A GAN-EfficientNet-Based Traceability Method for Malicious Code Variant Families

Due to the diversity and unpredictability of changes in malicious code,studying the traceability of variant families remains challenging.In this paper,we propose a GAN-EfficientNetV2-based method for tracing families of malicious code variants.This method leverages the similarity in layouts and textures between images of malicious code variants from the same source and their original family of malicious code images.The method includes a lightweight classifier and a simulator.The classifier utilizes the enhanced EfficientNetV2 to categorize malicious code images and can be easily deployed on mobile,embedded,and other devices.The simulator utilizes an enhanced generative adversarial network to simulate different variants of malicious code and generates datasets to validate the model’s performance.This process helps identify model vulnerabilities and security risks,facilitating model enhancement and development.The classifier achieves 98.61%and 97.59%accuracy on the MMCC dataset and Malevis dataset,respectively.The simulator’s generated image of malicious code variants has an FID value of 155.44 and an IS value of 1.72±0.42.The classifier’s accuracy for tracing the family of malicious code variants is as high as 90.29%,surpassing that of mainstream neural network models.This meets the current demand for high generalization and anti-obfuscation abilities in malicious code classification models due to the rapid evolution of malicious code.

Potentials and Challenges of Carbon Knowledge Graph in Sustainable Textile Production for Carbon Traceability:A Review

Textile production has received considerable attention owing to its significance in production value,the complexity of its manufacturing processes and the extensive reach of its supply chains.However,textile industry consumes substantial energy and materials and emits greenhouse gases that severely harm the environment.In addressing this challenge,the concept of sustainable production offers crucial guidance for the sustainable development of the textile industry.Low-carbon manufacturing technologies provide robust technical support for the textile industry to transition to a low-carbon model by optimizing production processes,enhancing energy efficiency and minimizing material waste.Consequently,low-carbon manufacturing technologies have gradually been implemented in sustainable textile production scenarios.However,while research on low-carbon manufacturing technologies for textile production has advanced,these studies predominantly concentrate on theoretical methods,with relatively limited exploration of practical applications.To address this gap,a thorough overview of carbon emission management methods and tools in textile production,as well as the characteristics and influencing factors of carbon emissions in key textile manufacturing processes is presented to identify common issues.Additionally,two new concepts,carbon knowledge graph and carbon traceability,are introduced,offering strategic recommendations and application directions for the low-carbon development of sustainable textile production.Beginning with seven key aspects of sustainable textile production,the characteristics of carbon emissions and their influencing factors in key textile manufacturing process are systematically summarized.The aim is to provide guidance and optimization strategies for future emission reduction efforts by exploring the carbon emission situations and influencing factors at each stage.Furthermore,the potential and challenges of carbon knowledge graph technology are summarized in achieving carbon traceability,and several research ideas and suggestions are proposed.

Research Progress and Prospects of Traceability Methods of Organic Matter in Lake Sediment

Organic matter in sediment is an important carrier of energy and material circulation in ecosystems,and also provides an important place for the accumulation of nutrient salts.The study of its composition,structure and characteristics is of great importance for the study of the geochemical cycle of sediment in water environment.Identifying the source of organic matter in sediment and mastering its temporal and spatial distribution characteristics are important ways to reveal the migration and transformation law of pollutants,which is conducive to controlling nutrient load from the source and providing strong technical support for the fine management of water environment.

Research of Blockchain Technology in the Traceability of Characteristic Agricultural Products

With the increasingly prominent problem of food safety,the quality traceability of characteristic agricultural products has become a pressing issue.This study focuses on the application of blockchain technology in the traceability of characteristic agricultural products,aiming to explore its potential and practical value in improving the efficiency and transparency of the traceability system of agricultural products.Through the combination of case analysis and model construction,a blockchain-based traceability system for characteristic agricultural products was established.The results showed that the traceability system could effectively record the whole process information of agricultural products from production and processing to sales,and greatly improve the immutability and traceability of data.Lastly,this paper also points out that the use of blockchain technology can improve the market trust in characteristic agricultural products,provide consumers with authentic and reliable product information,and provide new technical means for the quality management of agricultural products.

Application of Blockchain Sharding Technology in Chinese Medicine Traceability System

Traditional Chinese Medicine(TCM)is one of the most promising programs for disease prevention and treatment.Meanwhile,the quality of TCM has garnered much attention.To ensure the quality of TCM,many works are based on the blockchain scheme to design the traceability scheme of TCM to trace its origin.Although these schemes can ensure the integrity,sharability,credibility,and immutability of TCM more effectively,many problems are exposed with the rapid growth of TCM data in blockchains,such as expensive overhead,performance bottlenecks,and the traditional blockchain architecture is unsuitable for TCM data with dynamic growth.Motivated by the aforementioned problems,we propose a novel and lightweight TCM traceability architecture based on the blockchain using sharding(LBS-TCM).Compared to the existing blockchain-based TCM traceability system,our architecture utilizes sharding to develop a novel traceability mechanism that supports more convenient traceability operations for TCM requirements such as uploading,querying,and downloading.Specifically,our architecture consists of a leader shard blockchain layer as its main component,which employs a sharding mechanism to conveniently TCM tracing.Empirical evaluations demonstrated that our architecture showed better performance in many aspects compared to traditional blockchain architectures,such as TCM transaction processing,TCM transaction querying,TCM uploading,etc.In our architecture,tracing TCM has become a very efficient operation,which ensures the quality of TCM and provides great convenience for subsequent TCM analysis and retrospective research.

Smart Contract to Traceability of Food Social Selling

Traditionally,food sustainability has been considered solely in the stage of agricultural production.However,globalization,the expansion of the food production industry,and the emergence of supermarket chains that control the retail food market require specific significant changes in supply chains in the food sector and,therefore,we need to address the economic,social,and environmental impacts of these events.On the other hand,social selling has increased rapidly in recent years,with a further boom,following current events related to the coronavirus disease(COVID-19).This explosion of social sales,where there are usually no control and regulation entities,can bring problems associated with mishandling items.In this paper,we expose how Blockchain technology supports the traceability of social sales by validating the data provided by the chain participants such as digital health passports,production and transport data in the sale process;the proposed solution generates recommendations on productmanagement considering the agreements previously made by the network actors.To evaluate the proposed smart contracts,we useHyperledger Caliper,obtaining an average throughput of 12.6 transactions per second and an average latency of 0.3 s for the asset update process.We also use a study case to evaluate the proposed project platform’s selling-transport stage using Internet of Things(IoT)sensors.

ChainApparel: A Trustworthy Blockchain and IoT-Based Traceability Framework for Apparel Industry 4.0

Trustworthiness and product traceability are essential factors in the apparel industry 4.0 for establishing successful business relationships among stakeholders such as customers,manufacturers,suppliers,and consumers.Each stakeholder has implemented different technology-based systems to record and track product transactions.However,these systems work in silos,and there is no intra-system communication,leading to a lack of complete supply chain traceability for all apparel stakeholders.Moreover,apparel stakeholders are reluctant to share their business information with business competitors;thus,they involve third-party auditors to ensure the quality of the final product.Furthermore,the apparel manufacturing industry faces challenges with counterfeit products,making it difficult for consumers to determine the authenticity of the products.Therefore,in this paper,a trustworthy apparel product traceability framework called ChainApparel is developed using the Internet of Things(IoT)and blockchain to address these challenges of authenticity and traceability of apparel products.Specifically,multiple smart contracts are designed and developed for registration,process execution,audit,fault,and product traceability to authorize,validate,and trace every business transaction among the apparel stakeholders.Further,the real-time performance analysis of ChainApparel is carried out regarding transaction throughput and latency by deploying the compute nodes at different geographical locations using Hyperledger Fabric.The results conclude that ChainApparel accomplished significant performance under diverse workloads while ensuring complete traceability along the complex supply chain of the apparel industry.Thus,the ChainApparel framework helps make the apparel product more trustworthy and transparent in the market while safeguarding trust among the industry stakeholders.

Research on Welding Quality Traceability Model of Offshore Platform Block Construction Process

Quality traceability plays an essential role in assembling and welding offshore platform blocks.The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platform and the process level of the offshore industry.Currently,qualitymanagement remains in the era of primary information,and there is a lack of effective tracking and recording of welding quality data.When welding defects are encountered,it is difficult to rapidly and accurately determine the root cause of the problem from various complexities and scattered quality data.In this paper,a composite welding quality traceability model for offshore platform block construction process is proposed,it contains the quality early-warning method based on long short-term memory and quality data backtracking query optimization algorithm.By fulfilling the training of the early-warning model and the implementation of the query optimization algorithm,the quality traceability model has the ability to assist enterprises in realizing the rapid identification and positioning of quality problems.Furthermore,the model and the quality traceability algorithm are checked by cases in actual working conditions.Verification analyses suggest that the proposed early-warningmodel for welding quality and the algorithmfor optimizing backtracking requests are effective and can be applied to the actual construction process.

Cross-Domain Data Traceability Mechanism Based on Blockchain

With the application and development of blockchain technology,many problems faced by blockchain traceability are gradually exposed.Such as cross-chain information collaboration,data separation and storage,multisystem,multi-security domain collaboration,etc.To solve these problems,it is proposed to construct trust domains based on federated chains.The public chain is used as the authorization chain to build a cross-domain data traceability mechanism applicable to multi-domain collaboration.First,the architecture of the blockchain cross-domain model is designed.Combined with the data access strategy and the decision mechanism,the open and transparent judgment of cross-domain permission and cross-domain identity authentication is realized.And the public chain consensus node election mechanism is realized based on PageRank.Then,according to the characteristics of a nonsingle chain structure in the process of data flow,a data retrievalmechanism based on a Bloom filter is designed,and the cross-domain traceability algorithm is given.Finally,the safety and effectiveness of the traceability mechanism are verified by security evaluation and performance analysis.

Traceability Technology of DC Electric Energy Metering for On-Site Inspection of Chargers

The on-site inspection of high-power DC chargers results in new DC high-current measurement and DC energy traceability system requirements.This paper studies the traceability technology of electric energy value for automotive high-power DC chargers,including:(1)the traceability method of the built-in DC energy meter and shunt of the charger;(2)precision DC high current and small precision DC voltage output and measurement technology.This paper designs a 0.1 mA∼600 A DC high current measurement system and proposes a 0.005 level DC powermeasurement traceability system.The uncertainty evaluation experiment of theDC powermeasurement calibration system and the high-power DC charger’s on-site calibration experiment results verify the method’s effectiveness and feasibility in this paper.The experimental results show that the combined standard uncertainty of the DC power metering verification system can be 0.0451%.

Impacts of Transparency and Traceability on Fashion Supply Chain System

The level of fashion consumer awareness and communication regarding sustainable consumption is rising. Organizations are working to provide clarity and guidance on fashion consumption. Brands are experimenting with new materials and supply chain strategies, and suppliers are improving the manufacturing processes and quality of products. However, given the size and complexity of the industrial process, these efforts are not adequate in ensuring a sustainable fashion supply chain. Transparency and traceability in the fashion supply chain are needed to improve the fashion industry by supporting sustainable and ethical practices in the apparel supply chain. Key gaps include a lack of comprehensive and transparent information about how, where, and by whom materials are sourced, processed, and assembled;a lack of transparency in the supply chain practices and procedures affects the environment, working conditions, and human health. The industry has to build the capacity to manage its supply chain, more effectively and responsibly, by improving transparency and traceability as the top goals. So, in this context, the main purpose of this research paper is to study the impacts of transparency and traceability on the dimensions of sustainability in fashion supply chain. The researchers have applied descriptive research methods in which secondary data are collected and analyzed through a literature review of peer-reviewed research papers and the primary data are collected through the survey method by distributing a semi structured questionnaire. The data collected are analyzed using statistical tools and techniques. Finally, the results are discussed and presented.

Analysis on Classified Storage and Traceability of Construction Project Archives

With the development and progress of economic construction and market economy,urban construction is also developing rapidly.In the field of construction engineering,a large number of construction engineering files are constantly being produced and accumulated.Therefore,the role of file management is becoming more and more important.The archives are the true records of the whole process of project construction,including the information on the whole process from project design to completion,and are also the main basis for operation management after project delivery.However,there are many aspects to construction project archives,and there are many problems.Nowadays,the classification and preservation of archives are receiving more and more attention.In this article,the origin and development history of construction project archives is first expounded,and its attributes and importance are analyzed.Secondly,the differences between ancient and modern archives management are compared,and at the same time suggestions on improving the archives’traceability system,strengthening the use of archives,and establishing and improving archives management are given.In this paper,we summarize the problems in archives sorting and put forward specific solutions to improve the standardization and systematic management of archives work and enhance the authenticity and integrity of construction project archives.

论预制菜的安全追溯体系

预制菜行业发展迅速,但与之配套的安全追溯体系却未能及时建立。实践中,预制菜的安全追溯体系面临着主体分工不明确,追溯范围不清晰以及识别技术不统一等问题。为了预制菜行业的可持续发展,实现预制菜去向可追、来源可查、责任可定,有必要建立起预制菜的安全追溯体系。分析了预制菜行业的食品安全问题,总结了现行食品安全追溯体系的现状与不足,并提出了完善预制菜安全追溯体系的路径,指出应在食品安全法律规范的基础上,明确预制菜安全追溯体系的追溯主体、追溯范围和识别技术,以期推动预制菜行业健康发展,使预制菜吃得放心,用得安心。

具有高价值密度的农业物联网数据区块链压缩存储方案

针对现有区块链物联网体系主要采用链上存储摘要链下保留原始数据的存储方式中链上无法直接获得真实数据的问题,该研究提出了一种具有高价值密度的农业物联网数据区块链压缩存储方案。首先,边缘服务器将收集的同一批数据聚合到同一批事务中;其次,设计离群值可处理的自适应有损压缩方法,在满足用户保真度要求的前提下降低数据冗余;最后,压缩数据上链,实现区块链上物联网数据的高价值密度存储。与现有方案相比,该方案能提高链上存储真实物联网数据的效率。试验结果表明,在使用自适应压缩方法压缩数据时,针对不同的数据集会自适应选取k值,在满足用户重建精度的前提下,获得良好压缩效果,减少链上存储空间,提高了数据价值密度;相对于风速之类频率较高的数据,温湿度、二氧化碳等变化频率较低的数据可以获得较高的压缩比;当假设正常数据压缩比为10:1时,该方案可节省约85%的链上存储空间,相应的价值密度提高了约85%。该研究可为农产品溯源过程中的物联网数据高效存储提供解决方案,为实现分布式农业物联网数据压缩存储提供技术支持。

基于文献计量学分析的全球食品追溯研究进展

食品追溯是确保食品质量与安全的重要手段,本文对2001—2022年科学引文索引数据库收录的食品追溯论文进行计量分析和可视化呈现,以便为国内食品追溯的进一步研究和开发提供参考。结果发现:全球共有80个国家/地区、1 136个研究机构、3 020名作者、255种期刊开展了食品追溯研究,跨国家/地区合作、多学科交叉融合频繁;中国、意大利、美国、西班牙、荷兰等表现出较大的研究体量与较强的合作关系,意大利、美国、荷兰、西班牙食品追溯研究的总体质量较高,研究领域集中在食品科学技术、化学、农业、工程学上,在计算机科学、生态学与环境学、饮食与营养学领域也有较多研究成果。研究热点有食品质量与安全、食品供应链管理、原产地、追溯技术、食品鉴别与认证、支付意愿等。未来学术前沿将围绕基于工业4.0的智能食品追溯系统、以全基因组学和下一代测序技术为代表的食品真实性检测鉴别技术以及食品追溯系统主体参与动力、利益博弈和溢价支付的机制3个方面展开。

区块链食品追溯系统对消费者食品安全信任的影响机制

运用信任转移理论和D&M信息系统成功模型,构建基于区块链追溯的食品安全信任模型,深入探讨区块链食品追溯系统对消费者食品安全信任的机制。研究发现,系统质量、信息质量可以显著促进消费者食品安全信任,系统信任和供应商信任在此过程中起到了显著的中介作用,区块链知识在系统信任到食品安全信任转移过程中存在显著的正向调节作用。据此提出通过建设和维护区块链食品追溯系统,收集和分析系统数据,优化系统质量和信息披露,普及区块链知识等措施,增强消费者对食品的信任感,进一步提升食品安全水平。

面向软件定义网络的异常流量检测研究综述

针对软件定义网络(SDN)较传统网络更易遭受网络攻击的现实,从技术原理和架构特点出发,对近年来面向软件定义网络的异常流量检测研究进展进行综述,分析了SDN可能遭受网络攻击的组织形式,讨论了当前SDN异常流量检测、异常流量溯源、异常流量缓解相关技术的特点、优势及不足;对当前研究中常用的数据集进行了对比分析,并梳理出一些通用的数据预处理方法;总结并展望了未来SDN环境下异常流量检测方法的研究方向。调研结果可以指导实际应用需求中适配方法的选取,提出待解决的问题和矛盾可为后续研究提供引导。

基于区块链及IPFS的农产品多链追溯系统研究

面对农产品供应市场日益庞大以及现存追溯系统中心化结构严重、溯源信息模糊简陋、数据安全难以得到有效保障等问题,通过分析供应链的业务流程及相关特点,融合区块链及IPFS技术设计灵活的多链分布式追溯系统以应对错综复杂多变的市场情况中的精准溯源及监管的需求。充分利用星际文件系统IPFS的去重存储以及分布式存储特性提高存储资源的利用率,解决以往溯源数据存储中心化严重、数据类型单一、负载过大等问题;区块链多链与IPFS私有网络的结合以及CBC、ECC两个加密算法的采用可以支持全面的市场监管,并可以满足企业隐私数据的加密保护需求。为验证模型有效性,以水培蔬菜溯源项目作为应用案例进行分析测试,其中区块链多链系统吞吐量达到上链500 TPS、查询400 TPS;CBC加密算法的相关性、扩展性分析中密文改变率分别达到96.727%、97.136%。测试结果表明:本追溯系统在实现溯源数据高效记录存储和精准监管溯源的基础上,也能够给予供应链内各方合法权益及隐私数据有效的安全保护,亦可以面对业务交错复杂的市场供应链,为完整可靠的农产品区块链追溯监管系统研究发展与落地实现提供借鉴与参考。

信息化质量追溯系统在消毒供应中心医疗器械管理中的应用效果

目的:探讨信息化质量追溯系统在消毒供应中心(CSSD)医疗器械管理中的应用效果。方法:选取郑州儿童医院CSSD采取常规管理期间(2020年6月至2021年6月)接收的1018件器械为对照组,选取应用信息化质量追溯系统管理后(2021年7月至2022年7月)接收的1018件器械为观察组。比较两组医疗器械管理质量(清洗、灭菌、包装不合格率)及各科室医护人员对CSSD的满意度。结果:观察组医疗器械清洗、包装、灭菌不合格率均低于对照组,差异有统计学意义(P<0.05);各科室医护人员对观察组服务态度、技术水平、器械供应及时性、器械结构功能、器械无菌性等方面的满意度均高于对照组,差异有统计学意义(P<0.05)。结论:信息化质量追溯系统用于CSSD医疗器械管理可提高管理质量,降低医疗器械清洗、包装、灭菌不合格率,提高各科室医护人员满意度,有效保障医疗安全。

基于近红外光谱特征的国产绿茶产地溯源研究

目的研究我国多省出产绿茶近红外光谱特征,探索以近红外光谱差异进行绿茶产地溯源研究的可行性。方法运用傅里叶变换红外光谱仪漫反射法扫描我国多个产区的169份代表性绿茶样本,谱图分别采用一阶导数(first derivative,1st)、最大最小归一化(max-min normalization,Max-min)、标准正态变量变换(standard normal variable transformation,SNV)和多元散射校正(multiplicative scatter correction,MSC)4种预处理方式处理,采用连续投影算法(successive projections algorithm,SPA)筛选产地差异波段,采用主成分分析(principal component analysis,PCA)对光谱降维处理,建立茶叶产区判别模型。结果采用Max-min、SNV、MSC处理的数据前3个主成分的累计方差贡献率均达到95%以上。分别建立基于主成分的线性判别分析(linear discriminant analysis,LDA)、支持向量机(support vector machine,SVM)、K-最近邻算法(K-nearest neighbor algorithm,KNN)判别模型。经交叉验证和测试集验证,确定最佳处理路线为卷积平滑(Savitzky-Golay,S-G)+MSC+SPA+PCA,结合KNN和SVM建立非线性模型,其光谱测试集判别正确率均达到94%以上。结论近红外光谱结合判别模型可以用于绿茶产地溯源,本研究为绿茶溯源及模型参数选择提供了一定的参考。