Authors:
M. Hafiz Yusoff,Belal alifan,Waheed Ali H. M. Ghanem,Syarilla Iryani Ahmad Saany,Julaily Aida Jusoh,Yousef A. Baker El-Ebiary,DOI NO:
https://doi.org/10.26782/jmcms.2026.01.00001Keywords:
Internet of Things (IoT),Security Solutions,Authentication,Intrusion Detection,Data Encryption,Cloud Computing,Abstract
Introduction: The widespread adoption of Internet of Things (IoT) devices has transformed multiple industries, enhancing operational efficiency and convenience. However, the rapid expansion of IoT ecosystems also brings forth significant security challenges. Traditional security frameworks often fail to adequately protect these systems due to their large scale, diversity, and limited resources. In response, cloud-based security solutions have emerged as a promising alternative, offering centralized management, advanced authentication techniques, and real-time threat monitoring. Problem Statement: IoT environments are vulnerable to various security risks, including unauthorized access, data breaches, and device manipulation. Existing security mechanisms often fall short when it comes to defending against sophisticated cyber-attacks targeting IoT devices and networks. The resource-constrained nature of many IoT devices further limits the implementation of robust local security measures. As a result, there is an urgent need for effective, cloud-based security solutions designed specifically for the unique demands of IoT systems. Objective: This research aims to explore the effectiveness of cloud-based security solutions in mitigating the security challenges faced by IoT environments and devices. The study focuses on evaluating the performance of cloud-based authentication mechanisms, intrusion detection systems, and encryption techniques in strengthening the security and privacy of IoT ecosystems. Methodology: A comprehensive approach is employed, combining a literature review, case studies, and empirical research to assess the current landscape of IoT security in smart environments. Data collection includes unstructured interviews with industry experts and stakeholders, offering insights into current practices and emerging security trends. The research framework incorporates threat modeling, risk assessments, and the development of proactive security strategies. Results: Initial findings indicate that cloud-based security solutions offer several benefits for protecting IoT environments and devices. Centralized management enhances integration and scalability, while advanced authentication methods, such as multi-factor and biometric authentication, improve access control. Real-time threat detection and response capabilities further bolster security by enabling timely interventions to prevent breaches and attacks. Conclusion: Cloud-based security solutions present a highly effective approach to addressing the unique security concerns of IoT environments and devices. By leveraging the scalability, flexibility, and computational power of cloud platforms, organizations can enhance the resilience of their IoT deployments against evolving cyber threats. However, further research is needed to optimize cloud-based security tools to better serve diverse IoT applications and use cases.Refference:
I. A. Greeni, et al. “BrainLang DL: A Deep Learning Approach to FMRI for Unveiling Neural Correlates of Language across Cultures” International Journal of Advanced Computer Science and Applications (IJACSA), 15(6), 2024. 10.14569/IJACSA.2024.01506114
II. Ahmad Saany, S. I., et al. “Exploitation of a Technique in Arranging an Islamic Funeral.” Proceedings of the 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), IEEE, 2021, pp. 1–8. 10.1109/ICSCEE50312.2021.9498224
III. Ali, M. A., and M. S. Hossain. “Cloud-Assisted Privacy-Preserving Data Integrity Verification Scheme for IoT Devices.” IEEE Internet of Things Journal, vol. 8, no. 12, 2021, pp. 10177–10186. 10.1109/JIOT.2021.3113780
IV. Ali, S. A., M. Ansari, and M. Alam. “Resource Management Techniques for Cloud-Based IoT Environment.” Internet of Things (IoT) Concepts and Applications, Springer, 2020, pp. 63–87. 10.1007/978-3-030-33596-0_4
V. Alrawais, A., A. Alhothaily, and C. Hu. “Secure and Lightweight Data Sharing Scheme for IoT Devices in Cloud Computing Environments.” IEEE Internet of Things Journal, vol. 10, no. 1, 2023, pp. 580–587. 10.1109/JIOT.2022.3147475
VI. Al-Sammarraie, N. A., Y. M. H. Al-Mayali, and Y. A. Baker El-Ebiary. “Classification and Diagnosis Using Back Propagation Artificial Neural Networks (ANN).” Proceedings of the International Conference on Smart Computing and Electronic Enterprise (ICSCEE), IEEE, 2018, pp. 1–5. 10.1109/ICSCEE.2018.8538383
VII. Altrad, et al. “Amazon in Business to Customers and Overcoming Obstacles.” Proceedings of the 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), IEEE, 2021, pp. 175–179. 10.1109/ICSCEE50312.2021.9498129
VIII. Anna Gustina Zainal, et al. “Cross-Cultural Language Proficiency Scaling using Transformer and Attention Mechanism Hybrid Model” International Journal of Advanced Computer Science and Applications (IJACSA), 15(6), 2024. 10.14569/IJACSA.2024.01506116
IX. Anushree A., et al. “Real-time Air Quality Monitoring in Smart Cities using IoT-enabled Advanced Optical Sensors” International Journal of Advanced Computer Science and Applications (IJACSA), 15(4), 2024. 10.14569/IJACSA.2024.0150487
X. Antonius, Franciskus, et al. “Incorporating Natural Language Processing into Virtual Assistants: An Intelligent Assessment Strategy for Enhancing Language Comprehension.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 10, 2023. 10.14569/IJACSA.2023.0141079
XI. Araddhana Arvind Deshmukh, et al. “Event-based Smart Contracts for Automated Claims Processing and Payouts in Smart Insurance” International Journal of Advanced Computer Science and Applications (IJACSA), 15(4), 2024. 10.14569/IJACSA.2024.0150486
XII. Aradhana Sahu, et al. “Federated LSTM Model for Enhanced Anomaly Detection in Cyber Security: A Novel Approach for Distributed Threat” International Journal of Advanced Computer Science and Applications (IJACSA), 15(6), 2024. 10.14569/IJACSA.2024.01506125
XIII. Arifuzzaman, M., M. Alazab, and J. Bailey. “Security and Privacy Issues in IoT-Based Healthcare Clouds: A Comprehensive Survey.” IEEE Access, vol. 5, 2017, pp. 18414–18431. 10.1109/ACCESS.2017.2753445
XIV. Babu, S. M., A. J. Lakshmi, and B. T. Rao. “A Study on Cloud Based Internet of Things: CloudIoT.” Proceedings of the Global Conference on Communication Technologies (GCCT), IEEE, 2015, pp. 60–65. 10.1109/GCCT.2015.7342681
XV. Baker El-Ebiary, Y. A. “The Effect of Organizational Factors, Technology, and Social Influences on E-Government Adoption in Jordan.” Proceedings of the International Conference on Smart Computing and Electronic Enterprise (ICSCEE), IEEE, 2018, pp. 1–4. 10.1109/ICSCEE.2018.8538394
XVI. Baker El-Ebiary, Y. A., et al. “Blockchain as a Decentralized Communication Tool for Sustainable Development.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 127–133. 10.1109/ICSCEE50312.2021.9497910
XVII. Baker El-Ebiary, Y. A., et al. “Determinants of Customer Purchase Intention Using Zalora Mobile Commerce Application.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 159–163. 10.1109/ICSCEE50312.2021.9497995
XVIII. Baker El-Ebiary, Y. A., et al. “E-Government and E-Commerce Issues in Malaysia.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 153–158. https://doi.org/10.1109/ICSCEE50312.2021.9498092
XIX. Baker El-Ebiary, Y. A., et al. “Mobile Commerce and Its Apps: Opportunities and Threats in Malaysia.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 180–185. 10.1109/ICSCEE50312.2021.9498228
XX. Baker El-Ebiary, Y. A., et al. “Track Home Maintenance Business Centers with GPS Technology in the IR 4.0 Era.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 134–138. 10.1109/ICSCEE50312.2021.9498070
XXI. Bamansoor, S., et al. “Efficient Online Shopping Platforms in Southeast Asia.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 164–168. 10.1109/ICSCEE50312.2021.9497901
XXII. Bamansoor, S., et al. “Evaluation of Chinese Electronic Enterprise from Business and Customers Perspectives.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 169–174. 10.1109/ICSCEE50312.2021.9498093
XXIII. Choo, K. K. R., P. Vinod, and E. Rokon. “Security and Privacy in Cloud-Assisted Internet of Things (IoT): A Survey.” IEEE Communications Surveys & Tutorials, vol. 22, no. 1, 2020, pp. 447–469. 10.1109/COMST.2019.2935802
XXIV. Deeba, K., et al. “Optimizing Crop Yield Prediction in Precision Agriculture with Hyperspectral Imaging-Unmixing and Deep Learning.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 12, 2023. 10.14569/IJACSA.2023.0141261
XXV. Farooq, M. O., F. K. Hussain, and M. B. Amin. “Cloud-Based Security and Privacy Preserving Mechanisms for IoT Systems: A Survey.” IEEE Access, vol. 6, 2018, pp. 16592–16629. 10.1109/ACCESS.2018.2814178
XXVI. Ganesh Khekare, et al. “Optimizing Network Security and Performance Through the Integration of Hybrid GAN-RNN Models in SDN-Based Access Control.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 12, 2023. 10.14569/IJACSA.2023.0141262
XXVII. Gharaibeh, A., A. Khreishah, and I. Khalil. “A Survey of Techniques for IoT Communication, Security, and Privacy.” IEEE Communications Surveys & Tutorials, vol. 22, no. 3, 2020, pp. 2034–2068. 10.1109/COMST.2020.2975875
XXVIII. Ghanem, W. A. H. M., et al. “Metaheuristic Based IDS Using Multi-Objective Wrapper Feature Selection.” Advances in Cyber Security, Springer, 2021. 10.1007/978-981-33-6835-4_26
XXIX. Hasan, Mohammad Kamrul, et al. “Lightweight Cryptographic Algorithms for Guessing Attack Protection in Complex IoT Applications.” Complexity, 2021, Article ID 5540296. 10.1155/2021/5540296
XXX. Hilles, S. M. S., et al. “Adaptive Latent Fingerprint Image Segmentation and Matching Using Chan-Vese Technique.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 2–7. 10.1109/ICSCEE50312.2021.9497996
XXXI. Hilles, S. M. S., et al. “Latent Fingerprint Enhancement and Segmentation Technique Based on Hybrid Edge Adaptive DTV Model.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 8–13. 10.1109/ICSCEE50312.2021.9498025
XXXII. Hong, H. G., and Y. Kim. “A Lightweight and Secure Authentication Scheme for IoT Devices in Cloud Environments.” IEEE Internet of Things Journal, vol. 10, no. 5, 2023, pp. 4280–4289. 10.1109/JIOT.2022.3196429
XXXIII. Islam, S. M. R., and S. Nuzhat. “A Blockchain-Based Security Framework for IoT and Cloud Integration.” Proceedings of ICIoT 2020, IEEE, 2020. 10.1109/ICIoT49017.2020.9259799
XXXIV. Jang, W., and J. Jang. “Security Architecture for IoT and Cloud Integration Using Blockchain.” Proceedings of CloudCom 2019, IEEE, 2019. 10.1109/CloudCom2019.00057
XXXV. Jukić, O., I. Špeh, and I. Heđi. “Cloud-Based Services for the Internet of Things.” Proceedings of MIPRO 2018, IEEE, 2018, pp. 372–377. 10.23919/MIPRO.2018.8400114
XXXVI. Jusoh, J. A., et al. “Track Student Attendance at a Time of the COVID-19 Pandemic Using Location-Finding Technology.” Proceedings of ICSCEE 2021, IEEE, 2021, pp. 147–152. 10.1109/ICSCEE50312.2021.9498043
XXXVII. Khan, S. U., and S. Hassan. “A Comprehensive Survey of Security and Privacy in Internet-of-Things (IoT) Devices.” IEEE Communications Surveys & Tutorials, vol. 21, no. 3, 2019, pp. 2791–2835. 10.1109/COMST.2019.2905611
XXXVIII. Khodaei, M., and H. R. Rabiee. “Cloud-IoT Integration: A Survey.” IEEE Internet of Things Journal, vol. 6, no. 6, 2019, pp. 11289–11313. 10.1109/JIOT.2019.2923475
XXXIX. Koo, J., et al. “Security Architecture for Cloud-Based Command and Control System in IoT Environment.” Applied Sciences, vol. 10, no. 3, 2020, p. 1035. 10.3390/app10031035
XL. Lakshmi, K., et al. “Efficiency Analysis of Firefly Optimization-Enhanced GAN-Driven Model for Melanoma Classification.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 11, 2023. 10.14569/IJACSA.2023.0141175
XLI. Meraj, S. T., et al. “A Diamond Shaped Multilevel Inverter with Dual Mode of Operation.” IEEE Access, vol. 9, 2021, pp. 59873–59887. 10.1109/ACCESS.2021.3067139
XLII. Mohamad, M. B., et al. “Enterprise Problems and Proposed Solutions Using the Concept of E-Commerce.” Proceedings of the 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), IEEE, 2021, pp. 186–192. 10.1109/ICSCEE50312.2021.9498197
XLIII. Mukhedkar, Moresh, et al. “Enhanced Land Use and Land Cover Classification Through Human Group-Based Particle Swarm Optimization–Ant Colony Optimization Integration with Convolutional Neural Network.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 11, 2023. 10.14569/IJACSA.2023.0141142
XLIV. Mukhedkar, Moresh, et al. “Feline Wolf Net: A Hybrid Lion–Grey Wolf Optimization Deep Learning Model for Ovarian Cancer Detection.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 9, 2023. 10.14569/IJACSA.2023.0140962
XLV. Narayan Das, Nripendra, et al. “Utilizing Deep Convolutional Neural Networks and Non-Negative Matrix Factorization for Multi-Modal Image Fusion.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 9, 2023. 10.14569/IJACSA.2023.0140963
XLVI. Naramala, Venkateswara Rao, et al. “Enhancing Diabetic Retinopathy Detection Through Machine Learning with Restricted Boltzmann Machines.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 9, 2023. 10.14569/IJACSA.2023.0140961
XLVII. Pathmanathan, P. R., et al. “The Benefit and Impact of E-Commerce in Tourism Enterprises.” Proceedings of the 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE), IEEE, 2021, pp. 193–198. 10.1109/ICSCEE50312.2021.9497947
XLVIII. Pawar, B., et al. “Multi-Scale Deep Learning-Based Recurrent Neural Network for Improved Medical Image Restoration and Enhancement.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 10, 2023. 10.14569/IJACSA.2023.0141088
XLIX. Preethi, K. N., et al. “Enhancing Startup Efficiency: Multivariate DEA for Performance Recognition and Resource Optimization in a Dynamic Business Landscape.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 8, 2023. 10.14569/IJACSA.2023.0140869
L. Rahman, M. A., and M. S. Hossain. “Towards Cloud-Based Framework for Security and Privacy of IoT Systems.” Proceedings of the IEEE HPCC/SmartCity/DSS Conference, IEEE, 2017, pp. 800–807. 10.1109/HPCC-SmartCity-DSS.2017.119
LI. Raj, R. S., and H. K. D. Sarma. “A Survey on Security and Privacy Issues in IoT Integrated Cloud Environment.” Proceedings of the International Conference on Communication and Electronics Systems (ICCES), IEEE, 2018, pp. 442–446. 10.1109/CESYS.2018.8627207
LII. Ravi Prasad, et al. “Forecasting Electricity Consumption Through a Fusion of Hybrid Random Forest Regression and Linear Regression Models Utilizing Smart Meter Data.” Journal of Theoretical and Applied Information Technology, vol. 101, no. 21, 2023. https://www.jatit.org/volumes/Vol101No21/6Vol101No21.pdf
LIII. Sengupta, S., and S. Chakraborty. “A Survey on Security and Privacy Issues of Internet of Things (IoT) and Cloud Computing.” Proceedings of the International Conference on Computing, Communication and Automation (ICCCA), IEEE, 2017, pp. 708–713. 10.1109/CCAA.2017.8229871
LIV. Sundaramoorthy, K., et al. “Hybrid Optimization with Recurrent Neural Network-Based Medical Image Processing for Predicting Interstitial Lung Disease.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 4, 2023. 10.14569/IJACSA.2023.0140462
LV. Suresh Babu Jugunta, et al. “Exploring the Insights of Bat Algorithm-Driven XGB-RNN (BARXG) for Optimal Fetal Health Classification in Pregnancy Monitoring.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 11, 2023. 10.14569/IJACSA.2023.0141174
LVI. Suresh Babu Jugunta, et al. “Unleashing the Potential of Artificial Bee Colony Optimized RNN–Bi-LSTM for Autism Spectrum Disorder Diagnosis.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 11, 2023. 10.14569/IJACSA.2023.0141173
LVII. Sweety Bakyarani, E., et al. “Optimizing Network Intrusion Detection with a Hybrid Adaptive Neuro-Fuzzy Inference System.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 11, 2023. 10.14569/IJACSA.2023.0141131
LVIII. Tanwar, S., R. U. Khan, and A. Kaur. “A Trustworthy and Efficient Data Fusion Framework for Secure IoT in Cloud Environment.” IEEE Internet of Things Journal, vol. 8, no. 16, 2021, pp. 12964–12974. 10.1109/JIOT.2021.3106535
LIX. Tarshany, Y. M. A., Y. Al Moaiad, and Y. A. Baker El-Ebiary. “Legal Maxims Artificial Intelligence Application for Sustainable Architecture and Interior Design.” Proceedings of ETSAIDE 2022, IEEE, 2022, pp. 1–4. 10.1109/ETSAIDE53569.2022.9906357
LX. Tiwari, Atul, et al. “Optimized Ensemble of Hybrid RNN–GAN Models for Accurate and Automated Lung Tumour Detection from CT Images.” International Journal of Advanced Computer Science and Applications, vol. 14, no. 7, 2023 10.14569/IJACSA.2023.0140769
LXI. Wahsheh, F. R., et al. “E-Commerce Product Retrieval Using Knowledge from GPT-4.” Proceedings of the International Conference on Computer Science and Emerging Technologies (CSET), IEEE, 2023, pp. 1–8. 10.1109/CSET58993.2023.10346860
LXII. Wahsheh, F. R., et al. “An Evaluation and Annotation Methodology for Product Category Matching in E-Commerce Using GPT.” Proceedings of CSET 2023, IEEE, 2023, pp. 1–6. 10.1109/CSET58993.2023.10346684
LXIII. Wang, H., Q. Zhang, and J. Wang. “A Lightweight Cloud-Based Data Integrity Verification Scheme for IoT Devices.” IEEE Internet of Things Journal, vol. 10, no. 2, 2023, pp. 1315–1323. 10.1109/JIOT.2022.3147475
LXIV. Wang, S., and L. D. Xu. “A Survey on the Internet of Things Security.” Proceedings of the IEEE GreenCom Conference, IEEE, 2018, pp. 21–27. 10.1109/GreenCom-CPSCom.2018.00010
LXV. Wazid, M., et al. “Authentication in Cloud-Driven IoT-Based Big Data Environment: Survey and Outlook.” Journal of Systems Architecture, vol. 97, 2019, pp. 185–196. 10.1016/j.sysarc.2018.12.005
LXVI. Zawaideh, F. H., et al. “Blockchain Solution for SMEs Cybersecurity Threats in E-Commerce.” Proceedings of CSET 2023, IEEE, 2023, pp. 1–7. 10.1109/CSET58993.2023.10346628
LXVII. Zawaideh, F. H., et al. “E-Commerce Supply Chains with Considerations of Cyber-Security.” Proceedings of CSET 2023, IEEE, 2023, pp. 1–8. 10.1109/CSET58993.2023.10346738
LXVIII. Zhang, Y., et al. “Secure and Lightweight Cloud-Based Key Management Scheme for IoT Devices.” IEEE Internet of Things Journal, vol. 10, no. 3, 2023, pp. 2497–2506. 10.1109/JIOT.2022.3131279
LXIX. Zhang, H., Q. Wang, and J. Wang. “A Lightweight Cloud-Based Data Integrity Verification Scheme for IoT Devices.” IEEE Internet of Things Journal, vol. 10, no. 2, 2023, pp. 1315–1323. 10.1109/JIOT.2022.3147475
LXX. Hasan, M. K., et al. “Lightweight Cryptographic Algorithms for Guessing Attack Protection in Complex Internet of Things Applications.” Complexity, 2021, Article ID 5540296. 10.1155/2021/5540296