Cloud computing environment based hierarchical anomaly intrusion detection system using artificial neural network
Nowadays, computer technology is essential to everyday life, including banking, education, entertainment, and communication. Network security is essential in the digital era, and detecting intrusion threats is the most difficult problem. As a result, the network is monitored for unusual activity using this hierarchical anomaly intrusion detection system, and when these actions are detected, an alert is generated. This hierarchical anomaly intrusion detection system, which uses artificial neural network (ANN) and is implemented on a cloud computing environment, analyzes data even in the high levels of traffic and protects computer networks and data from malicious activity. As a result, this system shows better detection, accuracy, and precision rates.
Authors
- Koppisetti Giridhar (ORCID: https://orcid.org/0000-0001-8369-9985)
- Gajjala Venkata Ramesh Babu
- Lakshmeelavanya Alluri
- B. J. Job Karuna Sagar
- Giddaluru Somasekhar
- Garapati Swarna Latha
- Naresh Dondapati (ORCID: https://orcid.org/0000-0001-6243-8380)
Institutions
- Rajamangala University of Technology Isan (TH)
- Elgin Community College (US)
- Sri Venkateswara University (IN)
- Aditya Birla (India) (IN)
- SRKR Engineering College
Publication Details
- Journal
- International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
- Published
- 2024-11-18
- DOI
- https://doi.org/10.11591/ijece.v15i1.pp1209-1217
- Citations
- 4
- Primary Topic
- Network Security and Intrusion Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.40