Adaptive AI-Driven Security, Optimization, and Resource Management Frameworks for Internet of Medical Things and Smart Cloud-Integrated Environments
Keywords:
IoMT security, intrusion detection, cloud computing, metaheuristic optimizationAbstract
The rapid evolution of the Internet of Medical Things (IoMT), smart cities, and cloud-integrated infrastructures has introduced unprecedented opportunities for enhancing healthcare delivery, urban management, and computational efficiency. However, this technological advancement has simultaneously expanded the attack surface, making these systems increasingly vulnerable to sophisticated cyber threats. This research presents a comprehensive, integrated exploration of adaptive artificial intelligence-driven frameworks for cybersecurity, optimization, and resource management in IoMT and smart cloud environments. Drawing upon recent developments in deep learning, support vector machines, metaheuristic optimization, and hybrid scheduling algorithms, the study synthesizes a unified perspective that bridges the domains of intrusion detection, feature selection, load balancing, and intelligent resource allocation. The paper critically examines the limitations of traditional security mechanisms and proposes a multi-layered architecture that incorporates real-time anomaly detection, dynamic scheduling, and energy-efficient optimization strategies. Emphasis is placed on hybrid approaches combining convolutional neural networks, long short-term memory networks, and optimization algorithms such as particle swarm optimization, gray wolf optimization, and whale optimization. Furthermore, the study evaluates the role of knowledge graph embedding techniques and reinforcement learning in enhancing predictive capabilities and system resilience. The findings highlight the importance of integrating security and optimization frameworks to achieve robust, scalable, and efficient IoMT ecosystems. The research contributes to the academic discourse by providing a deeply theoretical and analytically rigorous framework, identifying critical gaps in current methodologies, and proposing directions for future research in adaptive, intelligent, and secure distributed systems.
References
Papaioannou M et al. (2022) A survey on security threats and countermeasures in Internet of Medical Things (IoMT). Transactions on Emerging Telecommunications Technologies 33(6):e4049
Quadar N, Chehri A, Jeon G, Hassan MM, Fortino G (2022) Cybersecurity issues of IoT in ambient intelligence (Am I) environment. IEEE Internet of Things Magazine 5(3):140–145
Rizi MHP, Seno SAH (2022) A systematic review of technologies and solutions to improve security and privacy protection of citizens in the smart city. Internet of Things, p 100584
Bajao NA, Sarucam J-A (2023) Threats detection in the Internet of Things using convolutional neural networks, long short-term memory, and gated recurrent units. Mesopotamian journal of cybersecurity 2023:22–29
Bozorgi E, Soleimani S, Alqaiidi SK, Arabnia HR, Kochut K (2024) Subgraph2vec: a random walk-based algorithm for embedding knowledge graphs. arXiv preprint arXiv:2405.02240
Kandel MA, Rizk FH, Hongou L, Zaki AM, Khan H, El-Kenawy E-SM (2023) Evaluating the efficacy of deep learning architectures in predicting traffic patterns for smart city development. Full Length Article 6(2):26–6–35
Shoeibi M, Oskouei AE, Kaveh M (2024) A novel six-dimensional chimp optimization algorithm—deep reinforcement learning-based optimization scheme for reconfigurable intelligent surface-assisted energy harvesting in batteryless IoT networks. Future Internet 16(12):460
Aswini J, Yamini B, Jatothu R, Nayaki KS, Nalini M (2022) An efficient cloud-based healthcare services paradigm for chronic kidney disease prediction application using boosted support vector machine. Concurrency and Computation: Practice and Experience 34(10):e6722
Ponmalar A, Dhanakoti V (2022) An intrusion detection approach using ensemble support vector machine based chaos game optimization algorithm in big data platform. Applied Soft Computing 116:108295
Masoudi-Sobhanzadeh Y, Emami-Moghaddam S (2022) A real-time IoT-based botnet detection method using a novel two-step feature selection technique and the support vector machine classifier. Computer Networks 217:109365
Tang L, Tian Y, Wang X, Pardalos PM (2023) A simple and reliable instance selection for fast training support vector machine: valid border recognition. Neural Networks 166:379–395
Mohammad RMA (2022) An enhanced multiclass support vector machine model and its application to classifying file systems affected by a digital crime. Journal of King Saud University-Computer and Information Sciences 34(2):179–190
Chui KT, Gupta BB, Chaurasia P, Arya V, Almomani A, Alhalabi W (2023) Three-stage data generation algorithm for multiclass network intrusion detection with highly imbalanced dataset. International Journal of Intelligent Networks 4:202–210
Agarwal G et al. (2023) Multiprocessor task scheduling using multi-objective hybrid genetic algorithm in fog–cloud computing. Knowledge-Based Systems
Chiang ML et al. (2023) Improvement of tasks scheduling algorithm based on load balancing candidate method under cloud computing environment. Expert Systems with Applications
Devaraj AFS et al. (2020) Hybridization of firefly and improved multi-objective particle swarm optimization algorithm for energy efficient load balancing in cloud computing environments. Journal of Parallel and Distributed Computing
He J et al. (2023) Hybrid teaching–learning-based optimization for workflow scheduling in cloud environment. IEEE Access
Jaafari A et al. (2022) Swarm intelligence optimization of the group method of data handling using the cuckoo search and whale optimization algorithms to model and predict landslides. Applied Soft Computing
Jena UK et al. (2022) Hybridization of meta-heuristic algorithm for load balancing in cloud computing environment. Journal of King Saud University-Computer and Information Sciences
Li C et al. (2022) Optimal data placement strategy considering capacity limitation and load balancing in geographically distributed cloud. Future Generation Computer Systems
Li C et al. (2022) Fault-tolerant scheduling and data placement for scientific workflow processing in geo-distributed clouds. Journal of Systems and Software
Li B et al. (2022) Multi-objective sparrow search algorithm: A novel algorithm for solving complex multi-objective optimisation problems. Expert Systems with Applications
Miao Z et al. (2021) A discrete PSO-based static load balancing algorithm for distributed simulations in a cloud environment. Future Generation Computer Systems
Najm M et al. (2022) Towards cost-aware VM migration to maximize the profit in federated clouds. Future Generation Computer Systems
Sharma M et al. (2020) An artificial neural network based approach for energy efficient task scheduling in cloud data centers. Sustainable Computing: Informatics and Systems
Kaushik B, Sharma R, Dhama K, Chadha A, Sharma S (2023) Performance evaluation of learning models for intrusion detection system using feature selection. Journal of Computer Virology and Hacking Techniques
Subramani S, Selvi M (2023) Multi-objective PSO based feature selection for intrusion detection in IoT based wireless sensor networks. Optik 273:170419
Al-Saleh A (2023) A balanced communication-avoiding support vector machine decision tree method for smart intrusion detection systems. Scientific Reports 13(1):9083
El-Kenawy E-SM, Khodadadi N, Mirjalili S, Abdelhamid AA, Eid MM, Ibrahim A (2024) Greylag goose optimization: nature-inspired optimization algorithm. Expert Systems with Applications 238:122147
Towfek S, Khodadadi N, Abualigah L, Rizk FH (2024) AI in higher education: insights from student surveys and predictive analytics using PSO-guided WOA and linear regression. Journal of Artificial Intelligence in Engineering Practice 1(1):1–17
Pan H, Chen S, Xiong H (2023) A high-dimensional feature selection method based on modified gray wolf optimization. Applied Soft Computing 135:110031
Nayak J, Swapnarekha H, Naik B, Dhiman G, Vimal S (2023) 25 years of particle swarm optimization: flourishing voyage of two decades. Archives of Computational Methods in Engineering 30(3):1663–1725
H. K. Krishnamurthy Sukumar, "A Novel Hybrid Grey Wolf Whale Optimization for Effectual Job Scheduling and Resource Distribution in Dynamic Cloud Computing," 2025 International Conference on Sustainability, Innovation & Technology (ICSIT), Nagpur, India, 2025, pp. 1-6, doi: 10.1109/ICSIT65336.2025.11293898.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Arjun Mehta
This work is licensed under a Creative Commons Attribution 4.0 International License.
Individual articles are published Open Access under the Creative Commons Licence: CC-BY 4.0.
