Current Issue : April - June Volume : 2021 Issue Number : 2 Articles : 5 Articles
Based on the research of business continuity and information security of the Internet of ,ings (IoT), a key business node\nidentification model for the Internet of ,ings security is proposed. First, the business nodes are obtained based on the business\nprocess, and the importance decision matrix of business nodes is constructed by quantifying the evaluation attributes of nodes.\nSecond, the attribute weights are improved by the analytic hierarchy process (AHP) and entropy weighting method from\nsubjective and objective dimensions to form the combination weight decision matrix, and the analytic hierarchy process and\nentropy weighting VIKOR (AE-VIKOR) method are used to calculate the business node importance coefficient to identify the key\nnodes. Finally, according to the NSL-KDD dataset, the network security events of IoT network intrusion detection based on\nmachine learning are monitored purposefully, and after the information security event occurs in the smart mobile phone, which\nimpacts through IoT on the business system, the impact of the key business node on business continuity is analyzed, and the\nbusiness continuity risk value is calculated to evaluate the business risk to prove the effectiveness of the model. ,e experimental\nresults of the civil aviation departure business show that the AE-VIKOR method can effectively identify key business node, and the\nimpact of the key business node on business continuity is analyzed, which further proves the efficiency and accuracy of the model\nin identifying the key business node....
With the development of wireless rechargeable sensor networks (WRSNs ), security issues\nof WRSNs have attracted more attention from scholars around the world. In this paper, a novel\nepidemic model, SILS(Susceptible, Infected, Low-energy, Susceptible), considering the removal,\ncharging and reinfection process of WRSNs is proposed. Subsequently, the local and global stabilities\nof disease-free and epidemic equilibrium points....................
Industrial control systems (ICS) involve many key industries, which once attacked will cause heavy losses. However, traditional\npassive defense methods of cybersecurity have difficulty effectively dealing with increasingly complex threats; a knowledge graph\nis a new idea to analyze and process data in cybersecurity analysis. We propose a novel overall framework of data-driven\nindustrial control network security defense, which integrated fragmented multisource threat data with an industrial network\nlayout by a cybersecurity knowledge graph. In order to better correlate data to construct a knowledge graph, we propose a\ndistant supervised relation extraction model ResPCNN-ATT; it is based on a deep residual convolutional neural network and\nattention mechanism, reduces the influence of noisy data in distant supervision, and better extracts deep semantic features in\nsentences by using deep residuals. We empirically demonstrate the performance of the proposed method in the field of general\ncybersecurity by using dataset CSER; the model proposed in this paper achieves higher accuracy than other models. And then,\nthe dataset ICSER was used to construct a cybersecurity knowledge graph (CSKG) on the basis of analyzing specific industrial\ncontrol scenarios, visualizing the knowledge graph for further security analysis to the industrial control system....
Aiming at the security problems caused by the access of a large number of new advanced metering system (AMI) equipment and\nthe rapid growth of new business data interaction volume and interaction frequency, a lightweight data security protection\nmethod for power Internet of things (IoT) is proposed. Firstly, based on the â??cloud-edge-endâ? AMI system architecture, a\nmultilevel anonymous authentication method is proposed to reduce the complexity of low-end equipment access without\nreauthentication when smart meters and other devices access the system. .en, when fully homomorphic encryption is used for\ndata encryption transmission, the lightweight packet recombination protocol is introduced, the lightweight hash function is used\nto reduce the calculation cost, and the sliding address window mechanism is used to reduce the packet loss rate. Finally, improved\nsecure multiparty computing (SMPC) is used to achieve frequency hopping data aggregation, using shared key to calculate local\nshared value for key update, reducing data interaction between massive devices and AMI cloud security server, and improving\nbroadband utilization in data aggregation process. .e experiment results indicate that the proposed method obtained better\nutilization in bandwidth and shorter average data collection completion time. Besides, the proposed method can ensure the\ninformation security in the interaction process....
5G applications face security risks due to the new technology used and the performance requirements of the specific application\nscenario. This paper analyzes the security requirements and presents hierarchical solutions for stakeholders to build secure 5G\napplications. First, we summarize the technical characteristics and typical usage scenarios of 5G. Then, we analyze the security\nand privacy risks faced by 5G applications and related security standards and research work. Next, we give the system reference\narchitecture and overall security and privacy solutions for 5G applications. Based on the three major application scenarios of\neMBB, uRLLC, and mMTC, we also provide specific suggestions for coping with security and privacy risks. Finally, we present a\nuse case of industrial terminal access control and make conclusions of this paper....
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