• Bhavya Deep Associate Professor, Department of Computer Science, Bhaskaracharya College of Applied Sciences, University of Delhi, Delhi, India
  • Aman Jain Student, Department of Computer Science, Bhaskaracharya College of Applied Sciences, University of Delhi, Delhi, India



Intrusion Detection System (IDS), Security, Threat, Cloud Computing, HMM

Abstract [English]

Cloud computing is one of the fast-growing technologies in recent times. People are adopting cloud services often and they do not possess any other substitute for its services. At the same time, users have to be aware of privacy and security issues in the cloud environment. Due to the distributed nature of cloud computing, multi-domain support, and multi-user platform, the cloud-based system is more vulnerable to security threats. Security threats can be distributed denial of service attacks and intrusion prospects. Thus, organizations need to have techniques like intrusion detection as well as prevention, firewalls, encryption, authentication, etc. for securing the stored information on the cloud. Intruders attempt to identify loopholes to break security. For that, organizations are adopting the system for intrusion detection and prevention to provide privacy and security in the cloud environment. Attacks whether internal or external must be prevented and thus it is significant to adopt the technique of preventing and detection system for identifying intrusion. Therefore, this research intends to study the prevention and detection of intrusion in the cloud environment.


Download data is not yet available.


Bedi, P., Deep, B., Kumar, P., and Sarna, P. (2018). Comparative Study of Opennebula, Cloudstack, Eucalyptus and Openstack. International Journal of Distributed and Cloud Computing, 6(1), 37-42 ISSN : 2321-6840.

Deep, B., Mathur, I., and Joshi, N. (2020). Estimated Power Cost Comparison of Physical Server Vs Virtualized Server In A Data Center. International Journal of Advanced Science and Technology, 29(06), 5335-5342.

Hassan, M. M. M. (2013). Current Studies on Intrusion Detection System, Genetic Algorithm and Fuzzy Logic. International Journal of Distributed and Parallel Systems, 4(2).

Jaiganesh, V., Mangayarkarasi, S., and Sumathi, P. (2013). Intrusion Detection Systems: A Survey and Analysis of Classification Techniques. International Journal of Advanced Research in Computer and Communication Engineering, 2(4).

Kodada, B. B. (2011). Intrusion Detection System Inside Grid Computing Environment (IDS-IGCE). International Journal of Grid Computing and Applications, 2(4), 27-36.

Kumar, P. P., and Naik, B. K. (2013). A Survey on Cloud Based Intrusion Detection System, International Journal of Software And Web Sciences, 4(2), 98-102.

Megha, P., and Meniya, A. (2013). Prevent DDOS Attack Using Intrusion Detection System In Cloud. International Journal of Computers And Applications, 2(3).

Modi, C., Patel, D., Borisaniya, B., Patel, H., Patel, A., and Rajarajan, M. (2013). A Survey of Intrusion Detection Techniques In Cloud. Journal of Network and Computer Applications, 36(1), 42-57.

Padmakumari, P., Surendra, K., Sowmya, M., and Sravya, M. (2014). Effective Intrusion Detection System for Cloud Architecture. ARPN Journal of Engineering and Applied Sciences, 9(11).

Prasad, M., Tripathi, S., and Dahal, K. (2020). An Efficient Feature Selection Based Bayesian and Rough Set Approach for Intrusion Detection. Applied Soft Computing, 87, 105980.

Raghav, I., Chhikara, S., and Hasteer, N. (2013). Intrusion Detection and Prevention In Cloud Environment: A Systematic Review. International Journal of Computer Applications, 68(24), 7-11.

Ram, S. M., Velmurugan, N., and Thirukumaran, S. (2012). Effective Analysis of Cloud Based Intrusion Detection System. International Journal of Computer Applications and Information Technology, 1(2).

Shelke, K. P., Sontakke, S., and Gawande, D. A. (2012). Intrusion Detection System for Cloud Computing. International Journal of Scientific and Technology Research, 1(4).

Tayyebi, Y., and Bhilare, S. D. (2015). Cloud Security Through Intrusion Detection System (IDS) : Review of Existing Solutions. International Journal of Emerging Trends and Technology In Computer Science, 4(6).

Vinchurkar, P. D., and Reshamwala. (2012). A Review of Intrusion Detection System Using Neural Network and Machine Learning Technique. International Journal of Engineering Science And Innovative Technology, 1(2).

Zhang, Z., Wen, J., Zhang, J., Cai, X., and Xie, L. (2020). A Many Objective-Based Feature Selection Model For Anomaly Detection in Cloud Environment. In IEEE Access, 8, 60218-60231.




How to Cite

Deep, B., & Jain, A. (2023). PREVENTION AND DETECTION OF INTRUSION IN CLOUD USING HIDDEN MARKOV MODEL. International Journal of Research -GRANTHAALAYAH, 11(2), 40–46.