Repositioning fertilizer manufacturing subsidies for improving food security and reducing greenhouse gas emissions in China

China removed fertilizer manufacturing subsidies from 2015 to 2018 to bolster market-oriented reforms and foster environmentally sustainable practices.However,the impact of this policy reform on food security and the environment remains inadequately evaluated.Moreover,although green and low-carbon technologies offer environmental advantages,their widespread adoption is hindered by prohibitively high costs.This study analyzes the impact of removing fertilizer manufacturing subsidies and explores the potential feasibility of redirecting fertilizer manufacturing subsidies to invest in the diffusion of these technologies.Utilizing the China Agricultural University Agri-food Systems model,we analyzed the potential for achieving mutually beneficial outcomes regarding food security and environmental sustainability.The findings indicate that removing fertilizer manufacturing subsidies has reduced greenhouse gas(GHG)emissions from agricultural activities by 3.88 million metric tons,with minimal impact on food production.Redirecting fertilizer manufacturing subsidies to invest in green and low-carbon technologies,including slow and controlled-release fertilizer,organic-inorganic compound fertilizers,and machine deep placement of fertilizer,emerges as a strategy to concurrently curtail GHG emissions,ensure food security,and secure robust economic returns.Finally,we propose a comprehensive set of government interventions,including subsidies,field guidance,and improved extension systems,to promote the widespread adoption of these technologies.

Security Implications of Edge Computing in Cloud Networks

Security issues in cloud networks and edge computing have become very common. This research focuses on analyzing such issues and developing the best solutions. A detailed literature review has been conducted in this regard. The findings have shown that many challenges are linked to edge computing, such as privacy concerns, security breaches, high costs, low efficiency, etc. Therefore, there is a need to implement proper security measures to overcome these issues. Using emerging trends, like machine learning, encryption, artificial intelligence, real-time monitoring, etc., can help mitigate security issues. They can also develop a secure and safe future in cloud computing. It was concluded that the security implications of edge computing can easily be covered with the help of new technologies and techniques.

An Investigation on Open-RAN Specifications:Use Cases,Security Threats,Requirements,Discussions

The emergence of various technologies such as terahertz communications,Reconfigurable Intelligent Surfaces(RIS),and AI-powered communication services will burden network operators with rising infrastructure costs.Recently,the Open Radio Access Network(O-RAN)has been introduced as a solution for growing financial and operational burdens in Beyond 5G(B5G)and 6G networks.O-RAN promotes openness and intelligence to overcome the limitations of traditional RANs.By disaggregating conventional Base Band Units(BBUs)into O-RAN Distributed Units(O-DU)and O-RAN Centralized Units(O-CU),O-RAN offers greater flexibility for upgrades and network automation.However,this openness introduces new security challenges compared to traditional RANs.Many existing studies overlook these security requirements of the O-RAN networks.To gain deeper insights into the O-RAN system and security,this paper first provides an overview of the general O-RAN architecture and its diverse use cases relevant to B5G and 6G applications.We then delve into specifications of O-RAN security threats and requirements,aiming to mitigate security vulnerabilities effectively.By providing a comprehensive understanding of O-RAN architecture,use cases,and security considerations,thisworkserves as a valuable resource for future research in O-RAN and its security.

Survey on Video Security:Examining Threats,Challenges,and Future Trends

Videos represent the most prevailing form of digital media for communication,information dissemination,and monitoring.However,theirwidespread use has increased the risks of unauthorised access andmanipulation,posing significant challenges.In response,various protection approaches have been developed to secure,authenticate,and ensure the integrity of digital videos.This study provides a comprehensive survey of the challenges associated with maintaining the confidentiality,integrity,and availability of video content,and examining how it can be manipulated.It then investigates current developments in the field of video security by exploring two critical research questions.First,it examine the techniques used by adversaries to compromise video data and evaluate their impact.Understanding these attack methodologies is crucial for developing effective defense mechanisms.Second,it explores the various security approaches that can be employed to protect video data,enhancing its transparency,integrity,and trustworthiness.It compares the effectiveness of these approaches across different use cases,including surveillance,video on demand(VoD),and medical videos related to disease diagnostics.Finally,it identifies potential research opportunities to enhance video data protection in response to the evolving threat landscape.Through this investigation,this study aims to contribute to the ongoing efforts in securing video data,providing insights that are vital for researchers,practitioners,and policymakers dedicated to enhancing the safety and reliability of video content in our digital world.

Enhancing Cybersecurity Competency in the Kingdom of Saudi Arabia:A Fuzzy Decision-Making Approach

The Kingdom of Saudi Arabia(KSA)has achieved significant milestones in cybersecurity.KSA has maintained solid regulatorymechanisms to prevent,trace,and punish offenders to protect the interests of both individual users and organizations from the online threats of data poaching and pilferage.The widespread usage of Information Technology(IT)and IT Enable Services(ITES)reinforces securitymeasures.The constantly evolving cyber threats are a topic that is generating a lot of discussion.In this league,the present article enlists a broad perspective on how cybercrime is developing in KSA at present and also takes a look at some of the most significant attacks that have taken place in the region.The existing legislative framework and measures in the KSA are geared toward deterring criminal activity online.Different competency models have been devised to address the necessary cybercrime competencies in this context.The research specialists in this domain can benefit more by developing a master competency level for achieving optimum security.To address this research query,the present assessment uses the Fuzzy Decision-Making Trial and Evaluation Laboratory(Fuzzy-DMTAEL),Fuzzy Analytic Hierarchy Process(F.AHP),and Fuzzy TOPSIS methodology to achieve segment-wise competency development in cyber security policy.The similarities and differences between the three methods are also discussed.This cybersecurity analysis determined that the National Cyber Security Centre got the highest priority.The study concludes by perusing the challenges that still need to be examined and resolved in effectuating more credible and efficacious online security mechanisms to offer amoreempowered ITES-driven economy for SaudiArabia.Moreover,cybersecurity specialists and policymakers need to collate their efforts to protect the country’s digital assets in the era of overt and covert cyber warfare.

Soybean maize strip intercropping:A solution for maintaining food security in China

The practice of intercropping leguminous and gramineous crops is used for promoting sustainable agriculture,optimizing resource utilization,enhancing biodiversity,and reducing reliance on petroleum products.However,promoting conventional intercropping strategies in modern agriculture can prove challenging.The innovative technology of soybean maize strip intercropping(SMSI)has been proposed as a solution.This system has produced remarkable results in improving domestic soybean and maize production for both food security and sustainable agriculture.In this article,we provide an overview of SMSI and explain how it differs from traditional intercropping.We also discuss the core principles that foster higher yields and the prospects for its future development.

Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

Food security amid the COVID-19 pandemic in Central Asia:Evidence from rural Tajikistan

Food security has been long understudied in the context of Central Asia.We present an analysis examining household-level food demand for Tajikistan and assessing the magnitude of its food security changes during the COVID-19 pandemic.Based on an extensive household survey data set from Tajikistan,we estimate the expenditure,income,and price elasticities for nine food categories using the QUAIDS model.Then,we develop a microsimulation model using the estimated elasticities to assess the dual impact of declining remittance income and rising food prices stemming from the pandemic shock.There are significant differences in demand elasticities across food groups,with high elasticities observed for nutritious foods,such as meat,fruit,eggs,and milk,in rural households.Moreover,our findings show that changes in remittance income and food prices significantly negatively affected food security for rural households during the COVID-19 pandemic.These findings have important implications for policymakers concerned about rural livelihoods and food security in remittance-receiving economies during the post-pandemic period.

Security Analysis in Smart Agriculture: Insights from a Cyber-Physical System Application

Smart agriculture modifies traditional farming practices,and offers innovative approaches to boost production and sustainability by leveraging contemporary technologies.In today’s world where technology is everything,these technologies are utilized to streamline regular tasks and procedures in agriculture,one of the largest and most significant industries in every nation.This research paper stands out from existing literature on smart agriculture security by providing a comprehensive analysis and examination of security issues within smart agriculture systems.Divided into three main sections-security analysis,system architecture and design and risk assessment of Cyber-Physical Systems(CPS)applications-the study delves into various elements crucial for smart farming,such as data sources,infrastructure components,communication protocols,and the roles of different stakeholders such as farmers,agricultural scientists and researchers,technology providers,government agencies,consumers and many others.In contrast to earlier research,this work analyzes the resilience of smart agriculture systems using approaches such as threat modeling,penetration testing,and vulnerability assessments.Important discoveries highlight the concerns connected to unsecured communication protocols,possible threats from malevolent actors,and vulnerabilities in IoT devices.Furthermore,the study suggests enhancements for CPS applications,such as strong access controls,intrusion detection systems,and encryption protocols.In addition,risk assessment techniques are applied to prioritize mitigation tactics and detect potential hazards,addressing issues like data breaches,system outages,and automated farming process sabotage.The research sets itself apart even more by presenting a prototype CPS application that makes use of a digital temperature sensor.This application was first created using a Tinkercad simulator and then using actual hardware with Arduino boards.The CPS application’s defenses against potential threats and vulnerabilities are strengthened by this integrated approach,which distinguishes this research for its depth and usefulness in the field of smart agriculture security.

Research progress and future prospects in the service security of key blast furnace equipment

The safety and longevity of key blast furnace(BF)equipment determine the stable and low-carbon production of iron.This pa-per presents an analysis of the heat transfer characteristics of these components and the uneven distribution of cooling water in parallel pipes based on hydrodynamic principles,discusses the feasible methods for the improvement of BF cooling intensity,and reviews the pre-paration process,performance,and damage characteristics of three key equipment pieces:coolers,tuyeres,and hearth refractories.Fur-thermoere,to attain better control of these critical components under high-temperature working conditions,we propose the application of optimized technologies,such as BF operation and maintenance technology,self-repair technology,and full-lifecycle management techno-logy.Finally,we propose further researches on safety assessments and predictions for key BF equipment under new operating conditions.

MV-Honeypot:Security Threat Analysis by Deploying Avatar as a Honeypot in COTS Metaverse Platforms

Nowadays,theuse of Avatars that are unique digital depictions has increased by users to access Metaverse—a virtual reality environment—through multiple devices and for various purposes.Therefore,the Avatar and Metaverse are being developed with a new theory,application,and design,necessitating the association of more personal data and devices of targeted users every day.This Avatar and Metaverse technology explosion raises privacy and security concerns,leading to cyber attacks.MV-Honeypot,or Metaverse-Honeypot,as a commercial off-the-shelf solution that can counter these cyber attack-causing vulnerabilities,should be developed.To fill this gap,we study user’s engagements with Avatars in Metaverse,analyze possible security vulnerabilities,and create a model named Simplified Avatar Relationship Association with Non-linear Gradient(SARANG)that draws the full diagram of infrastructure components and data flow through accessing Metaverse in this paper.We also determine the most significant threat for each component’s cyberattacks that will affect user data and Avatars.As a result,the commercial off-the-shelf(COTS)of the MV-Honeypot must be established.

A Review on the Security of the Ethereum-Based DeFi Ecosystem

Decentralized finance(DeFi)is a general term for a series of financial products and services.It is based on blockchain technology and has attracted people’s attention because of its open,transparent,and intermediary free.Among them,the DeFi ecosystem based on Ethereum-based blockchains attracts the most attention.However,the current decentralized financial system built on the Ethereum architecture has been exposed to many smart contract vulnerabilities during the last few years.Herein,we believe it is time to improve the understanding of the prevailing Ethereum-based DeFi ecosystem security issues.To that end,we investigate the Ethereum-based DeFi security issues:1)inherited from the real-world financial system,which can be solved by macro-control;2)induced by the problems of blockchain architecture,which require a better blockchain platform;3)caused by DeFi invented applications,which should be focused on during the project development.Based on that,we further discuss the current solutions and potential directions ofDeFi security.According to our research,we could provide a comprehensive vision to the research community for the improvement of Ethereum-basedDeFi ecosystem security.

A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security

In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is paramount.As cyber threats evolve in complexity,traditional cryptographic methods face increasingly sophisticated challenges.This article initiates an exploration into these challenges,focusing on key exchanges(encompassing their variety and subtleties),scalability,and the time metrics associated with various cryptographic processes.We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering.Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity,foundational pillars of information security.Our method employs a phased strategy,beginning with a detailed examination of traditional cryptographic processes,including Elliptic Curve Diffie-Hellman(ECDH)key exchanges.We also delve into encrypt/decrypt paradigms,signature generation modes,and the hashes used for Message Authentication Codes(MACs).Each process is rigorously evaluated for performance and reliability.To gain a comprehensive understanding,a meticulously designed simulation was conducted,revealing the strengths and potential improvement areas of various techniques.Notably,our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs,marking a significant advancement over existing methods.Furthermore,with integrity metrics at 9.35,the protocol’s resilience is further affirmed.These metrics,derived from stringent testing,underscore the protocol’s efficacy in enhancing data security.

Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world software.The existing analysis of software security vulnerabilities often focuses on specific features or modules.This partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the software.The key novelty lies in overcoming the constraints of partial approaches.The proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security guidelines.Security guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each product.These guidelines are not only practical but also applicable in real-world software,allowing for prioritized security responses.The proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related software.The analysis resulted in the identification of a total of 121 vulnerabilities.The successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.

Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful activity.The DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS research.The model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation accuracy.Thus,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in validation.Furthermore,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 scores.The macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are 0.942.Furthermore,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies precisely.The research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network security.The study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this field.Upcoming research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

A Review on Security and Privacy Issues Pertaining to Cyber-Physical Systems in the Industry 5.0 Era

The advent of Industry 5.0 marks a transformative era where Cyber-Physical Systems(CPSs)seamlessly integrate physical processes with advanced digital technologies.However,as industries become increasingly interconnected and reliant on smart digital technologies,the intersection of physical and cyber domains introduces novel security considerations,endangering the entire industrial ecosystem.The transition towards a more cooperative setting,including humans and machines in Industry 5.0,together with the growing intricacy and interconnection of CPSs,presents distinct and diverse security and privacy challenges.In this regard,this study provides a comprehensive review of security and privacy concerns pertaining to CPSs in the context of Industry 5.0.The review commences by providing an outline of the role of CPSs in Industry 5.0 and then proceeds to conduct a thorough review of the different security risks associated with CPSs in the context of Industry 5.0.Afterward,the study also presents the privacy implications inherent in these systems,particularly in light of the massive data collection and processing required.In addition,the paper delineates potential avenues for future research and provides countermeasures to surmount these challenges.Overall,the study underscores the imperative of adopting comprehensive security and privacy strategies within the context of Industry 5.0.

Security-Reliability Tradeoff Analysis for Jamming Aided Decode-and-Forward Relay Networks

In this paper,we explore a cooperative decode-and-forward(DF)relay network comprised of a source,a relay,and a destination in the presence of an eavesdropper.To improve physical-layer security of the relay system,we propose a jamming aided decodeand-forward relay(JDFR)scheme combining the use of artificial noise and DF relaying which requires two stages to transmit a packet.Specifically,in stage one,the source sends confidential message to the relay while the destination acts as a friendly jammer and transmits artificial noise to confound the eavesdropper.In stage two,the relay forwards its re-encoded message to the destination while the source emits artificial noise to confuse the eavesdropper.In addition,we analyze the security-reliability tradeoff(SRT)performance of the proposed JDFR scheme,where security and reliability are evaluated by deriving intercept probability(IP)and outage probability(OP),respectively.For the purpose of comparison,SRT of the traditional decode-and-forward relay(TDFR)scheme is also analyzed.Numerical results show that the SRT performance of the proposed JDFR scheme is better than that of the TDFR scheme.Also,it is shown that for the JDFR scheme,a better SRT performance can be obtained by the optimal power allocation(OPA)between the friendly jammer and user.

A Practical Regular LDPC Coded Scheme for Physical-Layer Information Security

In this paper,we aim to design a practical low complexity low-density parity-check(LDPC)coded scheme to build a secure open channel and protect information from eavesdropping.To this end,we first propose a punctured LDPC coded scheme,where the information bits in a codeword are punctured and only the parity check bits are transmitted to the receiver.We further propose a notion of check node type distribution and derive multi-edge type extrinsic information transfer functions to estimate the security performance,instead of the well-known weak metric bit error rate.We optimize the check node type distribution in terms of the signal-to-noise ratio(SNR)gap and modify the progressive edge growth algorithm to design finite-length codes.Numerical results show that our proposed scheme can achieve a lower computational complexity and a smaller security gap,compared to the existing scrambling and puncturing schemes.

Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

In the cloud environment,ensuring a high level of data security is in high demand.Data planning storage optimization is part of the whole security process in the cloud environment.It enables data security by avoiding the risk of data loss and data overlapping.The development of data flow scheduling approaches in the cloud environment taking security parameters into account is insufficient.In our work,we propose a data scheduling model for the cloud environment.Themodel is made up of three parts that together help dispatch user data flow to the appropriate cloudVMs.The first component is the Collector Agent whichmust periodically collect information on the state of the network links.The second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the scheduler.The third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable paths.It should be noted that each part of the proposedmodel requires the development of its algorithms.In this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link state.These algorithms are based on the grouping of transmitted files and the iterative method.The proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)problem.The experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

Advancing 5G Network Applications Lifecycle Security:An ML-Driven Approach

As 5th Generation(5G)and Beyond 5G(B5G)networks become increasingly prevalent,ensuring not only networksecurity but also the security and reliability of the applications,the so-called network applications,becomesof paramount importance.This paper introduces a novel integrated model architecture,combining a networkapplication validation framework with an AI-driven reactive system to enhance security in real-time.The proposedmodel leverages machine learning(ML)and artificial intelligence(AI)to dynamically monitor and respond tosecurity threats,effectively mitigating potential risks before they impact the network infrastructure.This dualapproach not only validates the functionality and performance of network applications before their real deploymentbut also enhances the network’s ability to adapt and respond to threats as they arise.The implementation ofthis model,in the shape of an architecture deployed in two distinct sites,demonstrates its practical viability andeffectiveness.Integrating application validation with proactive threat detection and response,the proposed modeladdresses critical security challenges unique to 5G infrastructures.This paper details the model,architecture’sdesign,implementation,and evaluation of this solution,illustrating its potential to improve network securitymanagement in 5G environments significantly.Our findings highlight the architecture’s capability to ensure boththe operational integrity of network applications and the security of the underlying infrastructure,presenting asignificant advancement in network security.