Enhancing Internet of Things Intrusion Detection Using Artificial Intelligence
Source abstract
Abstract
Escalating cyber security threats and the increased use of Internet of Things (IoT) devices require utilisation of the latest technologies available to supply adequate protection. The aim of Intrusion Detection Systems (IDS) ... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Network Security and Intrusion Detection · Internet of Things and AI · Smart Systems and Machine Learning
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (81)
Show source-provided references
1. Statista, “IoT connected devices worldwide 2019–2030, with forecasts from 2022 to 2030,” 2024. Accessed: May 11, 2024. [Online]. Available: https://www.statista.com/statistics/1183457/iot-connected-devices-worldwide
2. Agarwal · IoT for Sustainable Smart Cities and Society · 2022
3. Mohd · Enabling Technologies for Effective Planning and Management in Sustainable Smart Cities · 2023
4. Critical infrastructure awareness based on IoT context data10.1016/j.iot.2023.100855 ↗
5. Distributed ensemble method using deep learning to detect DDoS attacks in IoT networks
6. Review of deep learning: Concepts, CNN architectures, challenges, applications, future directions10.1186/s40537-021-00444-8 ↗
7. A two-phase random forest with differential privacy10.1007/s10489-022-04119-6 ↗
8. Research on intrusion detection based on an enhanced random forest algorithm
9. An explainable efficient flow-based industrial IoT intrusion detection system10.1016/j.compeleceng.2023.108732 ↗
10. Optimizing IoT intrusion detection system: Feature selection versus feature extraction in machine learning10.1186/s40537-024-00892-y ↗
11. Detection of botnet in IoT network through machine learning based optimized feature importance via ensemble models
12. Gupta · Distributed Denial of Service (DDoS) Attacks: Classification, Attacks, Challenges, and Countermeasures · 202110.1201/9781003107354 ↗
13. Label flipping attacks against Naive Bayes on spam filtering systems10.1007/s10489-020-02086-4 ↗
14. A novel evil twin MiTM attack through 802.11v protocol exploitation
15. Zero-day attack detection and prevention
16. Yang · Federated Learning · 2020
17. Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approach
18. Deep learning-enabled anomaly detection for IoT systems10.1016/j.iot.2022.100656 ↗
19. Feed-forward neural network for network intrusion detection
20. Long short-term memory with activation on gradient10.1016/j.neunet.2023.04.026 ↗
21. Knowledge graph random neural networks for recommender systems10.1016/j.eswa.2022.117120 ↗
22. An explainable deep learning-enabled intrusion detection framework in IoT networks10.1016/j.ins.2023.119000 ↗
23. Graph neural networks
24. Enhancing IoT network security through deep learning-powered intrusion detection system10.1016/j.iot.2023.100936 ↗
25. A controlled experiment on the impact of intrusion detection false alarm rate on analyst performance
26. Enhancing IoT intrusion detection system with modified E‐GraphSAGE: A graph neural network approach
27. An improved GraphSAGE to detect power system anomaly based on time-neighbor feature10.1016/j.egyr.2022.11.116 ↗
28. Graph-based vs. vector-based classification: A fair comparison
29. Hamdi · Applied Cryptography and Network Security · 2023 · 13905 · 532
30. Wei · Knowledge Science, Engineering and Management · 2023 · 43210.1007/978-3-031-40286-9_35 ↗
31. A new concatenated multigraph neural network for IoT intrusion detection10.1016/j.iot.2023.100818 ↗
32. Predictive and comparative analysis of LENET, ALEXNET and VGG-16 network architecture in smart behavior monitoring
33. Arslan · Accelerators for Convolutional Neural Networks · 2024
34. Classification of network security attack using KNN (K-Nearest Neighbour) and comparison of different attacks through different machine learning techniques
35. Intrusion detection system using feature extraction with machine learning algorithms in IoT10.3390/jsan12020029 ↗
36. Network-wide forwarding anomaly detection and localization in software defined networks
37. Enhancing intrusion detection in IoT communications through ML Model generalization with a new dataset (IDSAI)10.1109/ACCESS.2023.3292267 ↗
38. Du · Mobile Networks and Applications · 2022 · 27 · 43110.1007/s11036-021-01838-x ↗
39. Identification of network traffic intrusion using decision tree10.1155/2023/5997304 ↗
40. Intrusion detection framework for industrial Internet of Things using software defined network10.3390/su15119001 ↗
41. Ma · IEEE Internet Things · 2023 · 10 · 1252110.1109/JIOT.2023.3248259 ↗
42. Cross-layer federated learning for lightweight IoT intrusion detection systems10.3390/s23167038 ↗
43. Dependable federated learning for IoT intrusion detection against poisoning attacks10.1016/j.cose.2023.103381 ↗
44. IoT workload offloading efficient intelligent transport system in federated ACNN integrated cooperated edge‐cloud networks10.1186/s13677-024-00640-w ↗
45. An efficient network intrusion detection model based on temporal convolutional networks
46. Stacked sparse autoencoders that preserve the local and global feature structures for fault detection10.1177/01423312211037621 ↗
47. IoT intrusion detection model based on gated recurrent unit and residual network10.1007/s12083-023-01510-z ↗
48. Figen · Multimed. Tools Appl. · 2024 · 83 · 7235710.1007/s11042-024-18333-6 ↗
49. Deceiving post-hoc explainable AI (XAI) methods in network intrusion detection
50. Efficient intrusion detection toward IoT networks using cloud–edge collaboration10.1016/j.comnet.2023.109724 ↗
51. A survey on federated learning: The journey from centralized to distributed on-site learning and beyond10.1109/JIOT.2020.3030072 ↗
52. Federated learning-outcome prediction with multi-layer privacy protection10.1007/s11704-023-2791-8 ↗
53. From distributed machine to distributed deep learning: A comprehensive survey10.1186/s40537-023-00829-x ↗
54. A review of federated meta-learning and its application in cyberspace security
55. Yesi · Int. J. Inf. Secur. · 2024 · 23 · 161910.1007/s10207-023-00807-7 ↗
56. Deep convolutional autoencoder for energy-efficient smart health wearables in the era of big data
57. Mohd · Cluster Comput. · 2024
58. EIDM: Deep learning model for IoT intrusion detection systems10.1007/s11227-023-05197-0 ↗
59. Intrusion detection framework in IoT networks10.1007/s42979-023-01770-9 ↗
60. Securing IoT networks in cloud computing environments: A real‑time IDS10.1007/s11227-024-06021-z ↗
61. Enhancement of an IoT hybrid intrusion detection system based on fog-to-cloud computing
62. Detection and prevention of DDoS attacks on edge computing of IoT devices through reinforcement learning
63. Protecting IoT devices from security attacks using effective decision‐making strategy of appropriate features10.1007/s11227-023-05685-3 ↗
64. Sharma · Int. J. Inf. Tecnol. · 2024
65. Iqbal · Securing IoT Using Supervised Machine Learning in Artificial Intelligence of Things · 2023 · 3
66. FedProLs: Federated learning for IoT perception data prediction10.1007/s10489-022-03578-1 ↗
67. IoT-enabled sensors in automation systems and their security challenges in sensor networks
68. Performance analysis of distributed and federated learning models on private data10.1016/j.procs.2020.01.039 ↗
69. Ahsan · Cluster Comput. · 2024 · 27 · 836710.1007/s10586-024-04436-0 ↗
70. Jagarlamudi · J. Supercomput. · 2023 · 80 · 1051110.1007/s11227-023-05846-4 ↗
71. Federated learning with privacy-preserving and model IP-right-protection10.1007/s11633-022-1343-2 ↗
72. Privacy‑preserving federated learning based on partial low‑quality data10.1186/s13677-024-00618-8 ↗
73. A semi-decentralized security framework for connected and autonomous vehicles
74. An efficient approach for privacy preserving decentralized deep learning models based on secure multi-party computation10.1016/j.neucom.2020.10.014 ↗
75. Song · Collaborative Computing: Networking, Applications and Worksharing · 2024 · 375
76. Multi head self-attention gated graph convolutional network based multi‑attack intrusion detection in MANET10.1016/j.cose.2023.103526 ↗
77. Context aware hybrid network architecture for IoT with machine learning based intelligent gateway10.1007/s42979-023-01736-x ↗
78. Machine learning based low redundancy prediction model for IoT‑enabled Wireless Sensor Network10.1007/s42979-023-01898-8 ↗
79. Miller · Information Security, Privacy and Digital Forensics · 2023 · 213
80. DeepThink IoT: The strength of deep learning in Internet of Things10.1007/s10462-023-10513-4 ↗
81. Zhang · Multimedia Technology and Enhanced Learning · 2024 · 30810.1007/978-3-031-50580-5_27 ↗