Implementasi Network Intrusion Detection System (NIDS) Dalam Sistem Keamanan Open Cloud Computing

Main Article Content

Muqorobin Muqorobin Zul Hisyam Moch Mashuri Hanafi Hanafi Yudhi Setiyantara

Abstract

Security is the most important part of computer network technology systems. Among the technologies that utilize networks are cloud computing. One cloud computing provider such as eucalyptus uses a firewall for system security. The use of a firewall on the system cannot monitor and analyze traffic that is inside the cloud server and does not give a warning when an attack occurs. The purpose of this study is that researchers will implement a network intrusion detection system (NIDS) in cloud computing and mirroring traffic on switches. Intrusion detection system (IDS) is a security technology that can analyze network traffic and detect traffic if an attack is indicated. NIDS are placed hosted differently from cloud computing servers. With the switch mirroring traffic method, traffic will be directed to NIDS so that NIDS can record all network traffic originating from outside the cloud server or traffic between virtual machines within the cloud server. The test results of attacks with 2 scenarios, namely attacks from outside and from within the cloud system, then NIDS is able to provide an alert response to traffic attacks.

Downloads

Download data is not yet available.

Article Details

Section
Articles

References

Ali, K. M., Venus, W., & Rababaa, M. S. Al. (2009). The affect of fuzzification on neural networks intrusion detection system. 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, 1236–1241. https://doi.org/10.1109/ICIEA.2009.5138399

Ashari, A., & Setiawan, H. (2011). Cloud Computing : Solusi ICT ? Jurnal Sistem Informasi (JSI), VOL. 3, NO, 336–345.

Bao, F., Chen, I. R., Chang, M. J., & Cho, J. H. (2012). Hierarchical trust management for wireless sensor networks and its applications to trust-based routing and intrusion detection. IEEE Transactions on Network and Service Management,9(2),169–183. https://doi.org/10.1109/TCOMM.2012.031912. 110179

Barbosa, R. R. R., & Pras, A. (2010). Intrusion detection in SCADA networks. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6155 LNCS, 163–166. https://doi.org/10.1007/978-3-642-13986-4_23

Bastani, F. B., & Houston, H. (1994). Reliability of Systems with Fuzzy-Failure Criterion, 442–448. https://doi.org/10.1109/WCSP.2012.6542908

Bellettini, C., & Rrushi, J. L. (2008). A product machine model for anomaly detection of interposition attacks on cyber-physical systems. IFIP International Federation for Information Processing, 278, 285–299. https://doi.org/10.1007/978-0-387-09699-5_19

Ulfa, M. (2013). Implementasi Intrusion Detection System ( IDS ) Di Jaringan Universitas Bina Darma. Jurnal Ilmiah MATRIK, 15(12), 105–118. https://doi.org/10.1145/1809049.1809052