基于TrustZone硬件隔离技术的CLKScrew攻击防护研究

随着信息技术的迅猛发展,嵌入式系统中的安全性问题日益受到关注。本文针对嵌入式平台中动态电压频率调整技术存在的安全漏洞,基于高级精简指令集机器的TrustZone硬件隔离技术设计并实现了一种可信执行环境(TEE),利用TrustZone技术实现了TEE与普通执行环境操作系统间的切换。该环境能够有效抵御CLKScrew攻击,即通过多次调整中央处理器(CPU)线程工作频率来触发嵌入式平台的运行错误。实验结果表明,在该可信执行环境中,即使面临CLK⁃Screw攻击,CPU线程仍能正常工作,确保了系统的安全性。

An Enhanced Trust-Based Secure Route Protocol for Malicious Node Detection

The protection of ad-hoc networks is becoming a severe concern because of the absence of a central authority.The intensity of the harm largely depends on the attacker’s intentions during hostile assaults.As a result,the loss of Information,power,or capacity may occur.The authors propose an Enhanced Trust-Based Secure Route Protocol(ETBSRP)using features extraction.First,the primary and secondary trust characteristics are retrieved and achieved routing using a calculation.The complete trust characteristic obtains by integrating all logical and physical trust from every node.To assure intermediate node trust-worthiness,we designed an ETBSRP,and it calculates and certifies each mobile node's reputation and sends packets based on that trust.Connection,honesty,power,and capacity are the four trust characteristics used to calculate node repu-tation.We categorize Nodes as trustworthy or untrustworthy according to their reputation values.Fool nodes are detached from the routing pathway and cannot communicate.Then,we use the cryptographic functions to ensure more secure data transmission.Finally,we eliminate the untrustworthy nodes from the routing process,and the datagram from the origin are securely sent to the target,increas-ing throughput by 93.4%and minimizing delay.

Controllable optical bistability in a Fabry-Pérot cavity with a nonlinear three-dimensional Dirac semimetal

Optical bistability(OB)is capable of rapidly and reversibly transforming a parameter of an optical signal from one state to another,and homologous nonlinear optical bistable devices are core components of high-speed all-optical communication and all-optical networks.In this paper,we theoretically investigated the controllable OB from a Fabry-Pérot(FP)cavity with a nonlinear three-dimensional Dirac semimetal(3D DSM)in the terahertz band.The OB stems from the third-order nonlinear bulk conductivity of the 3D DSM and the resonance mode has a positive effect on the generation of OB.This FP cavity structure is able to tune the OB because the transmittance and the reflectance can be modulated by the Fermi energy of the 3D DSM.We believe that this FP cavity configuration could provide a reference concept for realizing tunable bistable devices.

CRBFT:A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

Blockchain has been widely used in finance,the Internet of Things(IoT),supply chains,and other scenarios as a revolutionary technology.Consensus protocol plays a vital role in blockchain,which helps all participants to maintain the storage state consistently.However,with the improvement of network environment complexity and system scale,blockchain development is limited by the performance,security,and scalability of the consensus protocol.To address this problem,this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance(PBFT)and proposes a Byzantine fault-tolerant(BFT)consensus protocol based on collaborative filtering recommendation(CRBFT).Specifically,an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation opinions.This can amplify the recommendation voice of good nodes,weaken the impact of cunningmalicious nodes on the trust value calculation,andmake the calculated resultsmore accurate.In addition,the nodes are given voting power according to their trust value,and a weight randomelection algorithm is designed and implemented to reduce the risk of attack.The experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments,and the feasibility of CRBFT is also proven by theoretical analysis.

Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent integration.The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and processing.However,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion terminals.Simultaneously,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart grid.In response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these issues.The scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT terminals.It then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy states.This comprehensive approach reduces the impact of subjective factors on trust measurements.Additionally,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious terminals.This,in turn,enhances the security and reliability of the smart grid environment.The effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation experiments.Notably,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

A novel pathogen Fusarium cuneirostrum causing common bean(Phaseolus vulgaris)root rot in China

Several fungal pathogens cause root rot of common bean,among which Fusarium spp.are the most common pathogens causing Fusarium root rot(FRR)worldwide.FRR has been becoming an increasingly severe disease of common bean in China,but the species of Fusarium spp.have remained unclear.Thus,this study was performed to identify the pathogen causing common bean root rot in Liangcheng County,Inner Mongolia,China.Nineteen Fusarium-like isolates were obtained after pathogen isolation and purification.The pathogenicity test indicated that eight isolates caused severe disease symptoms on common bean,while 11 other isolates were not pathogenic.The eight pathogenic isolates,FCL1–FCL8,were identified as Fusarium cuneirostrum by morphological characterization and phylogenetic analysis using partial sequences of EF-1α,ITS,28S,and IGS regions.Host range test showed that the representative F.cuneirostrum isolate FCL3 was also pathogenic to mung bean,while not pathogenic to adzuki bean,chickpea,cowpea,faba bean,pea,and soybean.Moreover,50 common bean and 50 mung bean cultivars were screened for resistance to FRR,and seven highly resistant or resistant cultivars of common bean were identified,while no resistant cultivars of mung bean were screened.This study revealed that F.cuneirostrum was one of common bean FRR pathogens in Inner Mongolia and it could induce mung bean root rot as well.To our knowledge,this is the first report of F.cuneirostrum causing FRR of common bean in China.

A Fuzzy Trust Management Mechanism with Dynamic Behavior Monitoring for Wireless Sensor Networks

Traditional wireless sensor networks(WSNs)are typically deployed in remote and hostile environments for information collection.The wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various attacks.Traditional encryption and authentication mechanisms cannot prevent attacks launched by internal malicious nodes.The trust-based security mechanism is usually adopted to solve this problem in WSNs.However,the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor nodes.Moreover,how to efficiently collect behavioral evidences are rarely discussed.To address these issues,in this paper,we present a trust management mechanism based on fuzzy logic and a cloud model.First,a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate uncertainty.Then,the cloud model is introduced to estimate the trust values for sensor nodes.Finally,a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety assurance.Simulation results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.

Trust Score-Based Malicious Vehicle Detection Scheme in Vehicular Network Environments

Advancements in the vehicular network technology enable real-time interconnection,data sharing,and intelligent cooperative driving among vehicles.However,malicious vehicles providing illegal and incorrect information can compromise the interests of vehicle users.Trust mechanisms serve as an effective solution to this issue.In recent years,many researchers have incorporated blockchain technology to manage and incentivize vehicle nodes,incurring significant overhead and storage requirements due to the frequent ingress and egress of vehicles within the area.In this paper,we propose a distributed vehicular network scheme based on trust scores.Specifically,the designed architecture partitions multiple vehicle regions into clusters.Then,cloud supervision systems(CSSs)verify the accuracy of the information transmitted by vehicles.Additionally,the trust scores for vehicles are calculated to reward or penalize them based on the trust evaluation model.Our proposed scheme demonstrates good scalability and effectively addresses the main cause of malicious information distribution among vehicles.Both theoretical and experimental analysis show that our scheme outperforms the compared schemes.

A Trust Evaluation Mechanism Based on Autoencoder Clustering Algorithm for Edge Device Access of IoT

First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.

Machine learning and human‐machine trust in healthcare:A systematic survey

As human‐machine interaction(HMI)in healthcare continues to evolve,the issue of trust in HMI in healthcare has been raised and explored.It is critical for the development and safety of healthcare that humans have proper trust in medical machines.Intelligent machines that have applied machine learning(ML)technologies continue to penetrate deeper into the medical environment,which also places higher demands on intelligent healthcare.In order to make machines play a role in HMI in healthcare more effectively and make human‐machine cooperation more harmonious,the authors need to build good humanmachine trust(HMT)in healthcare.This article provides a systematic overview of the prominent research on ML and HMT in healthcare.In addition,this study explores and analyses ML and three important factors that influence HMT in healthcare,and then proposes a HMT model in healthcare.Finally,general trends are summarised and issues to consider addressing in future research on HMT in healthcare are identified.

Enhancing the Trustworthiness of 6G Based on Trusted Multi-Cloud Infrastructure:A Practice of Cryptography Approach

Due to the need for massive device connectivity,low communication latency,and various customizations in 6G architecture,a distributed cloud deployment approach will be more relevant to the space-air-ground-sea integrated network scenario.However,the openness and heterogeneity of the 6G network cause the problems of network security.To improve the trustworthiness of 6G networks,we propose a trusted computing-based approach for establishing trust relationships inmulti-cloud scenarios.The proposed method shows the relationship of trust based on dual-level verification.It separates the trustworthy states of multiple complex cloud units in 6G architecture into the state within and between cloud units.Firstly,SM3 algorithm establishes the chain of trust for the system’s trusted boot phase.Then,the remote attestation server(RAS)of distributed cloud units verifies the physical servers.Meanwhile,the physical servers use a ring approach to verify the cloud servers.Eventually,the centralized RAS takes one-time authentication to the critical evidence information of distributed cloud unit servers.Simultaneously,the centralized RAS also verifies the evidence of distributed RAS.We establish our proposed approach in a natural OpenStack-based cloud environment.The simulation results show that the proposed method achieves higher security with less than a 1%system performance loss.

Genome-wide association mapping and genomic prediction of stalk rot in two mid-altitude tropical maize populations

Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Effective transmittance of Fabry–Perot cavity under non-parallel beam incidence

The Fabry–Perot(FP) resonant cavity is widely used in laser and spectroscopic measurements due to its unique interference transfer function(ITF). In the ideal case of parallel incident light, the ITF of the FP resonant cavity can be expressed by the Airy function. However, in reality, it is difficult to achieve perfect parallelism with collimated beams. In this article, a theoretical model is established for non-parallel light incidence, which assumes that the non-parallel incident light is a cone-shaped beam, and the cone angle is used to quantify the non-parallelism of the beam. The transmittance function of the FP resonant cavity under non-parallel light incidence is derived. The accuracy of the model is experimentally verified. Based on this model, the effects of divergence angle, tilt angle and FP cavity parameters(reflectivity, cavity length)on the ITF are studied. The reasons for the decrease in peak value, broadening and asymmetry of the interference peak under non-parallel light incidence are explained. It is suggested that a fine balance between the interference peak and the collimation effect of the incident light should be considered in the design and application of FP resonant cavities, especially for tilted applications such as angle-scanned spectroscopy. The research results of this article have certain significance for the design and application of FP resonant cavities.

Trusted Certified Auditor Using Cryptography for Secure Data Outsourcing and Privacy Preservation in Fog-Enabled VANETs

With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.

Research on Data Tampering Prevention Method for ATC Network Based on Zero Trust

The traditional air traffic control information sharing data has weak security characteristics of personal privacy data and poor effect,which is easy to leads to the problem that the data is usurped.Starting from the application of the ATC(automatic train control)network,this paper focuses on the zero trust and zero trust access strategy and the tamper-proof method of information-sharing network data.Through the improvement of ATC’s zero trust physical layer authentication and network data distributed feature differentiation calculation,this paper reconstructs the personal privacy scope authentication structure and designs a tamper-proof method of ATC’s information sharing on the Internet.From the single management authority to the unified management of data units,the systematic algorithm improvement of shared network data tamper prevention method is realized,and RDTP(Reliable Data Transfer Protocol)is selected in the network data of information sharing resources to realize the effectiveness of tamper prevention of air traffic control data during transmission.The results show that this method can reasonably avoid the tampering of information sharing on the Internet,maintain the security factors of air traffic control information sharing on the Internet,and the Central Processing Unit(CPU)utilization rate is only 4.64%,which effectively increases the performance of air traffic control data comprehensive security protection system.

Damage and Control Suggestions for the Emerging Disease Coffee Root Rot

[Objectives]The paper was to elucidate the symptoms,morphological characteristics,etiological factors,and current extent of damage associated with coffee root rot disease.[Methods]The symptoms,morphological characteristics,and etiological factors associated with coffee root rot disease were systematically observed,described,and analyzed.The assessment of damage was carried out using a specialized investigative methodology.[Results]The application of bottom fertilizer containing Fusarium incarnatum facilitated the pathogen's entry through root wounds during transplantation,resulting in the development of water-soaked depression lesions in the affected areas.This infection significantly reduced the number of lateral roots in coffee plants,leading to symptoms such as wilting,withering,and ultimately,the death of the aboveground foliage.F.incarnatum exhibited three distinct types of spore morphology:macroconidia,which were sickle-shaped;mesoconidia,which were spindle-shaped;and microconidia,which were oval-shaped.The incidence rate of the disease in the affected region reached 100%,with a disease index exceeding 91,indicating severe damage.[Conclusions]This study serves as a valuable reference for the prevention and management of the emerging disease known as coffee root rot.

New Rotative Radiofrequency Technology: A Multicenter Retrospective Study on Efficacy and Safety

Background: Non-ablative radiofrequency (RF) technology is widely used for the treatment of signs of aging, skin laxity, localized fat and cellulite. However, many RF devices suffer from technical limitations that make the results highly dependent on the user’s experience or clinical limitations that compromise safety, efficacy and comfort. Objective: To evaluate the efficacy and safety of a novel semi-automatic non-ablative RF device for skin tightening, body shaping and cellulite reduction. Materials and methods: A retrospective multicenter study was performed using a novel rotative RF device with temperature and impedance control (Sculpt&Shape®, Sinclair, Spain). 58 subjects underwent a minimum of 4 treatments every 1-2 weeks. A total of 120 treatments (56.7% body and 43.3% facial) and 1034 sessions were performed. Efficacy was evaluated by 3 researchers using the Global Aesthetic Improvement Scale (GAIS) and anthropometric measurements were collected. Subject and practitioner satisfaction were recorded. Safety was evaluated by analyzing the perception of pain during the treatment and the side and adverse effects immediately after treatment and over the next 48 hours. Results: Between 25% and 50% improvement was achieved according to the GAIS. Statistically significant (p < 0.01) abdominal fold reduction of 5.1 mm and circumference reduction of 32.0 mm, 16.4 mm and 13.9 mm were recorded for the abdomen, legs and arms, respectively. 77.5% of subjects and 94.9% of practitioners were either satisfied or very satisfied. Minor adverse effects were found in 0.97% of the sessions. Conclusion: This novel semi-automatic rotative RF device has been found to provide treatments that are effective, safe and comfortable for both practitioners and subjects. .

Influence of Microorganisms Effective against Basal Rot and on Agronomic Parameters of Onion [Allium cepa L. (Amaryllidaceae)]

Onions are a horticultural crop of great economic, dietary and medicinal importance, and are highly prized by the Ivorian population. However, production remains low, due to a number of constraints, including parasitic attacks. The most frequent is fusariosis caused by Fusarium sp., a pathogen that causes enormous damage to onion crops. Faced with these attacks, chemical control appears to be ineffective, with consequences for human health and the environment. This is why the search for effective alternative methods that respect the environment and human health is so necessary. It is in this context that this study was carried out, with the general aim of controlling fusarium wilt in onion crops, with a view to improving onion production in Ivory Coast through the use of effective microorganisms. The experimental set-up used for this purpose was a fisher block with complete randomization, comprising three replicates. A fungal spore concentration of 106 spore/mL of Fusarium sp., three doses (1%;2.5% and 5% v/v) of EM and one dose of a chemical fungicide (30 mL/16L) were tested on young onion plants. Each block consisted of nine sub-plots with nine treatments. Health parameters (incidence and severity) and agronomic parameters (growth and yield) were assessed. Microbiological analysis of the EM revealed the presence of nine morphotypes of Trichoderma sp., Aspergillus clavatus, Aspergillus flavus, Aspergillus sp., Penicillium sp., Rhizopus sp., lactic acid bacteria of the Bacillus family and the yeast Saccharomyces cerevisiae. Field experimentation showed that the 5% EM microbial solution reduced the incidence and severity of fusariosis compared with the chemical fungicide, and proved to be the best. This dose reduced yield losses by 7.14%, while improving onion growth and yield by over 5%. The results demonstrated the ability of the EM solution to effectively control the causal agent of basal rot in onion crops.

From Standard Policy-Based Zero Trust to Absolute Zero Trust (AZT): A Quantum Leap to Q-Day Security

Cybercrime is projected to cost a whopping $23.8 Trillion by 2027. This is essentially because there’s no computer network that’s not vulnerable. Fool-proof cybersecurity of personal data in a connected computer is considered practically impossible. The advent of quantum computers (QC) will worsen cybersecurity. QC will be a boon for data-intensive industries by drastically reducing the computing time from years to minutes. But QC will render our current cryptography vulnerable to quantum attacks, breaking nearly all modern cryptographic systems. Before QCs with sufficient qubits arrive, we must be ready with quantum-safe strategies to protect our ICT infrastructures. Post-quantum cryptography (PQC) is being aggressively pursued worldwide as a defence from the potential Q-day threat. NIST (National Institute of Standards and Technology), in a rigorous process, tested 82 PQC schemes, 80 of which failed after the final round in 2022. Recently the remaining two PQCs were also cracked by a Swedish and a French team of cryptographers, placing NIST’s PQC standardization process in serious jeopardy. With all the NIST-evaluated PQCs failing, there’s an urgent need to explore alternate strategies. Although cybersecurity heavily relies on cryptography, recent evidence indicates that it can indeed transcend beyond encryption using Zero Vulnerability Computing (ZVC) technology. ZVC is an encryption-agnostic absolute zero trust (AZT) approach that can potentially render computers quantum resistant by banning all third-party permissions, a root cause of most vulnerabilities. Unachievable in legacy systems, AZT is pursued by an experienced consortium of European partners to build compact, solid-state devices that are robust, resilient, energy-efficient, and with zero attack surface, rendering them resistant to malware and future Q-Day threats.