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Karamta, Miren
- Enhancement of Cloud Security Using Snort
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Authors
Affiliations
1 GTU - Graduate School of Engineering & Technology, Gandhinagar, Gujarat, IN
2 Bhaskaracharya Institute for Space Applications and Geo-Informatics, Gandhinagar, Gujarat, IN
1 GTU - Graduate School of Engineering & Technology, Gandhinagar, Gujarat, IN
2 Bhaskaracharya Institute for Space Applications and Geo-Informatics, Gandhinagar, Gujarat, IN
Source
International Journal of Distributed and Cloud Computing, Vol 7, No 1 (2019), Pagination: 25-29Abstract
Cloud computing is a paradigm that enables access to a shared pool of computing resources for cloud users in an on-demand and pay-per-use, fashion. Despite the existence of such merits, there are Security issues such as data integrity, users’ confidentiality, and service availability because of its open and distributed architecture that place restrictions on the usage of cloud computing. A preventive approach is to identify such issues and eliminate before it can cause the serious impact to the cloud users. Intrusion Detection System (IDS) is the most commonly used mechanism to detect attacks on cloud. In this paper snort IDS method is used in cloud environment to detect intrusions. Next step is enforcing snort intrusion detection system in cloud environment and new policies within the snort to improving the extent of security within the cloud environment and studying the snort log report, to see that it nicely alert the message in log record. So that administrator can take similarly protection selections associated with attacks.Keywords
Cloud Security, Intrusion Detection System, Snort.
References
- Y. Mehmood, M. A. Shibli, U. Habiba, and R. Masood, “Intrusion detection system in cloud computing: Challenges and opportunities,” 2013 2nd National Conference on Information Assurance (NCIA), IEEE, 2013.
- K. Kato, and V. Klyuev, “Development of a network intrusion detection system using Apache Hadoop and Spark,” 2017 IEEE Conference on Dependable and Secure Computing, IEEE, 2017.
- R. V. Gaddam, and M. Nandhini, “Analysis of various intrusion detection systems with a model for improving snort performance,” Indian Journal of Science and Technology, vol. 10, no. 20, May 2017.
- G. Nenvani, and H. Gupta, “A survey on attack detection on cloud using supervised learning techniques,” 2016 Symposium on Colossal Data Analysis and Networking (CDAN), IEEE, 2016.
- Z. Chiba, N. Abghour, K. Moussaid, A. Elomri, and M. Rida, “A cooperative and hybrid network intrusion detection framework in cloud computing based on snort and optimized back propagation neural network,” Procedia Computer Science, vol. 83, pp. 1200-1206, 2016.
- Y. Mehmood, M. A. Shibli, U. Habiba, and R. Masood, “Distributed intrusion detection system using mobile agents in cloud computing environment,” 2015 Conference on Information Assurance and Cyber Security (CIACS), IEEE, 2015.
- C. Mazzariello, R. Bifulco, and R. Canonico, “Integrating a network IDS into an open source cloud computing environment,” 2010 Sixth International Conference on Information Assurance and Security (IAS), IEEE, 2010.
- J. Cheon, and T.-Y. Choe, “Distributed processing of snort alert log using Hadoop,” International Journal of Engineering and Technology, vol. 5, no. 3, pp. 2685-2690, 2013.
- P. G. Prathibha, and E. D. Dileesh, “Design of a hybrid intrusion detection system using snort and Hadoop,” International Journal of Computer Applications, vol. 73, no. 10, pp. 5-10, 2013.
- M. Idhammad, K. Afdel, and M. Belouch, “Distributed intrusion detection system for cloud environments based on data mining techniques,” Procedia Computer Science, vol. 127, pp. 35-41, 2018.
- Y. Lee, and Y. Lee, “Detecting DDoS attacks with hadoop,” Proceedings of the ACM CoNEXT Student Workshop, ACM, 2011.
- A. Fuchsberger, “Intrusion detection systems and intrusion prevention systems,” Information Security Technical Report, vol. 10, no. 3, pp. 134-139, 2005.
- S. Potteti, and N. Parati, “An innovative intrusion detection system using snort for cloud environment,” International Journal of Innovative Research in Computer and Communication Engineering, vol. 3, no. 6, pp. 5679-5687, June 2015.
- C. Ambikavathi, and S. K. Srivatsa, “Integrated intrusion detection approach for cloud computing,” Indian Journal of Science and Technology, vol. 9, no. 22, June 2016.
- X. Lin, P. Wang, and B. Wu, “Log analysis in cloud computing environment with Hadoop and Spark,” 2013 5th IEEE International Conference on Broadband Network & Multimedia Technology (IC-BNMT), IEEE, 2013.
- J. Therdphapiyanak, and K. Piromsopa, “Applying Hadoop for log analysis toward distributed IDS,” Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication, ACM, 2013.
- A. Patel, M. Taghavi, K. Bakhtiyari, and J. Celestino Jr., “An intrusion detection and prevention system in cloud computing: A systematic review,” Journal of Network and Computer Applications, vol. 36, no. 1, pp. 25-41, 2013.
- S. O. Al-Mamory, “Speed enhancement of snort network intrusion detection system,” Journal of Babylon University/Pure and Applied Sciences, vol. 20, no. 1, pp. 10-19, 2012.
- Snort-network intrusion detection and prevention system. Available: https://www.snort.org/
- Basics of intrusion detection systems. Available: https://www.hackthis.co.uk/articles/basics-of-intrusiondetection-systems