adult attachment and reinforcement sensitivity.•Attachment avoidance is related to lowered RST-PQ BAS Reward Reactivity.•Attachment anxiety is unrelated to FFFS ...sensitivity.•Both attachment dimensions are related to greater BIS sensitivity.
This study examined the nature of the relationship between adult attachment and sensitivities of the Behavioural Approach System (BAS), Fight-Flight-Freeze System (FFFS), and the Behavioural Inhibition System (BIS) as defined by Gray and McNaughton’s (2000) revised Reinforcement Sensitivity Theory (r-RST). A total of 225 first year psychology students completed the Experiences in Close Relationships-Revised scale (ECR-R) as an index of adult attachment; along with Carver and White’s (1994) BAS scale (CW-BAS), Fear Survey Schedule (FSS), State-Trait Anxiety Inventory (STAI), and Reinforcement Sensitivity Theory Personality Questionnaire (RST-PQ) as indices of reinforcement sensitivity. Hierarchical multiple regressions revealed that both attachment dimensions are significantly related to BIS sensitivity, which suggests that motivational ambivalence is a central feature of attachment insecurity. This study contributes to the understanding of adult attachment behaviour in relationship to more fundamental motivational systems.
In this paper, a deep learning (DL)-based physical (PHY) layer authentication framework is proposed to enhance the security of industrial wireless sensor networks (IWSNs). Three algorithms, the deep ...neural network (DNN)-based sensor nodes' authentication method, the convolutional neural network (CNN)-based sensor nodes' authentication method, and the convolution preprocessing neural network (CPNN)-based sensor nodes' authentication method, have been adopted to implement the PHY-layer authentication in IWSNs. Among them, the improved CPNN-based algorithm requires few computing resources and has extremely low latency, which enable a lightweight multi-node PHY-layer authentication. The adaptive moment estimation (Adam) accelerated gradient algorithm and minibatch skill are used to accelerate the training of the neural networks. Simulations are performed to evaluate the performance of each algorithm and a brief analysis of the application scenarios for each algorithm is discussed. Moreover, the experiments have been performed with universal software radio peripherals (USRPs) to evaluate the authentication performance of the proposed algorithms. Due to the trainings being performed on the edge sides, the proposed method can implement a lightweight authentication for the sensor nodes under the edge computing (EC) system in IWSNs.
In this paper, an edge computing system for IoT-based (Internet of Things) smart grids is proposed to overcome the drawbacks in the current cloud computing paradigm in power systems, where many ...problems have yet to be addressed such as fully realizing the requirements of high bandwidth with low latency. The new system mainly introduces edge computing in the traditional cloud-based power system and establishes a new hardware and software architecture. Therefore, a considerable amount of data generated in the electrical grid will be analyzed, processed, and stored at the edge of the network. Aided with edge computing paradigm, the IoT-based smart grids will realize the connection and management of substantial terminals, provide the real-time analysis and processing of massive data, and foster the digitalization of smart grids. In addition, we propose a privacy protection strategy via edge computing, data prediction strategy, and preprocessing strategy of hierarchical decision-making based on task grading (HDTG) for the IoT-based smart girds. The effectiveness of our proposed approaches has been demonstrated via the numerical simulations.
In this paper, a light-weight radio frequency fingerprinting identification (RFFID) scheme that combines with a two-layer model is proposed to realize authentications for a large number of ...resource-constrained terminals under the mobile edge computing (MEC) scenario without relying on encryption-based methods. In the first layer, signal collection, extraction of RF fingerprint features, dynamic feature database storage, and access authentication decision are carried out by the MEC devices. In the second layer, learning features, generating decision models, and implementing machine learning algorithms for recognition are performed by the remote cloud. By this means, the authentication rate can be improved by taking advantage of the machine-learning training methods and computing resource support of the cloud. Extensive simulations are performed under the IoT application scenario. The results show that the novel method can achieve higher recognition rate than that of traditional RFFID method by using wavelet feature effectively, which demonstrates the efficiency of our proposed method.
PLA is a potential fully biodegradable material, but its poor toughness and heat resistance seriously limit its wide application. In this work, a strong and tough balanced PLA based PLA/PBAT material ...with good heat resistance was successfully prepared using a self-designed vibration injection molding (VIM) device. From the results of SEM, SAXS, and WAXD, the internal structure of samples changed apparently compared with conventional injection molded ones. The distribution of the orientated region was controlled by changing the vibration parameters. The combination of hierarchical structure and the introduction of elastomer provide the sample with improved toughness without the sacrifice of strength. The maximum impact strength of samples can reach 20.24 kJ/m
2
. Besides, the thermal resistance also improves. The Vicat softening temperature can reach 71.1 ℃. This work proves the superiority of hierarchical structure for PLA/PBAT samples and provides a new method to broaden the application range of PLA materials.
RNA research and applications are underpinned by
in vitro
transcription (IVT), but RNA impurities resulting from the enzymatic reagents severely impede downstream applications. To improve the ...stability and purity of synthesized RNA, we have characterized a novel single-subunit RNA polymerase (RNAP) encoded by the psychrophilic phage VSW-3 from a plateau lake. The VSW-3 RNAP is capable of carrying out
in vitro
RNA synthesis at low temperatures (4–25°C). Compared to routinely used T7 RNAP, VSW-3 RNAP provides a similar yield of transcripts but is insensitive to class II transcription terminators and synthesizes RNA without redundant 3’-cis extensions. More importantly, through dot-blot detection with the J2 monoclonal antibody, we found that the RNA products synthesized by VSW-3 RNAP contained a much lower amount of double-stranded RNA byproducts (dsRNA), which are produced by transcription from both directions and are significant in T7 RNAP IVT products. Taken together, the VSW-3 RNAP almost eliminates both terminal loop-back dsRNA and full-length dsRNA in IVT and thus is especially advantageous for producing RNA for
in vivo
use.
Data poisoning attack is a well-known attack against machine learning models, where malicious attackers contaminate the training data to manipulate critical models and predictive outcomes by ...masquerading as terminal devices. As this type of attack can be fatal to the operation of a smart grid, addressing data poisoning is of utmost importance. However, this attack requires solving an expensive two-level optimization problem, which can be challenging to implement in resource-constrained edge environments of the smart grid. To mitigate this issue, it is crucial to enhance efficiency and reduce the costs of the attack. This paper proposes an online data poisoning attack framework based on the online regression task model. The framework achieves the goal of manipulating the model by polluting the sample data stream that arrives at the cache incrementally. Furthermore, a point selection strategy based on sample loss is proposed in this framework. Compared to the traditional random point selection strategy, this strategy makes the attack more targeted, thereby enhancing the attack's efficiency. Additionally, a batch-polluting strategy is proposed in this paper, which synchronously updates the poisoning points based on the direction of gradient ascent. This strategy reduces the number of iterations required for inner optimization and thus reduces the time overhead. Finally, multiple experiments are conducted to compare the proposed method with the baseline method, and the evaluation index of loss over time is proposed to demonstrate the effectiveness of the method. The results show that the proposed method outperforms the existing baseline method in both attack effectiveness and overhead.
As a widely used steroid hormone medicine, glucocorticoids have the potential to cause steroid-induced osteonecrosis of the femoral head (SONFH) due to mass or long-term use. The non-coding RNA ...hypothesis posits that they may contribute to the destruction and dysfunction of cartilages as a possible etiology of SONFH. MiR-30b-5p was identified as a regulatory factor in cartilage degeneration caused by methylprednisolone (MPS) exposure in our study through cell transfection. The luciferase reporter assay confirmed that miR-30b-5p was downregulated and runt-related transcription factor 2 (Runx2) was mediated by miR-30b-5p. The nobly increased expression of matrix metallopeptidase 13 (MMP13) and type X collagen (Col10a1) as Runx2 downstream genes contributed to the hypertrophic differentiation of chondrocytes, and the efficiently upregulated level of matrix metallopeptidase 9 (MMP9) may trigger chondrocyte apoptosis with MPS treatments. The cell transfection experiment revealed that miR-30b-5p inhibited chondrocyte hypertrophy and suppressed MPS-induced apoptosis. As a result, our findings showed that miR-30b-5p modulated Runx2, MMP9, MMP13, and Col10a1 expression, thereby mediating chondrocyte hypertrophic differentiation and apoptosis during the SONFH process. These findings revealed the mechanistic relationship between non-coding RNA and SONFH, providing a comprehensive understanding of SONFH and other bone diseases.
In this paper, we propose an efficient distributed-certificate-service (DCS) scheme for vehicular networks. The proposed scheme offers flexible interoperability for certificate service in ...heterogeneous administrative authorities and an efficient way for any onboard units (OBUs) to update its certificate from the available infrastructure roadside units (RSUs) in a timely manner. In addition, the DCS scheme introduces an aggregate batch-verification technique for authenticating certificate-based signatures, which significantly decreases the verification overhead. Security analysis and performance evaluation demonstrate that the DCS scheme can reduce the complexity of certificate management and achieve excellent security and efficiency for vehicular communications.
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