Abstract
Internet of Things (IoT) is a network of interconnected, web-connected devices that can collect and transmit data across a wireless network without requiring human contact. People feel more at ease and relieved as a result of the Internet of Things. IoT devices give users the freedom to produce reports without constraints and access information even in remote locations. Additionally, they accurately direct people with wise judgements using communication technologies, as was already mentioned. Preprocessing is necessary since many linked devices gather a lot of raw sensed data. However, it only becomes something important since IoT devices require sufficient resources for edge computing. The essential tools for information inference in edge computing are AI-based algorithms. Additionally, the sensed data gathered by IoT applications is typically unstructured and requires further analysis, where AI-based models assist in extracting pertinent data. Additionally, there is a possibility for malicious arracks when data is transmitted from device to device. The use of Artificial Intelligence (AI) approaches to improve the security of Internet of Things (IoT) systems is explored in this chapter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Chander B, Pal S, De D, Buyya R (2022) Artificial intelligence-based internet of things for industry 5.0. In: Artificial intelligence-based internet of things systems, pp 3–45
Khilar R et al (2022) Artificial intelligence-based security protocols to resist attacks in internet of things. Wirel Commun Mob Comput 2022
Lin J, Yu W, Zhang N, Yang X, Zhang H, Zhao W (2017) A survey on internet of things: architecture, enabling technologies, security and privacy, and applications. IEEE Internet Things J 4(5):1125–1142
Tewari A, Gupta BB (2020) Security, privacy and trust of different layers in internet-of-things (IoTs) framework. Futur Gener Comput Syst 108:909–920
Yang Y, Wu L, Yin G, Li L, Zhao H (2017) A survey on security and privacy issues in internet-of-things. IEEE Internet Things J 4(5):1250–1258
Awotunde JB, Misra S (2022) Feature extraction and artificial intelligence-based intrusion detection model for a secure internet of things networks. In: Illumination of artificial intelligence in cybersecurity and forensics. Springer, pp 21–44
Mishra S, Tyagi AK (2022) The role of machine learning techniques in internet of things-based cloud applications. In: Artificial intelligence-based internet of things systems, pp 105–135
Gao X, Li Q, Liu F (2021) Research on the new normal technology and application of artificial intelligence in the internet of things. J Phys: Conf Ser 42062
Prasad M, Tripathi S, Dahal K (2020) Unsupervised feature selection and cluster center initialization based arbitrary shaped clusters for intrusion detection. Comput Secur 99:102062
Pal S, De D, Buyya R (2022) Artificial intelligence-based internet of things systems. Springer
Dulhare UN, Rasool S Harnessing the IoT-based activity trackers and sensors for cognitive assistance in COVID-19. In: Principles and applications of socio-cognitive and affective computing. IGI Publisher, pp 64–92
Geetha S, Dulhare UN, Sivatha Sindhu SS (2018) Intrusion detection using NBHoeffding rule based decision tree for wireless sensor networks. In: 2018 second international conference on advances in electronics, computers and communications (ICAECC), Bangalore, India, pp 1–5. https://doi.org/10.1109/ICAECC.2018.8479483
Dulhare UN, Rasool S IOT evolution and security challenges in cyber space: IOT security. In: Countering cyber attacks and preserving the integrity and availability of critical systems. IGI Publisher, pp 99–127
Seng KP, Ang LM, Ngharamike E (2022) Artificial intelligence internet of things: a new paradigm of distributed sensor networks. Int J Distrib Sens Netw 18(3):15501477211062836
Sasikumar A, Ravi L, Kotecha K, Saini JR, Varadarajan V, Subramaniyaswamy V (2022) Sustainable smart industry: a secure and energy efficient consensus mechanism for artificial intelligence enabled industrial internet of things. Comput Intell Neurosci 2022
Rasool S, Dulhare UN (2018) Evolution of indian railways through IOT. In: Innovative applications of big data in the railway industry, chap 12. IGI Global, pp 269–290
Nirmala P, Ramesh S, Tamilselvi M, Ramkumar G, Anitha G (2022) An artificial intelligence enabled smart industrial automation system based on internet of things assistance. In: 2022 international conference on advances in computing, communication and applied informatics (ACCAI), pp 1–6
Krishnan R, Rajpurkar P, Topol EJ (2022) Self-supervised learning in medicine and healthcare. Nat Biomed Eng 1–7
Shah D, Singh A, Prasad SS (2022) Sentimental analysis using supervised learning algorithms. In: 2022 3rd international conference on computation, automation and knowledge management (ICCAKM), pp 1–6
Rajapaksha S, Kalutarage H, Al-Kadri MO, Petrovski A, Madzudzo G, Cheah M (2023) Ai-based intrusion detection systems for in-vehicle networks: a survey. ACM Comput Surv 55(11):1–40
Donalek C (2011) Supervised and unsupervised learning. In: Astronomy colloquia, USA, p 8
Sagar R, Jhaveri R, Borrego C (2020) Applications in security and evasions in machine learning: a survey. Electronics (Basel) 9(1):97
Dulhare UN, Ali H (2023) Underwater human detection using faster R-CNN with data augmentation. Mater Today: Proc 80:1940–1945. ISSN 2214-7853
Ullah I, Mahmoud QH (2021) Design and development of a deep learning-based model for anomaly detection in IoT networks. IEEE Access 9:103906–103926
Houssein EH, Helmy BE, Rezk H, Nassef AM (2021) An enhanced Archimedes optimization algorithm based on local escaping operator and orthogonal learning for PEM fuel cell parameter identification. Eng Appl Artif Intell 103:104309
Hassanien AE, Kilany M, Houssein EH, AlQaheri H (2018) Intelligent human emotion recognition based on elephant herding optimization tuned support vector regression. Biomed Signal Process Control 45:182–191
Ismaeel AAK, Elshaarawy IA, Houssein EH, Ismail FH, Hassanien AE (2019) Enhanced elephant herding optimization for global optimization. IEEE Access 7:34738–34752
Houssein EH, Mahdy MA, Fathy A, Rezk H (2021) A modified marine predator algorithm based on opposition based learning for tracking the global MPP of shaded PV system. Expert Syst Appl 183:115253
Hamad A, Houssein EH, Hassanien AE, Fahmy AA (2018) Hybrid grasshopper optimization algorithm and support vector machines for automatic seizure detection in EEG signals. In: The international conference on advanced machine learning technologies and applications (AMLTA2018). Springer International Publishing, pp 82–91
Houssein EH, Mahdy MA, Shebl D, Manzoor A, Sarkar R, Mohamed WM (2022) An efficient slime mould algorithm for solving multi-objective optimization problems. Expert Syst Appl 187:115870
Houssein EH, Abdelminaam DS, Hassan HN, Al-Sayed MM, Nabil E (2021) A hybrid barnacles mating optimizer algorithm with support vector machines for gene selection of microarray cancer classification. IEEE Access 9:64895–64905
Hamad A, Houssein EH, Hassanien AE, Fahmy AA (2016) Feature extraction of epilepsy EEG using discrete wavelet transform. In: 2016 12th international computer engineering conference (ICENCO). IEEE, pp 190–195
Shaban H, Houssein EH, Pérez-Cisneros M, Oliva D, Hassan AY, Ismaeel AA, AbdElminaam DS, Deb S, Said M (2021) Identification of parameters in photovoltaic models through a Runge Kutta optimizer. Mathematics 9(18):2313
Abdelminaam DS, Said M, Houssein EH (2021) Turbulent flow of water-based optimization using new objective function for parameter extraction of six photovoltaic models. IEEE Access 9:35382–35398
Houssein EH, Hassaballah M, Ibrahim IE, AbdElminaam DS, Wazery YM (2022) An automatic arrhythmia classification model based on improved marine predators algorithm and convolutions neural networks. Expert Syst Appl 187:115936
Houssein EH, Neggaz N, Hosney ME, Mohamed WM, Hassaballah M (2021) Enhanced Harris hawks optimization with genetic operators for selection chemical descriptors and compounds activities. Neural Comput Appl 33:13601–13618
Ahmed MM, Houssein EH, Hassanien AE, Taha A, Hassanien E (2018) Maximizing lifetime of wireless sensor networks based on whale optimization algorithm. In: Proceedings of the international conference on advanced intelligent systems and informatics 2017. Springer International Publishing, pp 724–733
Houssein EH, Sayed A (2023) Dynamic candidate solution boosted beluga whale optimization algorithm for biomedical classification. Mathematics 11(3):707
Alloghani M, Al-Jumeily D, Mustafina J, Hussain A, Aljaaf AJ (2020) A systematic review on supervised and unsupervised machine learning algorithms for data science. In: Supervised and unsupervised learning for data science, pp 3–21
Ahmad Z et al (2021) Anomaly detection using deep neural network for IoT architecture. Appl Sci 11(15):7050
de Assis MVO, Carvalho LF, Rodrigues JJPC, Lloret J, Proença ML Jr (2020) Near real-time security system applied to SDN environments in IoT networks using convolutional neural network. Comput Electr Eng 86:106738
Zhao Z, Liu H (2007) Spectral feature selection for supervised and unsupervised learning. In: Proceedings of the 24th international conference on machine learning, pp 1151–1157
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Goswami, R.C., Joshi, H., Gautam, S. (2023). Artificial Intelligence-Based Internet of Things Security. In: Dulhare, U.N., Houssein, E.H. (eds) Machine Learning and Metaheuristics: Methods and Analysis. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-6645-5_9
Download citation
DOI: https://doi.org/10.1007/978-981-99-6645-5_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6644-8
Online ISBN: 978-981-99-6645-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)