Secure routing with multi-watchdog construction using deep particle convolutional model for IoT based 5G wireless sensor networks

Rajasoundaran, S.; Prabu, A.V.; Routray, Sidheswar; Malla, Prince Priya; Kumar, G. Sateesh; Mukherjee, Amrit; Qi, Yong

doi:10.1016/j.comcom.2022.02.004

Cited by 40 publications

(18 citation statements)

References 33 publications

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“…Priyanka et al [7] found that the past investment experience and years of investment experience of CPAs also affect the investment risk in future investment work, and the risk prevention measures recognized, learned, and accumulated in the experience can provide the basis for future investment work. Literature [8] based on the diversification of investment methods and the Internet environment, argues that CPA investment risks come from the level of information technology security, the level of system operation control, and the level of daily testing. Literature [9] based on big data cloud computing technology under the analysis of investment means, investment mode, and investment evidence relationship, argues that investment risk increases with the increase of insecurity factors existing in the network environment because big data cloud computers improve investment efficiency mainly with the help of the network environment.…”

Section: Related Workmentioning

confidence: 99%

5G Smart Sensor Network-Based e-Commerce Investment Risk Management System for SMEs

Tang

Yong-qing

2022

Journal of Sensors

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The rapid development of Internet technology in the new era has led to the prosperous development of the e-commerce industry, and more and more traditional retail enterprises are transforming into e-commerce enterprises in line with the development of the times to survive. Based on the relevant financial risk management theories, this paper designs an e-commerce investment risk management system for small and medium-sized enterprises based on the 5G intelligent sensor network, identify the financial risks arising from the e-commerce model, and takes appropriate countermeasures to manage the identified risks. For the optimal coverage problem of homogeneous terminals in the subnetwork of a smart sensing network, this paper introduces the concept of area coverage contribution, transforms the problem of selecting the optimal coverage subset in a large area into the problem of selecting the substrate particles, and organically combines the particle swarm algorithm in the bionic algorithm to consider the network survival period, area sensing coverage, and iteration cost for the hierarchical distributed large-scale IoT architecture. A minimum coverage subset dormancy scheduling algorithm based on homogeneous terminals is proposed. The simulation results are compared with the greedy algorithm and the multioptimized target task assignment algorithm, and it is demonstrated that this algorithm can consider multiple optimization objectives such as energy balance, scheduling cycle, timeout rate, network survival cycle, and system reliability and perform well in the case of large-scale deployment. Finally, an appropriate financial risk evaluation model is constructed to objectively evaluate the identified financial risks, and targeted financial risk control measures and suggestions are proposed based on four aspects: financing, investment, operation, and others.

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Section: Related Workmentioning

confidence: 99%

5G Smart Sensor Network-Based e-Commerce Investment Risk Management System for SMEs

Tang

Yong-qing

2022

Journal of Sensors

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“…Basic functions such as creating a TCP server and adding or deleting multiple clients are implemented through Qt's QTcpServer class. Control instructions are issued through TCP/IP protocol to interact with the hardware monitoring system, and the sampling rate and sampling time are set to read the client data [14]. At the same time, the module also has the function of detecting the client connection state.…”

Section: Communication Module Designmentioning

confidence: 99%

Construction of Intelligent Building Integrated Evaluation System Based on BIM Technology

Song¹

2022

Advances in Multimedia

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In order to alleviate the impact of the old bridge by the environment and its own life and the problem of increasing maintenance cost, the intelligent building integrated evaluation system based on BIM technology is proposed. Firstly, based on BIM technology, an all-weather hardware monitoring system is constructed by using multiple sensors laid on the bridge. The software communicates with the monitoring system through 5G public network and applies the unique advantages of deep neural network in classification to the assessment of the health status of old bridges with the help of the multiclassification convolutional neural network embedded in the software. The test results show that the preprocessed data is imported into the health diagnosis module for training, and the training accuracy reaches about 70%, and the loss curve is stable at about 0.5. Conclusion. The system meets the design requirements and solves the problem of difficult health diagnosis caused by long monitoring period and low efficiency of old bridges. The system has advantages of low difficulty in obtaining parameters, high precision, and accurate health assessment.

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“…As WSN distributes the data from various sender nodes via multi-path-routing procedures, the need for sender-originated IHFs is generated for the original frame sequence. In this process, each IHF holds a random number of fake data and other lookalike network credentials to thwart the attackers [ 47 , 48 ].…”

Section: Methodsmentioning

confidence: 99%

Interleaved Honeypot-Framing Model with Secure MAC Policies for Wireless Sensor Networks

Rajasoundaran

Maheswar

Muthuramalingam

et al. 2022

Sensors

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The Wireless Medium Access Control (WMAC) protocol functions by handling various data frames in order to forward them to neighbor sensor nodes. Under this circumstance, WMAC policies need secure data communication rules and intrusion detection procedures to safeguard the data from attackers. The existing secure Medium Access Control (MAC) policies provide expected and predictable practices against channel attackers. These security policies can be easily breached by any intelligent attacks or malicious actions. The proposed Wireless Interleaved Honeypot-Framing Model (WIHFM) newly implements distributed honeypot-based security mechanisms in each sensor node to act reactively against various attackers. The proposed WIHFM creates an optimal Wireless Sensor Network (WSN) channel model, Wireless Interleaved Honeypot Frames (WIHFs), secure hash-based random frame-interleaving principles, node-centric honeypot engines, and channel-covering techniques. Compared to various existing MAC security policies, the proposed model transforms unpredictable IHFs into legitimate frame sequences against channel attackers. Additionally, introducing WIHFs is a new-fangled approach for distributed WSNs. The successful development of the proposed WIHFM ensures resilient security standards and neighbor-based intrusion alert procedures for protecting MAC frames. Particularly, the proposed wireless honeypot methodology creates a novel idea of using honeypot frame traps against open wireless channel attacks. The development of a novel wireless honeypot traps deals with various challenges such as distributed honeypot management principles (node-centric honeypot, secretly interleaved-framing principles, and interleaving/de-interleaving procedures), dynamic network backbone management principles (On Demand Acyclic Connectivity model), and distributed attack isolation policies. This effort provides an effective wireless attack-trapping solution in dynamic WSNs. The simulation results show the advantage of the proposed WIHFM over the existing techniques such as Secure Zebra MAC (SZ-MAC), Blockchain-Assisted Secure-Routing Mechanism (BASR), and the Trust-Based Node Evaluation (TBNE) procedure. The experimental section confirms the proposed model attains a 10% to 14% superior performance compared to the existing techniques.

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Secure routing with multi-watchdog construction using deep particle convolutional model for IoT based 5G wireless sensor networks

Cited by 40 publications

References 33 publications

5G Smart Sensor Network-Based e-Commerce Investment Risk Management System for SMEs

5G Smart Sensor Network-Based e-Commerce Investment Risk Management System for SMEs

Construction of Intelligent Building Integrated Evaluation System Based on BIM Technology

Interleaved Honeypot-Framing Model with Secure MAC Policies for Wireless Sensor Networks

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