An Optimization Technique for Intrusion Detection of Industrial Control Network Vulnerabilities Based on BP Neural Network

Xia, Wei; Neware, Rahul; Kumar, Sanjeet; Karras, D.A.; Rizwan, Ali

doi:10.21203/rs.3.rs-990908/v1

Cited by 5 publications

(5 citation statements)

References 16 publications

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“…It is common for consumers to choose "Auto" channel selection rather than a particular channel when setting up an AP. Because of this, we only allow the use of orthogonal channels that have been demonstrated to not interfere with each other while transmitting data [28][29][30]. For lack of space in North America, we looked Figure 4 indicates that interfering APs (blue) utilise a different channel than the target SR-WLAN.…”

Section: Proposed Methodologymentioning

confidence: 99%

Aggregation-Based Dynamic Channel Bonding to Maximise the Performance of Wireless Local Area Networks (WLAN)

Parashar

Kashyap

Rizwan

et al. 2022

Wireless Communications and Mobile Computing

101

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Channel bonding is considered by the IEEE 802.11ac amendment to improve wireless local area network (WLAN) performance. In this article, the channel bonding and aggregation method were proposed to increase wireless local area network performance (WLANs). It combines many channels (or lanes) to boost the capacity of modem traffic. Channel bonding is the combination of two neighbouring channels within a certain frequency band to increase wireless device throughput. Wi-Fi employs channel bonding, also known as Ethernet bonding. Channel bandwidth is equal to the uplink/downlink ratio multiplied by the operational capacity. A single 20 MHz channel is divided into two, four, or eight power channels. At 80 MHz, there are more main and smaller channels. Performance of short-range WLANs is determined through graph-based approach. The two-channel access techniques including channel bonding proposed for the IEEE 802.11ac amendment are analysed and contrasted. The novel channel sizing algorithm based on starvation threshold is proposed to expand the channel size to improve WLAN performance. Second-cycle throughput is estimated at 20 Mbps, much beyond the starvation threshold. Our test reveals access points (AP) 1, 2, and 4 have enough throughput. A four-AP WLAN with a 5-Mbps starvation threshold is presented. C160 = 1 since there is only one 160 MHz channel. MIR (3, 160 (a, a, a)) =0, indicating that AP 3’s predicted throughput is 0. The algorithm rejects the 160 MHz channel width since ST is larger than 0. The channel width in MHz is given by B =0,1 MIR. The MIR was intended to maximise simultaneous broadcasts in WLANs. The authors claim that aggregation with channel bonding outperforms so all WLAN APs should have a single-channel width. It usually outperforms fairness-based measures by 15% to 20%. Wi-Fi standards advise “channel bonding,” or using higher frequency channels. Later standards allow channel bonding by increasing bands and channel lengths. Wider channels enhance average WLAN AP throughput, but narrower channels reduce appetite. Finally, it is concluded that APs are more useful than STAs.

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Section: Proposed Methodologymentioning

confidence: 99%

Aggregation-Based Dynamic Channel Bonding to Maximise the Performance of Wireless Local Area Networks (WLAN)

Parashar

Kashyap

Rizwan

et al. 2022

Wireless Communications and Mobile Computing

101

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“…is creates an intriguing gap that need to be addressed in further study and is something that has been done. In addition, our findings indicate that a number of AI techniques, such as NLP (machine-human interactions), TS (optimization, robot dynamics, and programming that focuses on creating intelligent robots), and MDP, require additional research and the adoption of these techniques in the industrial sector (a framework for modelling the decision-making process) [21][22][23][24][25].…”

Section: Limitations and Findingsmentioning

confidence: 96%

Performance Optimization of Industrial Supply Chain Using Artificial Intelligence

Alomar

2022

Computational Intelligence and Neuroscience

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Nowadays, organized retailing has witnessed a newer trend in the upcoming generations. Globally, these changes are attributed to growing family income, increased female participation, the transformation from joint to nuclear family structure, and technological advancements. Moreover, other variables such as lower supply chain costs, growing sales, rising consumer demands, changing market structure, and increasing competition also influenced supply chain networks. It is observed that the organizational nonlivestock supply chain performance is affected by strategic, operational, and environmental aspects. AI is helping to deliver powerful optimization capabilities, which are required for more accurate capacity planning, improved productivity, high quality, lower costs, and greater output, all while fostering safer working conditions. These benefits are all made possible thanks to the introduction of AI in supply chains. By conducting a comprehensive analysis of the relevant previous research, the purpose of this work is to determine the specific contributions that artificial intelligence (AI) has made to supply chain management. This research attempted to discover the present as well as possible AI strategies that may increase both the study of Supply Chain Management as well as the practice of it. This was done in order to solve the current scientific gap of AI in Supply Chain Management. It was also found that there are holes in the existing study that need to be filled by more scientific investigation. To be more exact, the following four facets were discussed: (1) the AI approaches that are most often used in Supply Chain Management; (2) the AI techniques that have the potential to be used in Supply Chain Management; (3) the Supply Chain Management subfields that have benefited from the application of AI so far; and (4) the subfields that have a high potential to be improved by AI. Identifying and evaluating articles from the four supply chain management domains of logistics, marketing, supply chain management, and manufacturing require the use of a predetermined set of inclusion and exclusion criteria. In this study, insights are provided via the use of methodical analysis and synthesis. A better understanding of these parameters not only improves the nonlivestock supply chain processes but also ensures competitive advantage. The present research aims to test the following elements that including supply chain speed, customer retention, supply chain management integration, and various management. The proposed work categorizes the performance of the supply chain using the Improved Feed Forward Network with Particle Swarm Optimization technique. Results indicate that inventory management, customer happiness, profitability, and client base identification are listed as competitive advantage elements. On the other hand, stakeholder satisfaction, innovation and learning, market performance, customer satisfaction, and financial success are the six recognized organizational performance criteria. Resultantly, the overall performance metrics of the proposed work is 94.12%, while accuracy rate, specificity, and sensitivity rate are found to be 94.12%, 92.15%, and 89.14%, respectively. The research can be helpful for industrial managers to optimize the performance of supply chain systems using artificial intelligence.

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“…New network segmentation has been deployed. Cars from different zones must transport data packets from one zone to the next [31]. 9 Wireless Communications and Mobile Computing Figure 7 summarises the findings of a partitioned urban network.…”

Section: An Example Of a Vanet In A Congestedmentioning

confidence: 99%

Simulation of IoT-based Vehicular Ad Hoc Networks (VANETs) for Smart Traffic Management Systems

Rizwan

Karras

Dighriri

et al. 2022

Wireless Communications and Mobile Computing

Self Cite

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Nowadays, traffic congestion and increasing road accidents have become a major concern for both developed and developing countries. To overcome this challenge, an internet of things- (IoT-) based Vehicular Ad Hoc Network (VANET) system is proposed in which vehicles interact with other vehicles and infrastructure. These self-organized ad hoc vehicle networks not only boost traffic safety but also enhances the efficiency of traffic management systems. The VANET systems are beneficial in busy locations, where improved data dissemination protocols are used to categorize a vehicle’s transmission. However, the performance of these VANETs is also hampered by network splits and insufficient connections. Under these situations, the proposed simulation model reduces broadcast storms by minimizing redundancies, which is equally beneficial for both rural and urban settings. The suggested Next Forwarder Vehicle (NFV) protocol is based on three factors: position, distance, and orientation. Moreover, the DDP4V technique is used to analyse each of these features. Results indicate that DDP4V is compatible with 96% of all traffic scenarios and simulation durations. It can transport data packets 60% faster due to its broadcast suppression capabilities. Also, in comparison to AID and DBRS, DDP4V has fewer dispersed packets, which results into reduced retransmissions. For 200 automobiles/km2, all these techniques accomplish 35–40% of the needed cars. However, the coverage also faces some restrictions since data packets only reach vehicles on the same side as the originating vehicle. Similarly, DDP4V delivers 90% coverage for 400 vehicles/km2, which is 30% greater than prior techniques. It is observed that the proposed protocol reduces broadcast storms by employing a waggon wheel to choose the next forwarding vehicle. In high-traffic areas, it outperforms standard techniques. Similarly, it employs a patchwork of vehicles outside of the impacted region to convey data. The industrial IoT-based VANETs provide an effective tool to monitor and control traffic besides reducing the number of traffic accidents.

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An Optimization Technique for Intrusion Detection of Industrial Control Network Vulnerabilities Based on BP Neural Network

Cited by 5 publications

References 16 publications

Aggregation-Based Dynamic Channel Bonding to Maximise the Performance of Wireless Local Area Networks (WLAN)

Aggregation-Based Dynamic Channel Bonding to Maximise the Performance of Wireless Local Area Networks (WLAN)

Performance Optimization of Industrial Supply Chain Using Artificial Intelligence

Simulation of IoT-based Vehicular Ad Hoc Networks (VANETs) for Smart Traffic Management Systems

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