Development Status and Industrial Security Countermeasures of Maize Deep-processing Industry in Shandong Province--Based on the Actual Investigation in Five Cities and Counties of Shandong Province

Corn deep processing industry is an important follow-up industry for corn production and processing. Shandong has numerous largescale corn processing enterprises and is one of the fast-growing regions in China for deep processing of corn. The status of production and processing of corn in the major corn-producing areas of Shandong Province such as Dezhou,Liaocheng and Tai'an was investigated on the spot. It was found that the development of the corn industry in Shandong also has many problems,such as the mismatch between corn demand and production areas,the excessively small planting area of special corn and the poor communication between technology and demand,resulting in barriers in technology and raw materials in the production and processing links of corn and making it difficult to form a complete industrial chain system. According to the actual investigation,a highly efficient agricultural industry safety review mechanism was established based on the sound judgement of industrial safety to ensure the safety of the company's development,and at the same time,the interpretation and promotion of the strategy of going abroad was strengthened,so as to provide a full range of information services for corn processing enterprises and help to further develop and optimize the corn industry in Shandong.

Advancing Autoencoder Architectures for Enhanced Anomaly Detection in Multivariate Industrial Time Series

In the context of rapid digitization in industrial environments,how effective are advanced unsupervised learning models,particularly hybrid autoencoder models,at detecting anomalies in industrial control system(ICS)datasets?This study is crucial because it addresses the challenge of identifying rare and complex anomalous patterns in the vast amounts of time series data generated by Internet of Things(IoT)devices,which can significantly improve the reliability and safety of these systems.In this paper,we propose a hybrid autoencoder model,called ConvBiLSTMAE,which combines convolutional neural network(CNN)and bidirectional long short-term memory(BiLSTM)to more effectively train complex temporal data patterns in anomaly detection.On the hardware-in-the-loopbased extended industrial control system dataset,the ConvBiLSTM-AE model demonstrated remarkable anomaly detection performance,achieving F1 scores of 0.78 and 0.41 for the first and second datasets,respectively.The results suggest that hybrid autoencoder models are not only viable,but potentially superior alternatives for unsupervised anomaly detection in complex industrial systems,offering a promising approach to improving their reliability and safety.

Security for Industrial Communication Systems

B. Remote Access to Stand-Alone Embedded Systems Industrial controllers, especially for power system and transportation applications, are often deployed as stand-alone systems in a geographically dispersed area. Maintenance and service costs of stand-alone embedded systems can be reduced when they can be

Security for Industrial Communication Systems

B. Network Architectures This section describes the main types of industrial and utility communication network topologies and protocols, in preparation for the discussion of specific security issues in the later sections. Communication networks for industrial automation are typically built in hierarchi-

Security for Industrial Communication Systems

D.Security on the Field Bus and Device Level As described in SectionⅢ-B,Fig.2,in- dustrial communication networks involve a number of levels.The lowest level\is closest to the application specific devices such as sensors,meters,and actuators.A large number of specialized and partly proprietary commu- nication systems,media,and protocols can be found on this level.Most were developed at a time when security issues were of lesser con- cern than today,and when no practical secu- rity measures were available.

Security for Industrial Communication Systems

E. Security of Embedded Systems for Industrial Control and Communication Industrial automation controllers are typically implemented on embedded computers. Such embedded systems have to cope with restrictions on cost, real-time performance, power consumption, and other constraints which are even more demanding than in large workstations. A reference discusses these aspects with the example of a thermostat con-

Analysis and Research on China′s Industrial Internet Security Development

Under the new situation of"integration of industrialization and industrialization"in China,security situational awareness is an important means to solve the problems of unclear boundaries,multiple roles and complex business relationships of industrial Internet.The main contents of the platform include industrial data collection,industrial protocol identification,industrial asset detection and industrial threat monitoring.Among them,risk prevention and detection,key data protection,cloud platform and identification resolution node protection are all important issues.On the one hand,escorting the industrial Internet business needs to summarize the industrial Internet network security data and master the network security situation from the overall perspective.On the other hand,it is also necessary to establish an industrial Internet platform security early warning and emergency response process system,promote the security rectification of industrial platform enterprises,find the security threats and risks that have been hidden in the industrial Internet platform for a long time,and provide perception and decision⁃making support for enterprises.

Edge Computing Task Scheduling with Joint Blockchain and Task Caching in Industrial Internet

Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost.

One-Variable Attack on the Industrial Fault Classification System and Its Defense

Recently developed fault classification methods for industrial processes are mainly data-driven.Notably,models based on deep neural networks have significantly improved fault classification accuracy owing to the inclusion of a large number of data patterns.However,these data-driven models are vulnerable to adversarial attacks;thus,small perturbations on the samples can cause the models to provide incorrect fault predictions.Several recent studies have demonstrated the vulnerability of machine learning methods and the existence of adversarial samples.This paper proposes a black-box attack method with an extreme constraint for a safe-critical industrial fault classification system:Only one variable can be perturbed to craft adversarial samples.Moreover,to hide the adversarial samples in the visualization space,a Jacobian matrix is used to guide the perturbed variable selection,making the adversarial samples in the dimensional reduction space invisible to the human eye.Using the one-variable attack(OVA)method,we explore the vulnerability of industrial variables and fault types,which can help understand the geometric characteristics of fault classification systems.Based on the attack method,a corresponding adversarial training defense method is also proposed,which efficiently defends against an OVA and improves the prediction accuracy of the classifiers.In experiments,the proposed method was tested on two datasets from the Tennessee–Eastman process(TEP)and steel plates(SP).We explore the vulnerability and correlation within variables and faults and verify the effectiveness of OVAs and defenses for various classifiers and datasets.For industrial fault classification systems,the attack success rate of our method is close to(on TEP)or even higher than(on SP)the current most effective first-order white-box attack method,which requires perturbation of all variables.

What Are the Strategic Industries that Must Be Given Priority？

This paper presents the argument that the security of strategic industries is more important than financial security and lies at the heart of economic security. It further identifies the following industries as strategic industries： sustenance industry, infrastructure industry, equipment industry, environmental industry and information industry. For the health and security of the national economy, this paper proposes that a priority must be placed on researching the security of strategic industries.

A New Intrusion Detection Algorithm AE-3WD for Industrial Control Network

In this paper,we propose a intrusion detection algorithm based on auto-encoder and three-way decisions(AE-3WD)for industrial control networks,aiming at the security problem of industrial control network.The ideology of deep learning is similar to the idea of intrusion detection.Deep learning is a kind of intelligent algorithm and has the ability of automatically learning.It uses self-learning to enhance the experience and dynamic classification capabilities.We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning,a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve intrusion detection accuracy.In the processing,deep learning AutoEncoder is used to extract the features of high-dimensional data by combining the coefficient penalty and reconstruction loss function of the encode layer during the training mode.A multi-feature space can be constructed by multiple feature extractions from AutoEncoder,and then a decision for intrusion behavior or normal behavior is made by three-way decisions.NSL-KDD data sets are used to the experiments.The experiment results prove that our proposed method can extract meaningful features and effectively improve the performance of intrusion detection.

A note on diagnosis and performance degradation detection in automatic control systems towards functional safety and cyber security

This note addresses diagnosis and performance degradation detection issues from an integrated viewpoint of functionality maintenance and cyber security of automatic control systems.It calls for more research attention on three aspects:(i)application of control and detection uni ed framework to enhancing the diagnosis capability of feedback control systems,(ii)projection-based fault detection,and complementary and explainable applications of projection-and machine learning-based techniques,and(iii)system performance degradation detection that is of elemental importance for today's automatic control systems.Some ideas and conceptual schemes are presented and illustrated by means of examples,serving as convincing arguments for research e orts in these aspects.They would contribute to the future development of capable diagnosis systems for functionality safe and cyber secure automatic control systems.

Promoting the Safe and Stable Development of Industrial and Supply Chains under the New Pattern of Development

It is an important component of national security,and also a required driver for coordinating development and security and building a new pattern of development to maintain the security and stability of and enhance the independent controllability of industrial and supply chains.According to the principles of taking enterprises as the mainstay,coordinating points and chains,combining advantages and disadvantages,adopting classified policies,and linking internal and external chains,the three industrial chains should be planned as a whole for the purpose of their coordinated and efficient operation,so as to solidly enhance,supplement,optimize,and consolidate industrial and supply chains,enhance support to the core links of industrial chains,exploit preponderant and advantageous links,accelerate the incubation of leading and hidden champion enterprises in the industrial ecology,promote the coordination between central and local governments,optimize the policy support system for the modernization of industrial chains,deepen international cooperation among industrial chains,expedite the construction of independent,controllable,safe,and efficient industrial and supply chains,and significantly improve the stability,international competitiveness,and modernization of China's industrial and supply chains.

A Study on the Path of Improving the Modernization Level of Industrial and Supply Chains

is well known that a lot of studies have been conducted on the modernization of industrial and supply chains.However,scholars have not reached a consensus on the definition and dynamic mechanism of the improvement of the modernization level of industrial and supply chains yet.This paper clarifies the constituent factors of industrial and supply chains and defines the connotation of improvement of the modernization level of industrial and supply chains from the perspective of constituent subjects and structure according to the characteristics and requirements of the new era.Then,the paper proposes improving the modernization level of industrial and supply chains aiming to make it more adaptable to the requirements of Chinese development in a new stage,the increasing instability and uncertainty in the international environment,and a new round of technological change.To this end,the improvement of the modernization level of industrial and supply chains should embrace the further enhancement of the following dimensions:innovation capability,added value,sustainability,digitalization,safety and reliability,fairness,and smooth coordination.Based on the analysis of the upgrade types of the existing industrial and supply chains,this paper distinguishes the factors driving the improvement of the modernization level of industrial and supply chains from a basic level.It proposes four basic dynamic mechanisms,namely,final demand,factor supply,regional industrial cluster,and integration into the global industrial division system.Finally,the paper analyzes the working way of the four dynamic mechanisms and the main constraints they face,and based on this,put forward a path to break through the constraints.