Published Papers

Volume 33 - Issue 1 (Regular Issue)
Transactions Papers

Enhanced multi‑level intrusion detection system (ML‑IDS) for secure cloud and fog computing environments

Anwar Basha H, Deepak R, Thanuja K, Babu M, and Soumyalatha Naveen
Pages: 1-10Published: 26 Jun 2026
DOI: 10.33430/V33N1THIE-2025-0008
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Anwar Basha H, Deepak R, Thanuja K, Babu M, and Soumyalatha Naveen, Enhanced multi‑level intrusion detection system (ML‑IDS) for secure cloud and fog computing environments, HKIE Transactions, Vol. 33, No. 1 (Regular Issue), Article THIE-2025-0008.R2, 2026, 10.33430/V33N1THIE-2025-0008

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Abstract:

Cloud computing, with its highly scalable and on‑demand computing, allows users access to large‑scale platforms. As a multi‑tenant environment, this is vulnerable to many cyberattacks. Robust security requires abundant computational resources in return for losing performance. The study proposes a Fog‑Assisted adaptive Security Monitoring System (FASMS) where cloud computing and fog computing are integrated for the purposes of efficient threat detection and mitigation. The approach uses the Enhanced Adaptive Intrusion Detection Algorithm (EAIDA) for dynamic real‑time security policy adjustment according to the rapidly assessable threats for optimised resource use without compromising security. The proposed system offloads initial threat processing to fog nodes, reducing the omputational burden on cloud servers and improving response times. Experimental results have shown that the FASMS enhances the efficiency of security monitoring by 27.3%, reduces latency by 19.6%, and optimises resource allocation to ensure improved performance in cloud environments. The study has shown that fog computing has the potential to strengthen cloud security while maintaining system efficiency.

Keywords:

cloud computing, fog computing, encryption, virtual machine, security

Reference List:

[1] Fuhong lin, Yutong Zhou, Ilsun You et al , “The Internet of Things (IoT) era has arrived with the advancement of the Internet and mobile technologies”, Special Section on Collaboration for Internet of Things, IEEE Access,2019.
[2] Sangeetha, SK B., C. Selvarathi, Sandeep Kumar Mathivanan, Jaehyuk Cho, and Sathishkumar Veerappampalayam Easwaramoorthy, "Secure Healthcare Access Control System (SHACS) for Anomaly Detection and Enhanced Security in Cloud‑Based Healthcare Applications." IEEE Access,2024.
[3] Hongchen Wu, Mingyang Li & Huaxiang Zhang , “Enabling Smart Anonymity Scheme for Security Collaborative Enhancement in Location‑Based Services”, IEEE. Translations and content mining,2019.
[4] Junaid Chaudhry, Kashif Saleem, Rafiqul Islam & Ali Selamat, “AZSPM꞉ Autonomic Zero‑Knowledge Security Provisioning Model for Medical Control Systems in Fog Computing Environments”, IEEE 42nd Conference on Local Computer Networks Workshops,2017.
[5] Lingjuan Lyu, Jiong Jin, Sutharsan Rajasegarar, “Fog‑Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering “,IEEE Internet of things journal, vol. 4, no. 5, october,2017.
[6] Luca Cerina, Sara Notargiacomo, Matteo Greco & Luca Paccani, “A Fog‑Computing architecture for Preventive Healthcare and Assisted Living in Smart Ambients”, IEEE,2017.
[ 7 ] D h a y a , R . , S . K . B . S a n g e e t h a , a n d A . Sharma,"Improved performance of two server architecture in multiple client environment Proceedings of the 2017 4th International Conference on Advanced Computing And
Communication Systems (ICACCS) January ,Coimbatore." 1‑4,2017.
[8] Rehmat Ullah, Muhammad Atif Ur Rehman & Byung Seo Kim, “Design and Implementation of an Open Source Framework and Prototype For Named Data Networking‑Based Edge Cloud Computing System”, IEEE. Translations and content mining,Volume 7,2019.
[9] Sangeetha, S. K. B., K. Veningston, Vanlin Sathya, and R. Kanthavel ,"Design of a novel privacy preservation based cyber security system framework for secure medical data transactions in cloud storage." In Intelligent Edge Computing for Cyber Physical Applications, pp. 35‑43. Academic Press,2023.
[10] Sandeep K.Sood & Isha Mahajan, “A Fog‑Based Healthcare Framework for Chikungunya “, IEEE Internet of Things Journal, Vol. 5, No. 2, April,2018.
[11] Sheng Zhou, Zhiyuan Jiang & Zhisheng Niu, “Exploiting Moving Intelligence꞉ Delay‑Optimized Computation Offloading in Vehicular Fog Networks”, IEEE Communication Magazine, May,2019.
[12] Songqing Chen, Tao Zhang & Weisong Shi, “ Fog Computing”, IEEE Internet Computing, Volume 21, Issue 2,2017.
[13] Thaha Muhammed, Rashid Mehmood, Aiiad Albeshri & Iyad Katib , “UbeHealth꞉ A Personalized Ubiquitous Cloud and Edge‑Enabled Networked Healthcare System for Smart Cities”, Special Section On Big Data Learning And Discovery, IEEE Access,2018.
[14] Xuyun Zhang, Yuan Yuan, Zhili Zhou,Shancang Li,Lianyong Qi & Deepak Puthal, “Intrusion Detection and Prevention in Cloud, Fog, and Internet of Things”, Security and Communication Networks,Volume 2019, Article ID 4529757,2019.
[15] Zhenyu Zhuo, Pengju Liu, Junhao Feng, Yan Zhang, Shahid Mumtaz & Jonathan rodriguez 2019, “Computation Resource Allocation and Task Assignment Optimization in Vehicular Fog Computing꞉ A Contract‑Matching Approach”, IEEE transactions on vehicular technology, vol. 68, no. 4, April, 2019.
[16] Shirafkan, M., Shahidinejad, A. & Ghobaei‑Arani, M. “An Intrusion Detection System using Deep Cellular Learning Automata and Semantic Hierarchy for Enhancing RPL Protocol Security”. Cluster Comput 26, 2443–2461, 2023.
[17] Abedi, S., Ghobaei‑Arani, M., Khorami, E., & Mojarad, M. “Dynamic Resource Allocation Using Improved Firefly Optimization Algorithm in Cloud Environment”. Applied Artificial Intelligence, 36(1), 2022.
[18] Shirafkan, M., Shahidienjad, A. & Ghobaei‑Arani, M. “An autonomous intrusion detection system for the RPL protocol”. Peer‑to‑Peer Netw. Appl. 15, 484–502, 2022.
[19] Mohsen Ghorbian, Mostafa Ghobaei‑Arani, Rohollah Asadolahpour‑Karimi, “Function Placement Approaches in Serverless Computing꞉ A Survey”,Journal of Systems Architecture, Volume 157, 103291, ISSN 1383‑7621,2024.
[20] Jazayeri, F., Shahidinejad, A. & Ghobaei‑Arani, M. “A latency‑aware and energy‑efficient computation offloading in mobile fog computing꞉ a hidden Markov model‑based approach”. J Supercomput 77, 4887–4916 ,2021.
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