Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures
Abstract In this paper, cyber-attacks in IOT-WSN are detected through proposed optimized-Neural Network algorithms such as (i) Equilibrium Optimizer Neural Network (EO-NN), (ii) Particle Swarm Optimization (PSO-NN), (iii) Single Candidate Optimizer Neural Network (SCO-NN) and (iv) Single Candidate O...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-12-01
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| Series: | Journal of Cloud Computing: Advances, Systems and Applications |
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| Online Access: | https://doi.org/10.1186/s13677-024-00722-9 |
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| author | S. Nandhini A. Rajeswari N. R. Shanker |
| author_facet | S. Nandhini A. Rajeswari N. R. Shanker |
| author_sort | S. Nandhini |
| collection | DOAJ |
| description | Abstract In this paper, cyber-attacks in IOT-WSN are detected through proposed optimized-Neural Network algorithms such as (i) Equilibrium Optimizer Neural Network (EO-NN), (ii) Particle Swarm Optimization (PSO-NN), (iii) Single Candidate Optimizer Neural Network (SCO-NN) and (iv) Single Candidate Optimizer Long Short-Term Memory (SCO-LSTM) with different connecting, hidden neural network layers and threat intelligence data. The proposed algorithms detect the attacker node, which frequently changes the behaviour such as attacker node/ normal node. Existing IDS system detects the attacks in WSN and unable to detect the changing behavior attacker nodes in IOT-WSN. The behaviour of attacker node changes from normal behaviour to attacker behaviour due to nodes connected to internet continuously. The classification accuracy rates of proposed SCO-LSTM algorithm without and with threat intelligence are about 99.7% and 99.89%, respectively. |
| format | Article |
| id | doaj-art-4cca3a7cc06145f99ab2dd1db4fae27c |
| institution | OA Journals |
| issn | 2192-113X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Cloud Computing: Advances, Systems and Applications |
| spelling | doaj-art-4cca3a7cc06145f99ab2dd1db4fae27c2025-08-20T02:31:41ZengSpringerOpenJournal of Cloud Computing: Advances, Systems and Applications2192-113X2024-12-0113112110.1186/s13677-024-00722-9Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architecturesS. Nandhini0A. Rajeswari1N. R. Shanker2Department of Electronics and Communication Engineering, Dhanalakshmi College of EngineeringDepartment of Computer Science and Engineering, Velammal Engineering CollegeDepartment of Computer Science and Engineering, Aalim Muhammed Salegh College of EngineeringAbstract In this paper, cyber-attacks in IOT-WSN are detected through proposed optimized-Neural Network algorithms such as (i) Equilibrium Optimizer Neural Network (EO-NN), (ii) Particle Swarm Optimization (PSO-NN), (iii) Single Candidate Optimizer Neural Network (SCO-NN) and (iv) Single Candidate Optimizer Long Short-Term Memory (SCO-LSTM) with different connecting, hidden neural network layers and threat intelligence data. The proposed algorithms detect the attacker node, which frequently changes the behaviour such as attacker node/ normal node. Existing IDS system detects the attacks in WSN and unable to detect the changing behavior attacker nodes in IOT-WSN. The behaviour of attacker node changes from normal behaviour to attacker behaviour due to nodes connected to internet continuously. The classification accuracy rates of proposed SCO-LSTM algorithm without and with threat intelligence are about 99.7% and 99.89%, respectively.https://doi.org/10.1186/s13677-024-00722-9WSN attackIOT-WSN attack- false data injectionBrute forceHybrid brute forceIDS |
| spellingShingle | S. Nandhini A. Rajeswari N. R. Shanker Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures Journal of Cloud Computing: Advances, Systems and Applications WSN attack IOT-WSN attack- false data injection Brute force Hybrid brute force IDS |
| title | Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures |
| title_full | Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures |
| title_fullStr | Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures |
| title_full_unstemmed | Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures |
| title_short | Cyber attack detection in IOT-WSN devices with threat intelligence using hidden and connected layer based architectures |
| title_sort | cyber attack detection in iot wsn devices with threat intelligence using hidden and connected layer based architectures |
| topic | WSN attack IOT-WSN attack- false data injection Brute force Hybrid brute force IDS |
| url | https://doi.org/10.1186/s13677-024-00722-9 |
| work_keys_str_mv | AT snandhini cyberattackdetectioniniotwsndeviceswiththreatintelligenceusinghiddenandconnectedlayerbasedarchitectures AT arajeswari cyberattackdetectioniniotwsndeviceswiththreatintelligenceusinghiddenandconnectedlayerbasedarchitectures AT nrshanker cyberattackdetectioniniotwsndeviceswiththreatintelligenceusinghiddenandconnectedlayerbasedarchitectures |